**Meet the editors**

Professor Taeko N. Wydell is a professor in cognitive neuroscience/neuropsychology, and Co-Director of the Centre for Cognition and Neuroimaging (CCNI) at Brunel University, UK. Her research interests include: cognitive and neural processes involved in language, in particular, reading using behavioural and brain imaging (EEG, MEG, & fMRI) techniques; normal and

impaired language/reading processes including developmental dyslexia, acquired dyslexia (with neurological patients), and SLI (Specific Language impairment) in different languages (e.g., Chinese, English, Finnish, & Japanese) and bilingual's language/reading processes. Professor Wydell is an internationally recognised researcher who has established several international collaborations in Europe and Asia-Pacific. She has many publications in prestigious journals such as Cognition, Cortex, JEP:LMC, J. of Cognitive Neuroscience, and Reading & Writing.

Dr Liory Fern-Pollak (BSc, MSc, PhD) is a cognitive neuroscientist at the Centre for Cognition and Neuroimaging (CCNI) of Brunel University, West London, investigating the neural correlates of multilingual language processing, reading and dyslexia in adults and children. Dr Fern-Pollak teaches biopsychology and statistics at Birkbeck, the Institute of Education,

University of London and Kingston University.

Contents

**Preface IX** 

Taeko N. Wydell

Juan E. Jiménez

Chapter 1 **Cross-Cultural/Linguistic Differences** 

Chapter 2 **Typical and Dyslexic Development** 

Chapter 3 **The Role of Phonological Processing** 

Chapter 4 **Phonological Restriction Knowledge** 

Chapter 5 **Antisaccades in Dyslexic Children: Evidence** 

Marie Lallier and Sylviane Valdois

Chapter 8 **Depression in Dyslexic Children Attending** 

Emmanuel Bui-Quoc and Magali Seassau

Norbert Maïonchi-Pino

Chapter 6 **Sequential** *Versus* **Simultaneous** 

Chapter 7 **The Contribution of Handwriting** 

Diane Montgomery

Tamara Leonova

Hua Shu and Hong Li

**in Learning to Read Chinese 15** 

**in Dyslexia in the Spanish Language 29** 

**in Dyslexia: Universal or Language-Specific? 47** 

**for Immaturity of Oculomotor Cortical Structures 61**  Maria Pia Bucci, Naziha Nassibi, Christophe-Loic Gerard,

**Processing Deficits in Developmental Dyslexia 73** 

**Specialized Schools: A Case of Switzerland 147** 

**and Spelling Remediation to Overcoming Dyslexia 109** 

**in the Prevalence of Developmental Dyslexia** 

**and the Hypothesis of Granularity and Transparency 1** 

## Contents

#### **Preface** XI


X Contents

```
Chapter 9 Dyslexia and Self-Esteem: Stories of Resilience 163 
Jonathan Glazzard
```
## Preface

This book covers all aspects of developmental dyslexia from the underlying aetiology to currently available, routinely used diagnostic tests and intervention strategies, and also addresses important social, cultural and quality of life issues of those with developmental dyslexia.

The ability to read and write is a remarkable trait of humanity. This trait enables us to convey spoken language through the conversion of symbols composed of lines, dashes, circles and dots, into words, phrases and sentences. This ability seems to have emerged around 3,500 years ago; in terms of evolution, this is a relatively recent phenomenon in human history, which dates back some 200,000 years! Unlike spoken language, learning to read and write does not happen through mere exposure during infancy, but requires systematic instruction and applied study, which normally begins in early childhood. While most children are able to reach a skilled level of reading and writing within 5-6 years, some struggle to acquire the skill and may be subsequently diagnosed as having Developmental Dyslexia. This term stands in contrast to Acquired Dyslexia, which is associated with brain damage in individuals who prior to the incident which caused the condition had adequate reading skills.

Developmental Dyslexia is characterised primarily by reading difficulty in the absence of any profound sensory, neurological and intellectual disorders or socio-cultural factors. However, it may co-occur with other developmental disorders such as attention deficit hyperactivity disorder (ADHD), dyscalculia, or dyspraxia, and may therefore manifest as delayed language production, spelling difficulties, and/or difficulties associating sounds and meanings with written words. The precise incidence of Developmental Dyslexia is not known, although it is thought that up to 12% of school children in some countries may face reading difficulties, with higher incidence in boys than girls.

Although now widely regarded as a neurobiological disorder with genetic origin, Developmental Dyslexia may be caused by deficits in auditory processing or visual processing skills, or visual attentional skills as well as a deficit in visual or verbal short-term memory, which can affect its manifestation in isolation or in conjunction. Moreover, different languages exert different cognitive demands on the process of reading. For example, reading in Spanish or Italian, where a close relationship exists between letters and their corresponding sounds, words can be pronounced correctly by assigning to each written consonant the sound of the vowel that follows. In contrast, reading in English often requires prior knowledge of the correct pronunciation, since the phonology of a large proportion of words is not consistent with their spelling (e.g., *pint* vs. hint, lint, mint, tint; *bread, head* vs. *bead; mead* vs. *steak*; *bough* vs. *cough* vs. *dough* vs. *through* vs. *thorough*; *colonel*; *gauge*; *yacht*). In logographic writing-systems such as Chinese and Japanese Kanji, phonemes do not form part of written text since these languages use intricate characters to directly convey meaning. Reading in these languages therefore requires rote memorization and a complete understanding of the combination of strokes included in each character. Dyslexia may therefore manifest itself differently for speakers of different languages.

Preface XI

writing and spelling both for early screening and diagnosis tools and for successful

The final two chapters touch upon the affective aspect of living with dyslexia among

**Professor Taeko N. Wydell and Dr. Liory Fern-Pollak**  Centre for Cognition and Neuroimaging (CCNI)

School of Social Sciences

Brunel University Middlesex

UK

French children in Switzerland and among British adults, respectively.

intervention.

Diagnosis of Developmental Dyslexia is a complex process, which requires intellectual, educational, speech and language, medical, and psychological evaluations, as well as a careful consideration of the properties of the particular language. Treatment is typically provided through educational support, which can help dyslexics to complete everyday reading and writing tasks through compensatory strategies, but cannot 'cure' or eliminate the underlying cause. Importantly, beyond the cognitive symptoms and the ensuing difficulty with reading and writing, Dyslexic children may suffer social exclusion, which can lead to behavioural and affective problems. Current research on Developmental Dyslexia therefore comprises various strands; some focusing on the aetiology, some on diagnosis and intervention, and others on psychological and behavioural aspects. All strands aim to provide new insight in order to facilitate early detection, efficient intervention and management of this challenging condition.

In nine chapters written by researchers from different parts of the world, this book brings together leading international research from all strands.

The first three chapters discuss the manifestation of Dyslexia in very different languages; Japanese, Chinese and Spanish, respectively, thus highlighting the effects of the orthographic properties of different languages on differential manifestation of reading difficulty.

The following three chapters explore specific cognitive and biological factors which affect the observed symptoms of Dyslexia among French speakers; namely degraded phonological representations, maturation of the oculomotor system and visual attention span. The eighth chapter provides a comprehensive review of different intervention programs used in UK schools, highlights individual differences in dyslexic children, and the difficulties they face in light of the available diagnostic tools and provision. It further proposes that beyond reading, focus must be shifted towards writing and spelling both for early screening and diagnosis tools and for successful intervention.

X Preface

languages.

this challenging condition.

reading difficulty.

reading. For example, reading in Spanish or Italian, where a close relationship exists between letters and their corresponding sounds, words can be pronounced correctly by assigning to each written consonant the sound of the vowel that follows. In contrast, reading in English often requires prior knowledge of the correct pronunciation, since the phonology of a large proportion of words is not consistent with their spelling (e.g., *pint* vs. hint, lint, mint, tint; *bread, head* vs. *bead; mead* vs. *steak*; *bough* vs. *cough* vs. *dough* vs. *through* vs. *thorough*; *colonel*; *gauge*; *yacht*). In logographic writing-systems such as Chinese and Japanese Kanji, phonemes do not form part of written text since these languages use intricate characters to directly convey meaning. Reading in these languages therefore requires rote memorization and a complete understanding of the combination of strokes included in each character. Dyslexia may therefore manifest itself differently for speakers of different

Diagnosis of Developmental Dyslexia is a complex process, which requires intellectual, educational, speech and language, medical, and psychological evaluations, as well as a careful consideration of the properties of the particular language. Treatment is typically provided through educational support, which can help dyslexics to complete everyday reading and writing tasks through compensatory strategies, but cannot 'cure' or eliminate the underlying cause. Importantly, beyond the cognitive symptoms and the ensuing difficulty with reading and writing, Dyslexic children may suffer social exclusion, which can lead to behavioural and affective problems. Current research on Developmental Dyslexia therefore comprises various strands; some focusing on the aetiology, some on diagnosis and intervention, and others on psychological and behavioural aspects. All strands aim to provide new insight in order to facilitate early detection, efficient intervention and management of

In nine chapters written by researchers from different parts of the world, this book

The first three chapters discuss the manifestation of Dyslexia in very different languages; Japanese, Chinese and Spanish, respectively, thus highlighting the effects of the orthographic properties of different languages on differential manifestation of

The following three chapters explore specific cognitive and biological factors which affect the observed symptoms of Dyslexia among French speakers; namely degraded phonological representations, maturation of the oculomotor system and visual attention span. The eighth chapter provides a comprehensive review of different intervention programs used in UK schools, highlights individual differences in dyslexic children, and the difficulties they face in light of the available diagnostic tools and provision. It further proposes that beyond reading, focus must be shifted towards

brings together leading international research from all strands.

The final two chapters touch upon the affective aspect of living with dyslexia among French children in Switzerland and among British adults, respectively.

#### **Professor Taeko N. Wydell and Dr. Liory Fern-Pollak**

Centre for Cognition and Neuroimaging (CCNI) School of Social Sciences Brunel University Middlesex UK

**1** 

*UK* 

Taeko N. Wydell

**Cross-Cultural/Linguistic Differences in the** 

**Prevalence of Developmental Dyslexia and the** 

In this chapter, cross-cultural and cross-linguistic differences in the prevalence of developmental dyslexia will be discussed. In order to account for the differences, the Hypothesis of Granularity and Transparency postulated by Wydell and Butterworth (1999)

Developmental dyslexia is defined as a failure to acquire reading skills, despite adequate intelligence, education and sociocultural opportunity (Chrichey, 1975), and it is generally accepted that it is a neurobiological disorder with a genetic origin (e.g., Eden & Moat, 2002; Fisher & DeFries, 2002). It has been reported that up to 10 – 12% of children in the English speaking world suffer from developmental dyslexia (e.g., Shaywitz, Shaywitz, Fletcher, & Escobar, 1990; Snowling, 2000). Extensive research has been conducted in order to ascertain the causes of dyslexia (and subsequently to develop intervention programmes), since dyslexia sufferers form a large minority group, and yet there seems to be no consensus

Ramus (2003) reviewed recent empirical studies in relation to major theories accounting for the causes of developmental dyslexia, such as for example, *the auditory processing* (in particular, *rapid or temporal processing) deficit hypothesis* (e.g., Tallal, 1980; Share, Jorm, MacLean, & Matthews, 2002); *the visual processing deficit hypothesis including magnocellular dysfunction hypothesis* (e.g., Hansen, Stein, Orde, Winter and Talcott, 2001; Stein, 2001; 2003); *the motor control deficit hypothesis* (e.g., Wolf, 2002) including *the cerebellar dysfunction hypothesis* (e.g., Nicholson, Fawcett, & Dean, 2001); *the general sensorimotor processing deficit hypothesis* (e.g., Laasonen, Service, & Virsu, 2001; 2002) and the *phonological processing deficit hypothesis* (e.g., Ramus, 2001; Snowling, 2000). In his succinctly written review, Ramus pointed out that behavioural genetic studies revealed that phonological deficits are highly heritable, whereas auditory and visual deficits are not (e.g., Davis, Gayan, Knopik, Smith, Cardon, Pennington, Olson, & DeFries, 2001; Olson & Datta, 2002), and concluded that "although the phonological deficit is still in need of a complete cognitive and neurological characterisation, the case for its causal role in the aetiology of the reading and writing

Indeed, many behavioural studies in English have found core phonological deficits in children with developmental dyslexia (e.g., Stanovich, 1988; Stanovich & Siegel, 1994;

amongst the researchers as to what causes developmental dyslexia.

disability of the great majority of dyslexic children is overwhelming" (p.216).

**1. Introduction** 

will be revisited.

**Hypothesis of Granularity and Transparency** 

*Centre for Cognition and NeuroImaging, Brunel University, Middlesex,* 

## **Cross-Cultural/Linguistic Differences in the Prevalence of Developmental Dyslexia and the Hypothesis of Granularity and Transparency**

Taeko N. Wydell *Centre for Cognition and NeuroImaging, Brunel University, Middlesex, UK* 

#### **1. Introduction**

In this chapter, cross-cultural and cross-linguistic differences in the prevalence of developmental dyslexia will be discussed. In order to account for the differences, the Hypothesis of Granularity and Transparency postulated by Wydell and Butterworth (1999) will be revisited.

Developmental dyslexia is defined as a failure to acquire reading skills, despite adequate intelligence, education and sociocultural opportunity (Chrichey, 1975), and it is generally accepted that it is a neurobiological disorder with a genetic origin (e.g., Eden & Moat, 2002; Fisher & DeFries, 2002). It has been reported that up to 10 – 12% of children in the English speaking world suffer from developmental dyslexia (e.g., Shaywitz, Shaywitz, Fletcher, & Escobar, 1990; Snowling, 2000). Extensive research has been conducted in order to ascertain the causes of dyslexia (and subsequently to develop intervention programmes), since dyslexia sufferers form a large minority group, and yet there seems to be no consensus amongst the researchers as to what causes developmental dyslexia.

Ramus (2003) reviewed recent empirical studies in relation to major theories accounting for the causes of developmental dyslexia, such as for example, *the auditory processing* (in particular, *rapid or temporal processing) deficit hypothesis* (e.g., Tallal, 1980; Share, Jorm, MacLean, & Matthews, 2002); *the visual processing deficit hypothesis including magnocellular dysfunction hypothesis* (e.g., Hansen, Stein, Orde, Winter and Talcott, 2001; Stein, 2001; 2003); *the motor control deficit hypothesis* (e.g., Wolf, 2002) including *the cerebellar dysfunction hypothesis* (e.g., Nicholson, Fawcett, & Dean, 2001); *the general sensorimotor processing deficit hypothesis* (e.g., Laasonen, Service, & Virsu, 2001; 2002) and the *phonological processing deficit hypothesis* (e.g., Ramus, 2001; Snowling, 2000). In his succinctly written review, Ramus pointed out that behavioural genetic studies revealed that phonological deficits are highly heritable, whereas auditory and visual deficits are not (e.g., Davis, Gayan, Knopik, Smith, Cardon, Pennington, Olson, & DeFries, 2001; Olson & Datta, 2002), and concluded that "although the phonological deficit is still in need of a complete cognitive and neurological characterisation, the case for its causal role in the aetiology of the reading and writing disability of the great majority of dyslexic children is overwhelming" (p.216).

Indeed, many behavioural studies in English have found core phonological deficits in children with developmental dyslexia (e.g., Stanovich, 1988; Stanovich & Siegel, 1994;

Cross-Cultural/Linguistic Differences in the Prevalence

reported by Wydell & Butterworth, 1999).

Japanese peers, as illustrated in *Table 1*.

might not be sensitive enough for these adolescent individuals.

as academic underachievers, as Hannell (2004) suggested.

which clearly indicate his phonological processing deficits.

at the end of Year-2 (aged seven), Year-6 (aged 11) and Year-9 (aged 14).

difficulties/impairments (e.g., Snowling & Griffiths, 2005).

**3. Dyslexia and the hypothesis of granularity and transparency** 

of Developmental Dyslexia and the Hypothesis of Granularity and Transparency 3

Those PPR-readers and 16 randomly selected normal readers were further tested for their skills in Word Reading, Nonword Reading, Spoonerizing, Phoneme Deletions, and Nonword Repetition. As illustrated in *Figure 1*, the results revealed that PPR-readers were significantly worse than the controls on all the tests (p>.01 – p>.0001) except for Phoneme Deletions (p=.08) and Non-word repetition (p>1). Note that Gathercole and Baddeley's (1996) Non-word Repetition test is known to be one of the most effective diagnostic tools to identify developmental dyslexia in young children. Yet, this test did not show any difference between the PPR-readers and the normal controls. This might be because the test was developed primarily to assess young children's phonological skills, and that the test

Furthermore, Wydell compared these PPR-readers' performance on SATs1 in English, Science and Mathematics individually, with that of the normal controls using z-scores2.

The results revealed that 60% of PPR-readers' SAT-English scores, and 70% of their SAT-Science scores were significantly lower than those of normal controls (both at p<.001). In SAT-Maths scores, however, none of the PPR-readers were significantly worse than the controls, indicating that cognitive processes involved in reading may be different from those involved in mathematical operations (a similar pattern of data can be seen in the case study

Wydell thus identified a subset of students aged 14-15 with phonological deficits even in a selective and competitive academic environment, where all students appeared to be performing well against the national average. Yet, these PPR-readers can still be considered

Wydell and Butterworth (1999) reported the case of an adolescent English-Japanese bilingual male, AS, whose reading and writing difficulties are confined to English only. Extensive investigations into his reading/writing difficulties in English revealed that he has typical phonological processing deficits (Wydell & Butterworth, 1999; Wydell & Kondo, 2003). *Figure 2* illustrates his performance in reading and phonological processing tests in English together with those of age-matched English and Japanese monolingual controls,

However his ability to read Japanese was equivalent and often better than that of his

Note that the Japanese writing system consists of two qualitatively different scripts: logographic, morphographic Kanji, derived from Chinese characters, and two forms of syllabic Kana, Hiragana and Katakana which are derived from Kanji characters (see Wydell, Patterson, & Humphreys, 1993 for more details). These three scripts are used to write different classes of words. Kanji characters are used for nouns and for the root morphemes

1 SATs - Standard Assessment Tests: national achievement tests given to all the children across the UK

2 This is because it has been reported that there are marked individual differences among children with developmental dyslexia both in terms of the extent of the severity and the nature of

Snowling 2000). The phonological deficits tend to interfere with the acquisition of appropriate grapheme-to-phoneme conversion skills. Moreover, adults with childhood diagnoses of dyslexia also revealed persistent phonological deficits (e.g., Bruck, 1992). For example, Felton, Naylor, and Wood (1990) found that adults with developmental dyslexia were impaired compared with normal controls using Rapid-Automatized-Naming (RAN), phonological awareness skills and non-word reading tests. Similarly, Paulesu, Frith, Snowling, Gallagher, Morton, Frackowiak and Frith (1996) found that even well-compensated dyslexic adults showed residual phonological deficits on phoneme deletions and Spoonerizing (exchange the initial phonemes of a pair of words, e.g., /car/ /park/ -> /par/ /cark/) tests.

#### **2. Dyslexia and poor phonological recoders**

More recently, Wydell in Shapiro, Hurry, Masterson, Wydell and Doctor (2009) tested 158 male and female students aged 14–15 in a state-funded selective and highly academic secondary school in the UK, and identified a subset students with phonological deficits.

The following five phonological tests (in written format) were administered to all the participating students: Rhyme-Judgements in words (e.g., YES to 'head–bed'), Rhyme-Judgement in nonwords (e.g., YES to 'kape-bap'), Homophone-Judgements in words (e.g., YES to 'their-there'), Homophone-Judgements in nonwords (e.g., YES to 'kane-kain'), Phonological-Lexical Decisions (e.g., YES to 'brane').

Wydell identified 16 students out of this cohort (*approximately just over 10%*), whose scores on any of these tests fell more than 1.5 standard deviations (SD) below the mean of the group, as *poor phonological recoder (PPR) readers* (i.e., those with phonological deficits).

Note: The figure was extracted from Shapiro, Hurry, Masterson, Wydell and Doctor (2009).

Fig. 1. Proportion correct for reading and phonological tasks of PPR-Readers compared with that of the controls.

Snowling 2000). The phonological deficits tend to interfere with the acquisition of appropriate grapheme-to-phoneme conversion skills. Moreover, adults with childhood diagnoses of dyslexia also revealed persistent phonological deficits (e.g., Bruck, 1992). For example, Felton, Naylor, and Wood (1990) found that adults with developmental dyslexia were impaired compared with normal controls using Rapid-Automatized-Naming (RAN), phonological awareness skills and non-word reading tests. Similarly, Paulesu, Frith, Snowling, Gallagher, Morton, Frackowiak and Frith (1996) found that even well-compensated dyslexic adults showed residual phonological deficits on phoneme deletions and Spoonerizing (exchange the initial phonemes of a pair of words, e.g., /car/ /park/ -> /par/ /cark/) tests.

More recently, Wydell in Shapiro, Hurry, Masterson, Wydell and Doctor (2009) tested 158 male and female students aged 14–15 in a state-funded selective and highly academic secondary school in the UK, and identified a subset students with phonological deficits.

The following five phonological tests (in written format) were administered to all the participating students: Rhyme-Judgements in words (e.g., YES to 'head–bed'), Rhyme-Judgement in nonwords (e.g., YES to 'kape-bap'), Homophone-Judgements in words (e.g., YES to 'their-there'), Homophone-Judgements in nonwords (e.g., YES to 'kane-kain'),

Wydell identified 16 students out of this cohort (*approximately just over 10%*), whose scores on any of these tests fell more than 1.5 standard deviations (SD) below the mean of the

group, as *poor phonological recoder (PPR) readers* (i.e., those with phonological deficits).

Note: The figure was extracted from Shapiro, Hurry, Masterson, Wydell and Doctor (2009).

that of the controls.

Fig. 1. Proportion correct for reading and phonological tasks of PPR-Readers compared with

**2. Dyslexia and poor phonological recoders** 

Phonological-Lexical Decisions (e.g., YES to 'brane').

Those PPR-readers and 16 randomly selected normal readers were further tested for their skills in Word Reading, Nonword Reading, Spoonerizing, Phoneme Deletions, and Nonword Repetition. As illustrated in *Figure 1*, the results revealed that PPR-readers were significantly worse than the controls on all the tests (p>.01 – p>.0001) except for Phoneme Deletions (p=.08) and Non-word repetition (p>1). Note that Gathercole and Baddeley's (1996) Non-word Repetition test is known to be one of the most effective diagnostic tools to identify developmental dyslexia in young children. Yet, this test did not show any difference between the PPR-readers and the normal controls. This might be because the test was developed primarily to assess young children's phonological skills, and that the test might not be sensitive enough for these adolescent individuals.

Furthermore, Wydell compared these PPR-readers' performance on SATs1 in English, Science and Mathematics individually, with that of the normal controls using z-scores2.

The results revealed that 60% of PPR-readers' SAT-English scores, and 70% of their SAT-Science scores were significantly lower than those of normal controls (both at p<.001). In SAT-Maths scores, however, none of the PPR-readers were significantly worse than the controls, indicating that cognitive processes involved in reading may be different from those involved in mathematical operations (a similar pattern of data can be seen in the case study reported by Wydell & Butterworth, 1999).

Wydell thus identified a subset of students aged 14-15 with phonological deficits even in a selective and competitive academic environment, where all students appeared to be performing well against the national average. Yet, these PPR-readers can still be considered as academic underachievers, as Hannell (2004) suggested.

#### **3. Dyslexia and the hypothesis of granularity and transparency**

Wydell and Butterworth (1999) reported the case of an adolescent English-Japanese bilingual male, AS, whose reading and writing difficulties are confined to English only. Extensive investigations into his reading/writing difficulties in English revealed that he has typical phonological processing deficits (Wydell & Butterworth, 1999; Wydell & Kondo, 2003). *Figure 2* illustrates his performance in reading and phonological processing tests in English together with those of age-matched English and Japanese monolingual controls, which clearly indicate his phonological processing deficits.

However his ability to read Japanese was equivalent and often better than that of his Japanese peers, as illustrated in *Table 1*.

Note that the Japanese writing system consists of two qualitatively different scripts: logographic, morphographic Kanji, derived from Chinese characters, and two forms of syllabic Kana, Hiragana and Katakana which are derived from Kanji characters (see Wydell, Patterson, & Humphreys, 1993 for more details). These three scripts are used to write different classes of words. Kanji characters are used for nouns and for the root morphemes

 1 SATs - Standard Assessment Tests: national achievement tests given to all the children across the UK at the end of Year-2 (aged seven), Year-6 (aged 11) and Year-9 (aged 14).

<sup>2</sup> This is because it has been reported that there are marked individual differences among children with developmental dyslexia both in terms of the extent of the severity and the nature of difficulties/impairments (e.g., Snowling & Griffiths, 2005).

Cross-Cultural/Linguistic Differences in the Prevalence

of Developmental Dyslexia and the Hypothesis of Granularity and Transparency 5

(pronunciations that were imported from spoken Chinese along with their corresponding characters) as well as a KUN-reading from the original Japanese spoken language. Some characters have no KUN-reading, but for those which have, the KUN-reading is almost always the correct reading when this character constitutes a word on its own (e.g., 花/hana/ in KUNreading, meaning 'flower' which represents a single-character word; 花束/hana-taba/ in

Note: Consistent = each character in a two-character Kanji word has one invariant ON (or occasionally KUN)-reading; Inc-ON (Inconsistent ON-reading) = each character takes ON-reading in a two-character word, but each character has a KUN-reading and/or another ON-reading; Inc-KUN (Inconsistent KUN) = each character takes KUN-reading in a two-character word, but each character has at least one ONreading; Jukujikun = truly exception words, neither character in a two-character Kanji word takes typical ON or KUN-reading, e.g., 雪崩/nadare/ meaning 'avalanche' however the first character means 'snow', and it is /yuki/ in KUN-reading, while it is /setsu/ in ON-reading; the second character means

Table 1 shows that his accuracy in reading two-character Kanji words is equivalent to Japanese undergraduate level except for low familiar Jukujikun (*z* = -3.63, *P* , 0.0009). Wydell and Butterworth stated that the latter may be due to the fact that he had not had enough exposure to low familiar Jukujikun. When AS was tested with these words, he was 16 years old, while the youngest participant who took part in the experiment of Wydell, Butterworth, Shibahara and Zorzi (1997) was 20 years old (mean age was 31 years old). Kanji learning is essentially a life-long continuous learning process. If he were continuously educated within the Japanese educational system, he would most probably be able to read these low familiar

In order to account for the dissociation between his ability to read in English and Japanese, Wydell and Butterworth (1999) put forward the Hypothesis of Granularity3 and

3 In their review paper, Ziegler and Goswami (2005) also pointed out the importance of 'granularity' in order to explain developmental dyslexia across different languages, and postulated the "Psycholinguistic grain size theory", which, however, "does not predict that orthographic consistency

'collapse', and it is /kuzu/ in KUN-reading, while it is /hou/ in ON-reading.

Table 1. AS's Performance for two-character Kanji word naming

Jukujikun by the time he graduated from a Japanese university.

The table was extracted from Wydell & Butterworth (1999).

KUN-reading, meaning 'bouquet' vs. 花瓶/ka-bin/ in ON-reading, meaning 'vase').

of inflected verbs, adjectives and adverbs. Hiragana characters are used mainly for function words and the inflections of verbs, adjectives and adverbs, and for some nouns with uncommon Kanji representations. Katakana characters are used for the large number of foreign loan words (e.g. テレビ/terebi/TV) in contemporary Japanese.

Both forms of Kana have an almost perfect one-to-one relationship between character and pronunciation. That is, one character always represents one particular syllable or mora (syllable like unit) of the Japanese language and its sound value does not change whether the character appears in the first position, the middle position or at the end of a multisyllable word. This is different from English, where orthographic units not only map onto sub-syllabic phonological units, but the mapping will also depend on context, i.e. the location within the word.

Note: These tests are in written format: Rhyme = Rhyme judgements; PLDT = Phonological lexical decision task (YES to psudohomophones, e.g., brane); PLDT = Orthographic lexical decision task (i.e., spell checking); Reading = reading aloud. \*\* = p<.01; \* = p<.05. The data were extracted from Wydell and Kondo (2003).

Fig. 2. A comparison of AS's performance with that of Japanese and English monolingual controls for reading and phonological tests

Words in Kanji have 1–5 characters with two being the modal number, and 2.4 the mean.

The relationship between character and pronunciation in Kanji is very opaque. This is because each Kanji character is a morphographic element that cannot phonetically be decomposed in the way that an alphabetic word can be. There are no separate components of a character that correspond to the individual phonemes (see Wydell, Patterson & Butterworth, 1995 for a further discussion). Also, most Kanji characters have one or more ON-readings,

of inflected verbs, adjectives and adverbs. Hiragana characters are used mainly for function words and the inflections of verbs, adjectives and adverbs, and for some nouns with uncommon Kanji representations. Katakana characters are used for the large number of

Both forms of Kana have an almost perfect one-to-one relationship between character and pronunciation. That is, one character always represents one particular syllable or mora (syllable like unit) of the Japanese language and its sound value does not change whether the character appears in the first position, the middle position or at the end of a multisyllable word. This is different from English, where orthographic units not only map onto sub-syllabic phonological units, but the mapping will also depend on context, i.e. the

95

57.8

66

92

40

55

English AS

Japanese

foreign loan words (e.g. テレビ/terebi/TV) in contemporary Japanese.

92

52

63

Rhyme PLDT OLDT Reading

Note: These tests are in written format: Rhyme = Rhyme judgements; PLDT = Phonological lexical decision task (YES to psudohomophones, e.g., brane); PLDT = Orthographic lexical decision task (i.e.,

Fig. 2. A comparison of AS's performance with that of Japanese and English monolingual

Words in Kanji have 1–5 characters with two being the modal number, and 2.4 the mean.

The relationship between character and pronunciation in Kanji is very opaque. This is because each Kanji character is a morphographic element that cannot phonetically be decomposed in the way that an alphabetic word can be. There are no separate components of a character that correspond to the individual phonemes (see Wydell, Patterson & Butterworth, 1995 for a further discussion). Also, most Kanji characters have one or more ON-readings,

\*\* \* \*\* \* \*\* \* \*\* \*

location within the word.

30

40

50

60

**Percentage** 

70

80

90

100

95

43

spell checking); Reading = reading aloud. \*\* = p<.01; \* = p<.05. The data were extracted from Wydell and Kondo (2003).

controls for reading and phonological tests

70

(pronunciations that were imported from spoken Chinese along with their corresponding characters) as well as a KUN-reading from the original Japanese spoken language. Some characters have no KUN-reading, but for those which have, the KUN-reading is almost always the correct reading when this character constitutes a word on its own (e.g., 花/hana/ in KUNreading, meaning 'flower' which represents a single-character word; 花束/hana-taba/ in KUN-reading, meaning 'bouquet' vs. 花瓶/ka-bin/ in ON-reading, meaning 'vase').


Note: Consistent = each character in a two-character Kanji word has one invariant ON (or occasionally KUN)-reading; Inc-ON (Inconsistent ON-reading) = each character takes ON-reading in a two-character word, but each character has a KUN-reading and/or another ON-reading; Inc-KUN (Inconsistent KUN) = each character takes KUN-reading in a two-character word, but each character has at least one ONreading; Jukujikun = truly exception words, neither character in a two-character Kanji word takes typical ON or KUN-reading, e.g., 雪崩/nadare/ meaning 'avalanche' however the first character means 'snow', and it is /yuki/ in KUN-reading, while it is /setsu/ in ON-reading; the second character means 'collapse', and it is /kuzu/ in KUN-reading, while it is /hou/ in ON-reading. The table was extracted from Wydell & Butterworth (1999).

Table 1. AS's Performance for two-character Kanji word naming

Table 1 shows that his accuracy in reading two-character Kanji words is equivalent to Japanese undergraduate level except for low familiar Jukujikun (*z* = -3.63, *P* , 0.0009). Wydell and Butterworth stated that the latter may be due to the fact that he had not had enough exposure to low familiar Jukujikun. When AS was tested with these words, he was 16 years old, while the youngest participant who took part in the experiment of Wydell, Butterworth, Shibahara and Zorzi (1997) was 20 years old (mean age was 31 years old). Kanji learning is essentially a life-long continuous learning process. If he were continuously educated within the Japanese educational system, he would most probably be able to read these low familiar Jukujikun by the time he graduated from a Japanese university.

In order to account for the dissociation between his ability to read in English and Japanese, Wydell and Butterworth (1999) put forward the Hypothesis of Granularity3 and

<sup>3</sup> In their review paper, Ziegler and Goswami (2005) also pointed out the importance of 'granularity' in order to explain developmental dyslexia across different languages, and postulated the "Psycholinguistic grain size theory", which, however, "does not predict that orthographic consistency

Cross-Cultural/Linguistic Differences in the Prevalence

be dyslexic in English but not in Japanese.

English, French and Italian speakers).

should *not lead to a high incidence of phonological dyslexia*.

of Developmental Dyslexia and the Hypothesis of Granularity and Transparency 7

and the orthography -to-phonology mapping is very opaque, hence Kanji can be placed in the shaded area. By this hypothesis, therefore, either of the two scripts used in Japanese

Now with this categorisation, English can be placed outside of the shaded area, since the granularity for English is small/finer, however, the orthography-to-phonology mapping is not always one-to-one and not transparent. By this hypothesis, English orthography *may lead to a high incidence of phonological dyslexia*. Given the differences between the two orthographies used in Japanese and English, therefore, the hypothesis of granularity and transparency argues that it might be possible for an English-Japanese bilingual individual to

**4. Prevalence of dyslexia and the hypothesis of granularity and transparency**  Indeed, researchers have argued that the difference in the prevalence of developmental dyslexia in the different languages might be primarily due to the differences inherent in the characteristics of each orthography, in particular, the way in which phonology is computed from orthography (e.g., de Luca, Burani, Paizi, Spinelli, Zoccolotti, 2010; Landerl, Wimmer, Frith, 1997; Wydell & Butterworth, 1999; Zoccolotti, de Luca, de Pace, Gasperini, Judica, Spinelli, 2005). Earlier it was mentioned that in English up to 10 – 12% of children are reported to suffer from developmental dyslexia (e.g., Shaywitz, et al., 1990; Snowling, 2000). In Danish, as many as 12% of adults in Denmark have difficulties in reading, which was revealed in the study conducted by Elbro, Moller, and Nielsen (1995). In these languages, orthography-to-phonology correspondence (which means grapheme-to-phoneme correspondence in alphabetic languages) is not consistent, i.e., not always one-to-one or transparent (e.g., hint, lint, tint vs. pint; bread, head vs. bead, mead; colonel; yacht; bough vs. dough vs. through vs. thorough). However, in alphabetical languages whereby the grapheme-to-phoneme correspondence is consistent or transparent, such as for example, Dutch, German, or Italian, the prevalence of developmental dyslexia is much lower (e.g., de Luca, et al., 2010; Zoccolotti et al., 2005 for Italian; Landerl, et al., 1997 for the comparison between German and English speakers; Paulesu, De´monet, Fazio, McCrory, Chanoine, Brunswick, Cappa, Cossu, Habib, Frith, C.D., & Frith U., 2001 for the comparison between

For example, Landerl et al. (1997) examined the reading and phonological processing skills of English and German dyslexic children against their normal chronological and reading age-matched controls, and found that although the same underlying phonological processing deficit might exist in both German and English dyslexic children, there were differences in the severity of the reading impairment. English dyslexic children showed a marked adverse effect in the acquisition of reading skills compared to German dyslexic children. These differences were also seen between the normal German and English control children in their reading performance. Landerl et al. suggested that these differences were due to differences in orthographic 'consistency'. That is, different orthographies have different mapping rules, and there is a wide range in the degree of consistency with which alphabets represent phonemes by graphemes. 'Consistency' here is interchangeable with 'transparency'. For orthographies such as German, Italian or Spanish, the grapheme-tophoneme mapping is, in general, one-to-one, and consistent/transparent. For other orthographies such as English or Danish, the grapheme-to-phoneme mapping is often one-

Transparency as illustrated in *Figure 3*. The hypothesis maintains that orthographies can be described in these two dimensions - (1) any orthography, where the print-to-sound translation is one-to-one or transparent *would not produce a high incidence of phonological dyslexia* (i.e., dyslexia due to phonological deficits) regardless of the level of translation, i.e. phoneme, syllable, character, etc. This is the 'transparency' dimension, and (2) even when this relationship is opaque and not one-to-one, any orthography whose smallest orthographic unit representing sound is coarse, i.e. a whole character or whole word, *would not produce a high incidence of phonological dyslexia*. This is the 'granularity' dimension. Any orthography used in any language can be placed in the transparency-granularity orthogonal dimension described by this hypothesis.

#### **Granular Size**

Fig. 3. Hypothesis of Granularity and Transparency and orthography-to-phonology correspondence.

For example, the granularity of the smallest orthographic unit representing phonology for *Japanese Kana* is finer than the whole word, but coarser than the grapheme, and its orthography-to-phonology mapping is at the level of syllables and one-to-one. In contrast, for *Japanese Kanji*, the unit of granularity is much coarser, i.e. a character or a whole word,

<sup>(</sup>i.e., transparency) reduced developmental dyslexia" (p.20). They further argued that had Wydell and Butterworth included nonword reading tasks in terms of "timed performance", he (AS) would have "displayed clear deficits in reading" in both languages (p.20). However, Zigler and Goswami did not include Wydell and Kondo (2003)'s follow-up study in their review paper. Wydell and Kondo stated that "AS's reading was never laborious and slow" (p.40). Although they did not measure RT for each stimulus word or nonword in milliseconds, they measured AS's reading latencies for stimulus lists (in minutes/seconds), which included nonwords in English and Japanese Kana. AS's reading latencies were comparable to those of the English controls, and were shorter than those of the Japanese controls.

Transparency as illustrated in *Figure 3*. The hypothesis maintains that orthographies can be described in these two dimensions - (1) any orthography, where the print-to-sound translation is one-to-one or transparent *would not produce a high incidence of phonological dyslexia* (i.e., dyslexia due to phonological deficits) regardless of the level of translation, i.e. phoneme, syllable, character, etc. This is the 'transparency' dimension, and (2) even when this relationship is opaque and not one-to-one, any orthography whose smallest orthographic unit representing sound is coarse, i.e. a whole character or whole word, *would not produce a high incidence of phonological dyslexia*. This is the 'granularity' dimension. Any orthography used in any language can be placed in the transparency-granularity orthogonal

dimension described by this hypothesis.

 **Degree of Transparency** 

Fig. 3. Hypothesis of Granularity and Transparency and orthography-to-phonology

For example, the granularity of the smallest orthographic unit representing phonology for *Japanese Kana* is finer than the whole word, but coarser than the grapheme, and its orthography-to-phonology mapping is at the level of syllables and one-to-one. In contrast, for *Japanese Kanji*, the unit of granularity is much coarser, i.e. a character or a whole word,

(i.e., transparency) reduced developmental dyslexia" (p.20). They further argued that had Wydell and Butterworth included nonword reading tasks in terms of "timed performance", he (AS) would have "displayed clear deficits in reading" in both languages (p.20). However, Zigler and Goswami did not include Wydell and Kondo (2003)'s follow-up study in their review paper. Wydell and Kondo stated that "AS's reading was never laborious and slow" (p.40). Although they did not measure RT for each stimulus word or nonword in milliseconds, they measured AS's reading latencies for stimulus lists (in minutes/seconds), which included nonwords in English and Japanese Kana. AS's reading latencies were comparable to those of the English controls, and were shorter than those of the Japanese controls.

 **Granular Size** 

correspondence.

and the orthography -to-phonology mapping is very opaque, hence Kanji can be placed in the shaded area. By this hypothesis, therefore, either of the two scripts used in Japanese should *not lead to a high incidence of phonological dyslexia*.

Now with this categorisation, English can be placed outside of the shaded area, since the granularity for English is small/finer, however, the orthography-to-phonology mapping is not always one-to-one and not transparent. By this hypothesis, English orthography *may lead to a high incidence of phonological dyslexia*. Given the differences between the two orthographies used in Japanese and English, therefore, the hypothesis of granularity and transparency argues that it might be possible for an English-Japanese bilingual individual to be dyslexic in English but not in Japanese.

### **4. Prevalence of dyslexia and the hypothesis of granularity and transparency**

Indeed, researchers have argued that the difference in the prevalence of developmental dyslexia in the different languages might be primarily due to the differences inherent in the characteristics of each orthography, in particular, the way in which phonology is computed from orthography (e.g., de Luca, Burani, Paizi, Spinelli, Zoccolotti, 2010; Landerl, Wimmer, Frith, 1997; Wydell & Butterworth, 1999; Zoccolotti, de Luca, de Pace, Gasperini, Judica, Spinelli, 2005). Earlier it was mentioned that in English up to 10 – 12% of children are reported to suffer from developmental dyslexia (e.g., Shaywitz, et al., 1990; Snowling, 2000). In Danish, as many as 12% of adults in Denmark have difficulties in reading, which was revealed in the study conducted by Elbro, Moller, and Nielsen (1995). In these languages, orthography-to-phonology correspondence (which means grapheme-to-phoneme correspondence in alphabetic languages) is not consistent, i.e., not always one-to-one or transparent (e.g., hint, lint, tint vs. pint; bread, head vs. bead, mead; colonel; yacht; bough vs. dough vs. through vs. thorough). However, in alphabetical languages whereby the grapheme-to-phoneme correspondence is consistent or transparent, such as for example, Dutch, German, or Italian, the prevalence of developmental dyslexia is much lower (e.g., de Luca, et al., 2010; Zoccolotti et al., 2005 for Italian; Landerl, et al., 1997 for the comparison between German and English speakers; Paulesu, De´monet, Fazio, McCrory, Chanoine, Brunswick, Cappa, Cossu, Habib, Frith, C.D., & Frith U., 2001 for the comparison between English, French and Italian speakers).

For example, Landerl et al. (1997) examined the reading and phonological processing skills of English and German dyslexic children against their normal chronological and reading age-matched controls, and found that although the same underlying phonological processing deficit might exist in both German and English dyslexic children, there were differences in the severity of the reading impairment. English dyslexic children showed a marked adverse effect in the acquisition of reading skills compared to German dyslexic children. These differences were also seen between the normal German and English control children in their reading performance. Landerl et al. suggested that these differences were due to differences in orthographic 'consistency'. That is, different orthographies have different mapping rules, and there is a wide range in the degree of consistency with which alphabets represent phonemes by graphemes. 'Consistency' here is interchangeable with 'transparency'. For orthographies such as German, Italian or Spanish, the grapheme-tophoneme mapping is, in general, one-to-one, and consistent/transparent. For other orthographies such as English or Danish, the grapheme-to-phoneme mapping is often one-

Cross-Cultural/Linguistic Differences in the Prevalence

phonological processing problems.

of Developmental Dyslexia and the Hypothesis of Granularity and Transparency 9

Thus the results of Uno et al.'s (2009) study further lend support to the Hypothesis of Granularity and Transparency. Wydell and Butterworth (1999) argued that English orthography would require a fine tuning of the orthography-to-phonology mapping, because English orthography is not completely transparent at the subsyllabic level (i.e. smaller grain-unit than syllables). In contrast, the grain size for Kana is at the whole character level (i.e., greater grain-unit than graphemes), and its orthography-to-phonology mapping is transparent (one-to-one). Hence Japanese children in general find it easier to master reading in Kana. This is because, as Landerl et al. (1997) argued for German, the phonological recoding of Kana is not a demanding task. Moreover, although the grain size for Kanji is either at whole character or whole word level, its orthography-to-phonology mapping is opaque (one-to-many). Consequently learning to read in Kanji for Japanese children is harder than that in Kana. The results thus indicate that reading Kanji may require different reading strategies or different cognitive skills to those required for reading Kana. If so, reading English may yet require different reading strategies to those required for Kanji or Kana.

Wydell and Butterworth (1999) thus speculated that it is therefore possible to be a Danish or

Interestingly, in Japan rather than group studies, single case studies of children with reading disorders have started to emerge (e.g., Kaneko, Uno, Kaga, Matsuda, Inagaki, & Haruhara, 1997; 1998; Uno, Kaneko, Haruhara, Matsuda, Kato, & Kasahara, 2002). The majority of these children in Japan tend to have both reading and writing difficulties, and often the writing impairment is more severe than the reading impairment4. Significantly, in Japan there are very few reported cases of children with reading impairments only. The Japanese researchers usually attribute these reading and writing impairments among children to 'visual' or 'visuospatial' processing problems (e.g., Kaneko et al., 1998) rather than

Unlike alphabetic orthographies but similar to Japanese KANJI, the Chinese language uses a logographic writing system whereby the basic orthographic units, the Chinese characters, correspond directly to morphemic meanings and to syllables in the spoken language. The pronunciations of Chinese characters are represented at the monosyllabic level, and no phonemes are represented in a character. That is, reading a Chinese character does not allow the segmental analysis (i.e., grapheme-to-phoneme conversion), which is fundamental in alphabetic orthographies (Wanga, Bi, Gao, &Wydell, 2010). Therefore Chinese is often referred as a morphosyllabic writing system (Shu & Anderson, 1997). Further, Meng, Sai, Wang X., Wang, J., Sha, and Zhou (2005) pointed out that there is only limited systematic correspondence between orthography and phonology. Moreover, Mandarin Chinese has a large number of homophonic morphemes and homophonic characters. Therefore it is often stated that the use of phonological information may not be as critical in reading Chinese as it is in reading alphabetic languages (Ho, Chan, Lee, Tsang, & Luan, 2004; Ho, Chan, Tsang, & Lee, 2002; Shu, McBride-Chang,Wu, & Liu, 2006). If this were the case, then a high incidence

4 In English, it is often the case that when reading is impaired, writing is also impaired, and therefore

dyslexia is assumed to mean both reading and writing impairments.

English-Japanese bilingual with monolingual dyslexia in Danish or English.

**5. Dyslexia and cross-cultural and cross-linguistic differences** 

to-many (e.g., food vs. hood vs. flood or blood), and less consistent/transparent (e.g. Seidenberg, Waters, Barnes, & Tanenhaus, 1984). Thus it was assumed that orthographic consistency/transparency affects both the nature and degree of reading difficulties (de Luca, et al., 2010; Zoccolotti et al., 2005).

Landerl et al. further argued that phonological recoding itself may not necessarily be a demanding task. When grapheme-to-phoneme mapping is consistent/transparent, children can easily acquire the grapheme-phoneme correspondence rules, and use these to assemble pronunciations for novel letter strings (as seen with Italian or Spanish children for example). Therefore, the phonological recoding may become a demanding task, only when the grapheme-phoneme correspondence in an orthography is not consistent/transparent, such as for example, English (Snowling, 2000) or Danish (Elbo et al., 1995). Therefore, if the grapheme-phoneme correspondence is consistent, even children with phonological deficits may be able to learn to map print onto sound thus without showing a delay in reading acquisition. Similarly, the 'hypothesis of granularity and transparency' in particular, the transparency dimension predicts that *developmental phonological dyslexia* should not manifest itself in a writing system where the print-to-sound correspondence is transparent regardless of the size unit of granularity.

Moreover, the granularity dimension of the hypothesis predicts that developmental phonological dyslexia should not manifest itself in a writing system where the unit of granularity is coarse at a whole character or whole word level. It should therefore be possible to find a bilingual individual with monolingual dyslexia, especially between two orthographies such as English and Japanese.

Further evidence which lends support to the Hypothesis can be seen in a recent cross sectional study conducted in Japanese by Uno, Wydell, Haruhara, Kaneko and Shinya (2009). In their study, 495 Japanese primary school children (from 2nd Grade aged eight to 6th Grade aged 12) in Japan were tested for their reading, writing and other cognitive skills including phonological awareness (STRAW, 2006). The results showed that percentages of children who had reading difficulties (defined as those whose reading/writing/phonological tests' scores fell below -1.5SD) in syllabic Hiragana, syllabic Katakana, and logographic Kanji were 0.2%, 1.4%, and 6.9% respectively – these figures were significantly lower than those reported in the studies in English (Shaywitz et al., 1997; Snowling, 2000) or Danish (Elbo et al., 1995). Yet there was no significant difference in the IQ scores between the normal group and reading/writing disabled (RWD) group (measured by Ravens Coloured Progressive Matrices, 1976).

The study also suggested that different reading strategies might be adopted when reading in Kana and Kanji. For Kana, where the character-to-sound-mapping is transparent, a simple on-line phonological processing (i.e., sublexical analytical reading) strategy might be used (Wydell & Butterworth, 1999; Rastle, Havelka, Wydell, Coltheart, Besner 2009), just like other consistent orthographies such as Italian (de Luca, et al., 2010; Zoccolotti et al., 2005) or German (Landerl et al., 1997). In contrast, for Kanji, because the character-to-soundrelationship is opaque, and the correct pronunciation is determined at the whole-word level, a lexical whole-word reading strategy might be used (e.g., Morton, Sasanuma, Patterson & Sakuma, 1992; Wydell, 1998; Wydell & Butterworth, 1999; Wydell, et al., 1993; Wydell, Butterworth & Patterson, 1995; however also see Fushimi, Ijuin, Patterson & Tatsumi, 1999 for counter argument).

to-many (e.g., food vs. hood vs. flood or blood), and less consistent/transparent (e.g. Seidenberg, Waters, Barnes, & Tanenhaus, 1984). Thus it was assumed that orthographic consistency/transparency affects both the nature and degree of reading difficulties (de Luca,

Landerl et al. further argued that phonological recoding itself may not necessarily be a demanding task. When grapheme-to-phoneme mapping is consistent/transparent, children can easily acquire the grapheme-phoneme correspondence rules, and use these to assemble pronunciations for novel letter strings (as seen with Italian or Spanish children for example). Therefore, the phonological recoding may become a demanding task, only when the grapheme-phoneme correspondence in an orthography is not consistent/transparent, such as for example, English (Snowling, 2000) or Danish (Elbo et al., 1995). Therefore, if the grapheme-phoneme correspondence is consistent, even children with phonological deficits may be able to learn to map print onto sound thus without showing a delay in reading acquisition. Similarly, the 'hypothesis of granularity and transparency' in particular, the transparency dimension predicts that *developmental phonological dyslexia* should not manifest itself in a writing system where the print-to-sound correspondence is transparent regardless

Moreover, the granularity dimension of the hypothesis predicts that developmental phonological dyslexia should not manifest itself in a writing system where the unit of granularity is coarse at a whole character or whole word level. It should therefore be possible to find a bilingual individual with monolingual dyslexia, especially between two

Further evidence which lends support to the Hypothesis can be seen in a recent cross sectional study conducted in Japanese by Uno, Wydell, Haruhara, Kaneko and Shinya (2009). In their study, 495 Japanese primary school children (from 2nd Grade aged eight to 6th Grade aged 12) in Japan were tested for their reading, writing and other cognitive skills including phonological awareness (STRAW, 2006). The results showed that percentages of children who had reading difficulties (defined as those whose reading/writing/phonological tests' scores fell below -1.5SD) in syllabic Hiragana, syllabic Katakana, and logographic Kanji were 0.2%, 1.4%, and 6.9% respectively – these figures were significantly lower than those reported in the studies in English (Shaywitz et al., 1997; Snowling, 2000) or Danish (Elbo et al., 1995). Yet there was no significant difference in the IQ scores between the normal group and reading/writing disabled (RWD) group (measured

The study also suggested that different reading strategies might be adopted when reading in Kana and Kanji. For Kana, where the character-to-sound-mapping is transparent, a simple on-line phonological processing (i.e., sublexical analytical reading) strategy might be used (Wydell & Butterworth, 1999; Rastle, Havelka, Wydell, Coltheart, Besner 2009), just like other consistent orthographies such as Italian (de Luca, et al., 2010; Zoccolotti et al., 2005) or German (Landerl et al., 1997). In contrast, for Kanji, because the character-to-soundrelationship is opaque, and the correct pronunciation is determined at the whole-word level, a lexical whole-word reading strategy might be used (e.g., Morton, Sasanuma, Patterson & Sakuma, 1992; Wydell, 1998; Wydell & Butterworth, 1999; Wydell, et al., 1993; Wydell, Butterworth & Patterson, 1995; however also see Fushimi, Ijuin, Patterson & Tatsumi, 1999

et al., 2010; Zoccolotti et al., 2005).

of the size unit of granularity.

orthographies such as English and Japanese.

by Ravens Coloured Progressive Matrices, 1976).

for counter argument).

Thus the results of Uno et al.'s (2009) study further lend support to the Hypothesis of Granularity and Transparency. Wydell and Butterworth (1999) argued that English orthography would require a fine tuning of the orthography-to-phonology mapping, because English orthography is not completely transparent at the subsyllabic level (i.e. smaller grain-unit than syllables). In contrast, the grain size for Kana is at the whole character level (i.e., greater grain-unit than graphemes), and its orthography-to-phonology mapping is transparent (one-to-one). Hence Japanese children in general find it easier to master reading in Kana. This is because, as Landerl et al. (1997) argued for German, the phonological recoding of Kana is not a demanding task. Moreover, although the grain size for Kanji is either at whole character or whole word level, its orthography-to-phonology mapping is opaque (one-to-many). Consequently learning to read in Kanji for Japanese children is harder than that in Kana. The results thus indicate that reading Kanji may require different reading strategies or different cognitive skills to those required for reading Kana. If so, reading English may yet require different reading strategies to those required for Kanji or Kana.

Wydell and Butterworth (1999) thus speculated that it is therefore possible to be a Danish or English-Japanese bilingual with monolingual dyslexia in Danish or English.

#### **5. Dyslexia and cross-cultural and cross-linguistic differences**

Interestingly, in Japan rather than group studies, single case studies of children with reading disorders have started to emerge (e.g., Kaneko, Uno, Kaga, Matsuda, Inagaki, & Haruhara, 1997; 1998; Uno, Kaneko, Haruhara, Matsuda, Kato, & Kasahara, 2002). The majority of these children in Japan tend to have both reading and writing difficulties, and often the writing impairment is more severe than the reading impairment4. Significantly, in Japan there are very few reported cases of children with reading impairments only. The Japanese researchers usually attribute these reading and writing impairments among children to 'visual' or 'visuospatial' processing problems (e.g., Kaneko et al., 1998) rather than phonological processing problems.

Unlike alphabetic orthographies but similar to Japanese KANJI, the Chinese language uses a logographic writing system whereby the basic orthographic units, the Chinese characters, correspond directly to morphemic meanings and to syllables in the spoken language. The pronunciations of Chinese characters are represented at the monosyllabic level, and no phonemes are represented in a character. That is, reading a Chinese character does not allow the segmental analysis (i.e., grapheme-to-phoneme conversion), which is fundamental in alphabetic orthographies (Wanga, Bi, Gao, &Wydell, 2010). Therefore Chinese is often referred as a morphosyllabic writing system (Shu & Anderson, 1997). Further, Meng, Sai, Wang X., Wang, J., Sha, and Zhou (2005) pointed out that there is only limited systematic correspondence between orthography and phonology. Moreover, Mandarin Chinese has a large number of homophonic morphemes and homophonic characters. Therefore it is often stated that the use of phonological information may not be as critical in reading Chinese as it is in reading alphabetic languages (Ho, Chan, Lee, Tsang, & Luan, 2004; Ho, Chan, Tsang, & Lee, 2002; Shu, McBride-Chang,Wu, & Liu, 2006). If this were the case, then a high incidence

 4 In English, it is often the case that when reading is impaired, writing is also impaired, and therefore dyslexia is assumed to mean both reading and writing impairments.

Cross-Cultural/Linguistic Differences in the Prevalence

languages.

**6. References** 

*Psychology, 28*, 874–886.

*Reading and Writing, 19*(6), 543–561.

of Developmental Dyslexia and the Hypothesis of Granularity and Transparency 11

Other brain imaging studies using fMRI (functional Magnetic Resonance Imaging) in Chinese such as Siok, Niu, Jin, Perfetti, and Tan (2008) or Siok, Perfetti, Jin, & Tan (2004) revealed functional and structural abnormalities in the left middle frontal gyrus of Chinese dyslexic children, but not in the left temporoparietal and occipitotemporal regions that are important for reading in alphabetic languages (e.g., Paulesu, McCrory, et al., 2000; Wydell, Vuorinen, Helenius & Salmelin, 2003), and are typically compromised in dyslexic children in alphabetic languages (e.g., Horwitz, Rumsey, & Donohue, 1998; Temple, Poldrack, Salidis, Deutsch, Tallall, Merzenich, & Gabriel, 2001). These researchers therefore argued that reading Chinese characters might require firstly greater cognitive demand for visual processing than reading in alphabetic languages such as English, and secondly a greater inter-activity between orthography and phonology. This is because, like Japanese Kanji, reading Chinese characters requires retrieving phonology as a whole rather than addressing phonology in piece-meal fashion (see Wang et al., 2010 for more details). Therefore Siok and his colleagues also suggested that the neural abnormality found in impaired readers is

dependent on culture (see also Paulesu, Frith, et al., 2001 for a similar argument).

Thus in this Chapter, having reviewed recent empirical studies in alphabetical as well as non-alphabetic languages such as Chinese and Japanese, the chapter has shown significant cross-cultural/linguistic differences in the prevalence of developmental dyslexia in different

Bruck, M. (1992). Persistence of dyslexics' phonological awareness deficits. *Developmental* 

Chan, D.W., Ho, C.S.H., Tsang, S.M., Lee, S.H., & Chung, K.K.H. (2006). Exploring the

Chrichey, M. (1975). Specific developmental dyslexia. In: Lenneberg, E.H., Lenneberg, E. (Eds.), *Foundations of Language Development*, Vol. 2. Academic Press, New York. Davis, C.J., Gayan, J., Knopik, V.S., Smith, S.D., Cardon, L.R., Pennington, B.F., Olson, R.K.,

Coloradotwin study of reading disability. *Behavioral Genetics, 31*:625-635. de Luca M, Burani C, Paizi D, Spinelli D, Zoccolotti P. (2010). Letter and letter-string

Eden, G., & Moats, L. (2002). The role of neuroscience in the remediation of students with

Elbo, C., Moller, S., & Nielsen, E.M., (1995). Functional reading difficulties in Denmark: a study of adult reading of common text. *Reading and Writing 7,* 257–276. Felton, R. H., Naylor, C. E., & Wood, F. B. (1990). Neuropsychological profile of adult

Fisher, S. E., & DeFries, J. (2002). Developmental dyslexia: genetic dissection of a complex

Fushimi, T., Ijuin, M., Patterson, K., & Tatsumi, I. (1999). Consistency, frequency, and

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of phonological dyslexia in Chinese should not be seen (*cf* the Hypothesis of Granularity and Transparency (Wydell & Butterworth, 1999)).

Similar to Uno et al.'s (2009) study in Japanese, Li, Shu, McBride-Chang, Liu and Peng (in press) investigated the acquisition of reading in Chinese, and tested 184 kindergarten children and 273 primary school children from Beijing, Mainland China for their skills in (a) Chinese character recognition, (b) visual-spatial relationships and visual memory, (c) orthographic judgement, (d) phonological awareness including (d1) Rime deletion, (d2) Syllable deletion, (d3) Phoneme deletion and (d4) Rapid number naming, (e) Morphological awareness including (e1) Homophone judgements, (e2) Morphological construction, and (e3) Morpheme production.

The results showed that especially for the primary school children, a unique and relatively strong relationship between (c) orthographic knowledge (and not (b) visual skills) and reading was found. In addition, (d) phonological and (e) morphological awareness "appear to be somewhat important for reading throughout the very beginning and intermediate periods of character acquisition" (p.15). However, (d3) phoneme deletion was not uniquely associated with reading particularly for the primary school children. Li et al. thus argued that "phoneme awareness by itself is relatively unimportant for reading Chinese because the phoneme is not explicitly represented in the Chinese orthography" (p.16). Li et al. further argued that unlike most alphabetic writing systems where there is a strong relationship between phoneme awareness and reading skills, in Chinese larger unit size such as syllable or rime may be a better predictor variable for reading Chinese characters.

Indeed, recent research has revealed that the major cause of developmental dyslexia in Chinese is a deficit in orthographic processing skills, rather than in phonological processing skills (e.g., Chan, Ho, Tsang, Lee, & Chung, 2006; Ho et al., 2004; Shu et al., 2006), though some studies did show that Chinese dyslexic children had phonological deficits (e.g., deficits in rapid naming (e.g., Ho, Law, & Ng, 2000) and auditory processing (e.g., Meng et al., 2005).

In order to ascertain neurophysiologically a cause of developmental dyslexia in Chinese, Wang, Bi, Gao, and Wydell (2010) conducted an ERP (Event Related Potential) study with Chinese dyslexic and chronological-age-matched, and reading-level-matched non-dyslexic children from Beijing, Mainland China, employing a psychophysical experiment, i.e., the motion-onset paradigm. A similar psychophysical paradigm was first employed by Rogers-Ramachandran and Ramachandran (1998) with English-speakers as their participants, whereby two distinct visual systems/pathways in human vision were identified, namely, "a fast, sign-invariant system concerned with extracting controls" (p.71) which is the magnocellular visual system, and "a shallower, sign-sensitive system concerned with assigning surface colour" (p.71), which is the parvocellular visual system. Subsequent similar psychophysics studies with English-speaking children as participants showed that the performance of the participating children significantly correlated with the measures of orthographic skills in the Magnocellular Condition (e.g., Sperling, Lu, Manis, and Seidenberg, 2003; Talcott, Witton, McLean, Hansen, Rees, & Green, 2000).

Wang et al.'s ERP study revealed that the Chinese dyslexic children's orthographic processing skills were significantly compromised, when compared to their Chinese chronological and reading age-matched control children, which in turn, Wang et al. argued, is linked to a deficit in the visual magnocelluar system.

Other brain imaging studies using fMRI (functional Magnetic Resonance Imaging) in Chinese such as Siok, Niu, Jin, Perfetti, and Tan (2008) or Siok, Perfetti, Jin, & Tan (2004) revealed functional and structural abnormalities in the left middle frontal gyrus of Chinese dyslexic children, but not in the left temporoparietal and occipitotemporal regions that are important for reading in alphabetic languages (e.g., Paulesu, McCrory, et al., 2000; Wydell, Vuorinen, Helenius & Salmelin, 2003), and are typically compromised in dyslexic children in alphabetic languages (e.g., Horwitz, Rumsey, & Donohue, 1998; Temple, Poldrack, Salidis, Deutsch, Tallall, Merzenich, & Gabriel, 2001). These researchers therefore argued that reading Chinese characters might require firstly greater cognitive demand for visual processing than reading in alphabetic languages such as English, and secondly a greater inter-activity between orthography and phonology. This is because, like Japanese Kanji, reading Chinese characters requires retrieving phonology as a whole rather than addressing phonology in piece-meal fashion (see Wang et al., 2010 for more details). Therefore Siok and his colleagues also suggested that the neural abnormality found in impaired readers is dependent on culture (see also Paulesu, Frith, et al., 2001 for a similar argument).

Thus in this Chapter, having reviewed recent empirical studies in alphabetical as well as non-alphabetic languages such as Chinese and Japanese, the chapter has shown significant cross-cultural/linguistic differences in the prevalence of developmental dyslexia in different languages.

#### **6. References**

10 Dyslexia – A Comprehensive and International Approach

of phonological dyslexia in Chinese should not be seen (*cf* the Hypothesis of Granularity

Similar to Uno et al.'s (2009) study in Japanese, Li, Shu, McBride-Chang, Liu and Peng (in press) investigated the acquisition of reading in Chinese, and tested 184 kindergarten children and 273 primary school children from Beijing, Mainland China for their skills in (a) Chinese character recognition, (b) visual-spatial relationships and visual memory, (c) orthographic judgement, (d) phonological awareness including (d1) Rime deletion, (d2) Syllable deletion, (d3) Phoneme deletion and (d4) Rapid number naming, (e) Morphological awareness including (e1) Homophone judgements, (e2) Morphological construction, and

The results showed that especially for the primary school children, a unique and relatively strong relationship between (c) orthographic knowledge (and not (b) visual skills) and reading was found. In addition, (d) phonological and (e) morphological awareness "appear to be somewhat important for reading throughout the very beginning and intermediate periods of character acquisition" (p.15). However, (d3) phoneme deletion was not uniquely associated with reading particularly for the primary school children. Li et al. thus argued that "phoneme awareness by itself is relatively unimportant for reading Chinese because the phoneme is not explicitly represented in the Chinese orthography" (p.16). Li et al. further argued that unlike most alphabetic writing systems where there is a strong relationship between phoneme awareness and reading skills, in Chinese larger unit size such as syllable

Indeed, recent research has revealed that the major cause of developmental dyslexia in Chinese is a deficit in orthographic processing skills, rather than in phonological processing skills (e.g., Chan, Ho, Tsang, Lee, & Chung, 2006; Ho et al., 2004; Shu et al., 2006), though some studies did show that Chinese dyslexic children had phonological deficits (e.g., deficits in rapid naming (e.g., Ho, Law, & Ng, 2000) and auditory processing (e.g., Meng et al., 2005).

In order to ascertain neurophysiologically a cause of developmental dyslexia in Chinese, Wang, Bi, Gao, and Wydell (2010) conducted an ERP (Event Related Potential) study with Chinese dyslexic and chronological-age-matched, and reading-level-matched non-dyslexic children from Beijing, Mainland China, employing a psychophysical experiment, i.e., the motion-onset paradigm. A similar psychophysical paradigm was first employed by Rogers-Ramachandran and Ramachandran (1998) with English-speakers as their participants, whereby two distinct visual systems/pathways in human vision were identified, namely, "a fast, sign-invariant system concerned with extracting controls" (p.71) which is the magnocellular visual system, and "a shallower, sign-sensitive system concerned with assigning surface colour" (p.71), which is the parvocellular visual system. Subsequent similar psychophysics studies with English-speaking children as participants showed that the performance of the participating children significantly correlated with the measures of orthographic skills in the Magnocellular Condition (e.g., Sperling, Lu, Manis, and

Wang et al.'s ERP study revealed that the Chinese dyslexic children's orthographic processing skills were significantly compromised, when compared to their Chinese chronological and reading age-matched control children, which in turn, Wang et al. argued,

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Compared with research on alphabetic languages, research on reading acquisition and impairment in Chinese has a relatively short history. However, this field has attracted more and more attention, and increasing number of findings have been reported in recent years. In the present chapter, we will firstly describe some important features of the Chinese language, and how these features influence reading acquisition of normal Chinese children. Then, we will summarize a series of studies of dyslexic development in learning to read Chinese, in which the critical deficits for Chinese dyslexic children were identified. Finally, several longitudinal studies will be reviewed, in which the early predictors and developmental trajectories of reading acquisition and impairment in Chinese children were

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It has long been recognized that phonological skills are highly correlated with reading ability in alphabetic languages (Bradley & Bryant, 1983; Wagner & Torgesen, 1987; Ziegler & Goswami, 2005). In recent years, increasing research evidence has been reported that the contribution of the cognitive skills on reading acquisition is also related to the nature of the orthographies. For example, naming speed (Wimmer et al., 2000) and letter knowledge (Gallagher, Frith, & Snowling, 2000) have been identified to be also the important cognitive

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**1. Introduction** 

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Hua Shu and Hong Li *Beijing Normal University,* 


## **Typical and Dyslexic Development in Learning to Read Chinese**

Hua Shu and Hong Li *Beijing Normal University, China* 

#### **1. Introduction**

14 Dyslexia – A Comprehensive and International Approach

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Compared with research on alphabetic languages, research on reading acquisition and impairment in Chinese has a relatively short history. However, this field has attracted more and more attention, and increasing number of findings have been reported in recent years. In the present chapter, we will firstly describe some important features of the Chinese language, and how these features influence reading acquisition of normal Chinese children. Then, we will summarize a series of studies of dyslexic development in learning to read Chinese, in which the critical deficits for Chinese dyslexic children were identified. Finally, several longitudinal studies will be reviewed, in which the early predictors and developmental trajectories of reading acquisition and impairment in Chinese children were explored.

#### **2. Properties of the Chinese language and the cognitive correlates in reading acquisition of Chinese children**

It has long been recognized that phonological skills are highly correlated with reading ability in alphabetic languages (Bradley & Bryant, 1983; Wagner & Torgesen, 1987; Ziegler & Goswami, 2005). In recent years, increasing research evidence has been reported that the contribution of the cognitive skills on reading acquisition is also related to the nature of the orthographies. For example, naming speed (Wimmer et al., 2000) and letter knowledge (Gallagher, Frith, & Snowling, 2000) have been identified to be also the important cognitive correlates of reading acquisition in transparent orthographies.

Chinese is a logographic writing system. The basic units of written Chinese are characters. More than 80% of modern Chinese characters are phonetic compound characters and consist of sub-character components or radicals arranged under the orthographic rules. For example, a compound character (e.g., 盯, /ding1/, *stare*) consists of two parts: one component is called semantic radical (e.g., 目, *eye*), which carries the meaning information of a character, and another component called phonetic radical (丁, /ding1/), which provides the information about pronunciation of a character. The corpus study by Shu, Chen, Anderson, Wu, and Xuan (2003) showed that, in all of the characters taught in elementary schools, about 88% of the compound characters are semantic transparent (e.g. the character妈 (*mother*) is with a female radical "女") or semi-transparent (e.g. the character猎

Typical and Dyslexic Development in Learning to Read Chinese 17

Chow, McBride-Chang, & Burgess, 2005; Siok & Fletcher, 2001; Ho, Law, & Ng, 2000). Lexical tone is a fundamental feature of Chinese spoken language in which four tones are used to distinguish meanings that are not differentiated by segmental information. Studies showed that different levels of phonological awareness in Chinese emerge as the results of age or experience. Syllable and rhyme awareness appear to develop naturally with age in preschool children. However, onset and tone awareness appear to depend upon school

Rapid Automatized Naming (RAN) refers to tasks that require readers to name a list of familiar stimuli as rapidly as possible. RAN tasks were suggested to predict reading better in transparent orthographies than in opaque orthographies. However, recent studies have suggested RAN to be a consistent predictor of Chinese reading development, in which linking printed information with a given phonological representation arbitrarily is important. It predicts reading fluency and accuracy in both typically developing children and dyslexics (Ho & Lai, 1999; Ho et al., 2000; Shu, McBride-Chang, Wu, & Liu, 2006; Lei, Pan, Liu, McBride-Chang, Li, Zhang, Chen, Tardif, Liang, Zhang, & Shu, 2011; Pan,

To summarize, studies have reported a strong link between phonological awareness and character recognition in Chinese children (e.g., Siok & Fletcher, 2001; Shu et al., 2008). The role of morphological awareness, visual-orthographic skills, and rapid automatized naming in reading acquisition and impairment has also been demonstrated (e.g., Ho et al., 2004; Shu et al., 2006). What assessments can best examine those cognitive skills and are most sensitive to differences in reading ability at different stages of development? Li et al., (in press) administered 184 kindergarten children at age 5 to 6, and 273 primary school children at age 7 to 9 from Beijing with a comprehensive battery of tasks, including those for visualorthographic, phonological, morphological skills, rapid automatized naming abilities, and Chinese character recognition skills, in order to explore the cognitive correlates which can better predict Chinese reading acquisition across preschool and early grade levels. Visual Spatial Relationships and Visual Memory subtests were administered to test children's visual skills. An orthographic judgment task was created to measure orthographic awareness of Chinese children, in which children were asked to judge 4 types of critical items, including black and white line drawings (e.g. ), ill-formed structure with radicals in the illegal positions (e.g. ) , ill-formed components (e.g. ), and well-formed structure pseudo-characters items (e.g. ). Phonological awareness contained syllable deletion, rime detection, and phoneme deletion. Three tasks were designed for measurement of morphological awareness, specifically for knowledge of compound words, knowledge of homophones, and knowledge of homographs. The morphological construction task aims to test if children are able to decompose a compound word (大红花, *big red flower*) into morphemes (大 *big,* 红 *red,* 花*flower*) and construct a new compound word based on the new morphemes (e.g. "If a big flower that is red in color is called "大红花, *big red flower*", what should we call the big flower that is blue?" The correct answer is "大蓝花, *big blue flower")*. The homophone judgment task aims to test if children can distinguish the morphemes with the same sound but different meanings based on the compound word context. For example, the second syllable of the words "蛋(*egg*)糕(*cake*), /dan4-gao1/, *cake"*  and "跳(jump)高(high), /tiao4-gao1/, *high jump"* share the same sound /gao1/ but with different meanings "糕, *cake"* and "高, *high*". Children were asked to judge "If the

instruction (Shu, Peng, & McBride-Chang, 2008).

McBride-Chang, Shu, Liu, Zhang, & Li. in press).

(*hunting*) is with an animal radical "犭"). However, only about 39% of the compound characters are regular in pronunciation (e.g., the character 逗 /dou4/ is with the phonetic radical "豆" /dou4/).

The semantic and phonetic radicals may be further divided into about 600 subcomponents (e.g. 十, 口) which have fixed internal structures. The components or subcomponents are combined to form thousands of characters. Many of the radicals or components have their legal positions within the characters, although others can occur on flexible positions. For example, some components can appear only on the left (e.g. 扌), on the right (e.g.刂), on the top (艹) or on the bottom (灬) of characters. Awareness of inter-structure and position of components within characters are important in character recognition and it makes relatively greater demands on basic visual or orthographic analysis in Chinese reading. Previous studies have demonstrated that visual skill and orthographic awareness (e.g. Huang & Hanley, 1995; Ho & Bryant, 1997; Ho, Chan, Lee, Tsang, & Luan, 2004; Li, Peng, & Shu, 2006; Li, Shu, McBride-Chang, Liu, & Peng, in press) play significant roles in Chinese reading development. The brain mechanism of orthographic processing in Chinese reading were also reported in the fMRI studies (Liu, Zhang, Tang, Mai, Chen, Tardif & Luo, 2008; Tan, Liu, Perfetti, Spinks, Fox, & Gao, 2001; Wang, Yang, Shu & Zevin, 2011)

The unit of interface between the written word and spoken language in Chinese is *morpheme*. A character corresponds with one syllable and usually represents one morpheme. It makes morphological awareness potentially important in Chinese reading. Morphological awareness in Chinese is suggested to consist of three types of knowledge related to reading (Wu, Packard, & Shu, 2009). First, the fact that there are about 7,000 morphemes but only 1,200 syllables in Mandarin Chinese suggesting that more than five morphemes or characters share one syllable. Therefore the knowledge of homophones becomes important when reading Chinese, in which a reader is required to distinguish the homophone characters which share the same syllable (e.g. /yi4/) but with different morphemes (e.g. 义 *'meaning'*, 易*'easy'*, 亿 *'a hundred million'*, 宜 *'appropriate'*, 益 *'benefit'*, 艺 *'art'*, 议 *'discuss'*, and so on. The second is knowledge of homographs which requires a reader to be aware that a single written character (e.g. 草) may represent different morphemes ('grass' or 'careless'). The different morphemes contribute to the word's meaning when they are in different compound words (e.g. *'grass'* in 草地 *'lawn'* or *'careless'* in 草率 *'cursory'*). The third is knowledge of the morphemic structure of compound words which requires the awareness of the contribution of the individual morphemes (e.g. 飞 *'fly'* and 机 *'machine'*) to the meaning of the whole word (e.g. 飞机, *'airplane'*) . Because of the central role played by the morpheme in Chinese orthography, sensitivity to morphological knowledge is especially important in the development of oral and written vocabulary in Chinese. Morphological awareness is critically important for children learning to read and write, and emerges early and develops with age in preschool children (Chen, Hao, Geva, Zhu, & Shu, 2009; McBride-Chang, Shu, Zhou, Wat, & Wagner, 2003).

Chinese has a relatively simple syllable structure: a syllable consists of an onset and a rime and the combination is regular in spelling; mapping from spelling to sound is syllablebased. However, numerous studies on Chinese children's reading development and impairment have demonstrated that phonological skills, including syllable awareness, onset awareness and rime awareness, are associated with Chinese character recognition (e.g.

(*hunting*) is with an animal radical "犭"). However, only about 39% of the compound characters are regular in pronunciation (e.g., the character 逗 /dou4/ is with the phonetic

The semantic and phonetic radicals may be further divided into about 600 subcomponents (e.g. 十, 口) which have fixed internal structures. The components or subcomponents are combined to form thousands of characters. Many of the radicals or components have their legal positions within the characters, although others can occur on flexible positions. For example, some components can appear only on the left (e.g. 扌), on the right (e.g.刂), on the top (艹) or on the bottom (灬) of characters. Awareness of inter-structure and position of components within characters are important in character recognition and it makes relatively greater demands on basic visual or orthographic analysis in Chinese reading. Previous studies have demonstrated that visual skill and orthographic awareness (e.g. Huang & Hanley, 1995; Ho & Bryant, 1997; Ho, Chan, Lee, Tsang, & Luan, 2004; Li, Peng, & Shu, 2006; Li, Shu, McBride-Chang, Liu, & Peng, in press) play significant roles in Chinese reading development. The brain mechanism of orthographic processing in Chinese reading were also reported in the fMRI studies (Liu, Zhang, Tang, Mai, Chen, Tardif & Luo, 2008; Tan,

The unit of interface between the written word and spoken language in Chinese is *morpheme*. A character corresponds with one syllable and usually represents one morpheme. It makes morphological awareness potentially important in Chinese reading. Morphological awareness in Chinese is suggested to consist of three types of knowledge related to reading (Wu, Packard, & Shu, 2009). First, the fact that there are about 7,000 morphemes but only 1,200 syllables in Mandarin Chinese suggesting that more than five morphemes or characters share one syllable. Therefore the knowledge of homophones becomes important when reading Chinese, in which a reader is required to distinguish the homophone characters which share the same syllable (e.g. /yi4/) but with different morphemes (e.g. 义 *'meaning'*, 易*'easy'*, 亿 *'a hundred million'*, 宜 *'appropriate'*, 益 *'benefit'*, 艺 *'art'*, 议 *'discuss'*, and so on. The second is knowledge of homographs which requires a reader to be aware that a single written character (e.g. 草) may represent different morphemes ('grass' or 'careless'). The different morphemes contribute to the word's meaning when they are in different compound words (e.g. *'grass'* in 草地 *'lawn'* or *'careless'* in 草率 *'cursory'*). The third is knowledge of the morphemic structure of compound words which requires the awareness of the contribution of the individual morphemes (e.g. 飞 *'fly'* and 机 *'machine'*) to the meaning of the whole word (e.g. 飞机, *'airplane'*) . Because of the central role played by the morpheme in Chinese orthography, sensitivity to morphological knowledge is especially important in the development of oral and written vocabulary in Chinese. Morphological awareness is critically important for children learning to read and write, and emerges early and develops with age in preschool children (Chen, Hao, Geva, Zhu, & Shu, 2009; McBride-

Chinese has a relatively simple syllable structure: a syllable consists of an onset and a rime and the combination is regular in spelling; mapping from spelling to sound is syllablebased. However, numerous studies on Chinese children's reading development and impairment have demonstrated that phonological skills, including syllable awareness, onset awareness and rime awareness, are associated with Chinese character recognition (e.g.

Liu, Perfetti, Spinks, Fox, & Gao, 2001; Wang, Yang, Shu & Zevin, 2011)

Chang, Shu, Zhou, Wat, & Wagner, 2003).

radical "豆" /dou4/).

Chow, McBride-Chang, & Burgess, 2005; Siok & Fletcher, 2001; Ho, Law, & Ng, 2000). Lexical tone is a fundamental feature of Chinese spoken language in which four tones are used to distinguish meanings that are not differentiated by segmental information. Studies showed that different levels of phonological awareness in Chinese emerge as the results of age or experience. Syllable and rhyme awareness appear to develop naturally with age in preschool children. However, onset and tone awareness appear to depend upon school instruction (Shu, Peng, & McBride-Chang, 2008).

Rapid Automatized Naming (RAN) refers to tasks that require readers to name a list of familiar stimuli as rapidly as possible. RAN tasks were suggested to predict reading better in transparent orthographies than in opaque orthographies. However, recent studies have suggested RAN to be a consistent predictor of Chinese reading development, in which linking printed information with a given phonological representation arbitrarily is important. It predicts reading fluency and accuracy in both typically developing children and dyslexics (Ho & Lai, 1999; Ho et al., 2000; Shu, McBride-Chang, Wu, & Liu, 2006; Lei, Pan, Liu, McBride-Chang, Li, Zhang, Chen, Tardif, Liang, Zhang, & Shu, 2011; Pan, McBride-Chang, Shu, Liu, Zhang, & Li. in press).

To summarize, studies have reported a strong link between phonological awareness and character recognition in Chinese children (e.g., Siok & Fletcher, 2001; Shu et al., 2008). The role of morphological awareness, visual-orthographic skills, and rapid automatized naming in reading acquisition and impairment has also been demonstrated (e.g., Ho et al., 2004; Shu et al., 2006). What assessments can best examine those cognitive skills and are most sensitive to differences in reading ability at different stages of development? Li et al., (in press) administered 184 kindergarten children at age 5 to 6, and 273 primary school children at age 7 to 9 from Beijing with a comprehensive battery of tasks, including those for visualorthographic, phonological, morphological skills, rapid automatized naming abilities, and Chinese character recognition skills, in order to explore the cognitive correlates which can better predict Chinese reading acquisition across preschool and early grade levels. Visual Spatial Relationships and Visual Memory subtests were administered to test children's visual skills. An orthographic judgment task was created to measure orthographic awareness of Chinese children, in which children were asked to judge 4 types of critical items, including black and white line drawings (e.g. ), ill-formed structure with radicals in the illegal positions (e.g. ) , ill-formed components (e.g. ), and well-formed structure pseudo-characters items (e.g. ). Phonological awareness contained syllable deletion, rime detection, and phoneme deletion. Three tasks were designed for measurement of morphological awareness, specifically for knowledge of compound words, knowledge of homophones, and knowledge of homographs. The morphological construction task aims to test if children are able to decompose a compound word (大红花, *big red flower*) into morphemes (大 *big,* 红 *red,* 花*flower*) and construct a new compound word based on the new morphemes (e.g. "If a big flower that is red in color is called "大红花, *big red flower*", what should we call the big flower that is blue?" The correct answer is "大蓝花, *big blue flower")*. The homophone judgment task aims to test if children can distinguish the morphemes with the same sound but different meanings based on the compound word context. For example, the second syllable of the words "蛋(*egg*)糕(*cake*), /dan4-gao1/, *cake"*  and "跳(jump)高(high), /tiao4-gao1/, *high jump"* share the same sound /gao1/ but with different meanings "糕, *cake"* and "高, *high*". Children were asked to judge "If the

Typical and Dyslexic Development in Learning to Read Chinese 19

framework for understanding acquired and developmental dyslexia in Chinese derived from a cognitive neuropsychological account of reading and writing Chinese. Their model assumes that normal oral reading in Chinese depends on a division of labor between the lexical semantic pathway and a nonsemantic pathway. Impairment to the lexical semantic pathway will result in acquired surface dyslexia, while impairment to the nonsemantic pathway results in deep dyslexia. In a case study, Shu, Meng, Chen, Luan, and Cao, (2005) reported two types of dyslexic children, surface and deep, who showed the impairment in different pathways. Two dyslexic children, Child-L and Child-J, were tested by a word recognition task, in which they were asked to name a character and then to compose a compound word based on the target character. It was found that Child-L, identified as 'surface dyslexic', could correctly pronounce many of regular characters but made many regularization errors in irregular character naming. And Child-L also made many homophone errors when he composed a compound word based on the target character. According to Hillis and Caramazza (1995), the information from semantic-lexical and OPC routes integrate to provide the constraint for the selection of word pronunciation. For a Chinese reader, a compound character 拦 /lan2/*'obstruct'*may active a set of homophone characters /lan2/, and also active the characters with the meaning related with *'obstruct'.* The correct pronunciation and meaning of the character will be accessed with the two pathways. However, Child-L could correctly pronounce a target character (e.g. 拦 /lan2/) based on its phonetic cue (e.g. 兰 /lan2/), but he could not access the semantic information of the character. Then he composed a wrong compound word 篮子 /lan2 zi/, *'basket'* with a homophone character 篮 /lan2/, as illustrated in Figure 1. It suggests that as a surface dyslexic, Child-L normally developed the nonsemantic or sublexical route so that he could utilize phonetic radical information in character naming. But his semantic pathway was

developmentally delayed or deficient.

Fig. 1. An example of reading model for surface dyslexic Child L

compound words 蛋糕 /*dan4 gao1/* and 跳高 /*tiao4 gao1/* share the same morpheme /gao1/?" The correct answer is "No". Morpheme production task aimed to test if children can distinguish homographs, that is, the morphemes with same character and same sound, but with different meanings based on the compound word context. For example, the morpheme "明"in word "明(next)天(day), /*ming2 tian1/*, *tomorrow"* and"明(bright)亮(light), /*ming2 liang4/*, *brighten"* share the same character and same sound, but with the different meanings 'next' and *'bright'*. In the task, the experimenter spoke a word (e.g. "明(next)天(day), /*ming2 tian1/*, *tomorrow'* ) to children. Children were asked to produce two compound words containing the same character and sound but with different morphemes (homograph). The possible correct words are 明(next)年(year) /*ming2 nian2/* '*next year'* with the morpheme *'next'* and 明(bright)亮(light) /*ming2 liang4/*, '*brightness'* with the morpheme *'bright'*).

Regression analyses indicated that only syllable deletion, morphological construction, and speed number-naming were unique correlates of Chinese character recognition in kindergarten children. Among primary school children, the independent correlates of character recognition were rime detection, homophone judgment, morpheme production, orthographic knowledge, and speed number-naming. Results confirmed that phonological awareness, morphological awareness and speed naming are important in explaining character recognition for both kindergarten and lower grade primary school children. Orthographic awareness becomes significant to character recognition of school children as they learn to read. It is important to choose tasks which are suitable for the age of children that are being tested, since some tasks are sensitive to a wide range of ages, while others are more age-specific.

#### **3. Chinese children with dyslexia and its early prediction**

#### **3.1 The characteristics and core deficits of Chinese children with dyslexia**

About 5%-10% of school-aged children, in any language, have a persistent difficulty in learning to read that could not be explained by sensory deficits, low general intelligence, poor educational opportunity, or lack of motivation (Fisher, DeFries, 2002; Shaywitz, Shaywitz, Fletcher, Escobar, 1990). However, for a long time developmental dyslexia was believed to be a problem that exists only in western languages, since the strong assumption that phonological awareness has a major impact on the acquisition of literacy only in alphabetic languages. Since Stevenson, Stigler, Lucker, Lee, Hsu, and Kitamura (1982) first found that the prevalence of dyslexia among American, Japanese and Chinese children is comparable, a great number of studies in Hong Kong, Taiwan and Mainland China have congruously reported that between 5% and 10% of school-aged children in Chinese were dyslexic in the past years (Zhang, Zhang, Yin, Zhou, & Chang, 1996; Yin and Weekes, 2003). Research has revealed that, just like in alphabetic languages, dyslexic children in Chinese mainly suffered from the accuracy and speed of word reading and spelling, so that reading measures widely used in distinguishing dyslexic from normal children are single character or word recognition measures ((Ho, et. al, 2002, 2004; Meng, Shu & Zhou, 1999; Shu, Wu, McBride-Chang, 2006).

According to the dual-route model of reading, mapping from print to sound is achieved through at least two pathways, a lexical semantic route and a nonsematic GPC route (Coltheart, Rastle, Perry, Langdon & Ziegler, 2001). Yin and Weekes (2003) proposed a

developmentally delayed or deficient.

18 Dyslexia – A Comprehensive and International Approach

compound words 蛋糕 /*dan4 gao1/* and 跳高 /*tiao4 gao1/* share the same morpheme /gao1/?" The correct answer is "No". Morpheme production task aimed to test if children can distinguish homographs, that is, the morphemes with same character and same sound, but with different meanings based on the compound word context. For example, the morpheme "明"in word "明(next)天(day), /*ming2 tian1/*, *tomorrow"* and"明(bright)亮(light), /*ming2 liang4/*, *brighten"* share the same character and same sound, but with the different meanings 'next' and *'bright'*. In the task, the experimenter spoke a word (e.g. "明(next)天(day), /*ming2 tian1/*, *tomorrow'* ) to children. Children were asked to produce two compound words containing the same character and sound but with different morphemes (homograph). The possible correct words are 明(next)年(year) /*ming2 nian2/* '*next year'* with the morpheme *'next'*

Regression analyses indicated that only syllable deletion, morphological construction, and speed number-naming were unique correlates of Chinese character recognition in kindergarten children. Among primary school children, the independent correlates of character recognition were rime detection, homophone judgment, morpheme production, orthographic knowledge, and speed number-naming. Results confirmed that phonological awareness, morphological awareness and speed naming are important in explaining character recognition for both kindergarten and lower grade primary school children. Orthographic awareness becomes significant to character recognition of school children as they learn to read. It is important to choose tasks which are suitable for the age of children that are being tested, since some tasks are sensitive to a wide range of ages, while others are

and 明(bright)亮(light) /*ming2 liang4/*, '*brightness'* with the morpheme *'bright'*).

**3. Chinese children with dyslexia and its early prediction** 

**3.1 The characteristics and core deficits of Chinese children with dyslexia** 

About 5%-10% of school-aged children, in any language, have a persistent difficulty in learning to read that could not be explained by sensory deficits, low general intelligence, poor educational opportunity, or lack of motivation (Fisher, DeFries, 2002; Shaywitz, Shaywitz, Fletcher, Escobar, 1990). However, for a long time developmental dyslexia was believed to be a problem that exists only in western languages, since the strong assumption that phonological awareness has a major impact on the acquisition of literacy only in alphabetic languages. Since Stevenson, Stigler, Lucker, Lee, Hsu, and Kitamura (1982) first found that the prevalence of dyslexia among American, Japanese and Chinese children is comparable, a great number of studies in Hong Kong, Taiwan and Mainland China have congruously reported that between 5% and 10% of school-aged children in Chinese were dyslexic in the past years (Zhang, Zhang, Yin, Zhou, & Chang, 1996; Yin and Weekes, 2003). Research has revealed that, just like in alphabetic languages, dyslexic children in Chinese mainly suffered from the accuracy and speed of word reading and spelling, so that reading measures widely used in distinguishing dyslexic from normal children are single character or word recognition measures ((Ho, et. al, 2002, 2004; Meng, Shu & Zhou, 1999; Shu, Wu,

According to the dual-route model of reading, mapping from print to sound is achieved through at least two pathways, a lexical semantic route and a nonsematic GPC route (Coltheart, Rastle, Perry, Langdon & Ziegler, 2001). Yin and Weekes (2003) proposed a

more age-specific.

McBride-Chang, 2006).

framework for understanding acquired and developmental dyslexia in Chinese derived from a cognitive neuropsychological account of reading and writing Chinese. Their model assumes that normal oral reading in Chinese depends on a division of labor between the lexical semantic pathway and a nonsemantic pathway. Impairment to the lexical semantic pathway will result in acquired surface dyslexia, while impairment to the nonsemantic pathway results in deep dyslexia. In a case study, Shu, Meng, Chen, Luan, and Cao, (2005) reported two types of dyslexic children, surface and deep, who showed the impairment in different pathways. Two dyslexic children, Child-L and Child-J, were tested by a word recognition task, in which they were asked to name a character and then to compose a compound word based on the target character. It was found that Child-L, identified as 'surface dyslexic', could correctly pronounce many of regular characters but made many regularization errors in irregular character naming. And Child-L also made many homophone errors when he composed a compound word based on the target character. According to Hillis and Caramazza (1995), the information from semantic-lexical and OPC routes integrate to provide the constraint for the selection of word pronunciation. For a Chinese reader, a compound character 拦 /lan2/*'obstruct'*may active a set of homophone characters /lan2/, and also active the characters with the meaning related with *'obstruct'.* The correct pronunciation and meaning of the character will be accessed with the two pathways. However, Child-L could correctly pronounce a target character (e.g. 拦 /lan2/) based on its phonetic cue (e.g. 兰 /lan2/), but he could not access the semantic information of the character. Then he composed a wrong compound word 篮子 /lan2 zi/, *'basket'* with a homophone character 篮 /lan2/, as illustrated in Figure 1. It suggests that as a surface dyslexic, Child-L normally developed the nonsemantic or sublexical route so that he could utilize phonetic radical information in character naming. But his semantic pathway was

Fig. 1. An example of reading model for surface dyslexic Child L

Typical and Dyslexic Development in Learning to Read Chinese 21

Research has revealed that phonological, naming-speed and orthographic deficits are important features in Chinese dyslexic children. Testing 147 Hong Kong children with dyslexia on a number of literacy and cognitive tasks, Ho, et al. (2004) found that rapid naming deficit (57%) and orthographic deficit (42%) were the most dominant types of cognitive deficits in Chinese developmental dyslexia, while the relatively small proportion

Shu, et al. (2006) specifically examined the role of morphological skills in Chinese dyslexia besides other cognitive skills. Comparing 75 dyslexic with 77 normal children from primary schools in Beijing, the study systematically examined their literacy skills (character naming, reading comprehension, and dictation), linguistic and nonlinguistic cognitive skills with morphological awareness, rapid naming, phonological awareness, verbal short-term memory, lexical vocabulary, visual spatial test, articulatory rate, visual attention and nonverbal short-term memory tasks. In the logistic regression analysis, dyslexic children were found to be best distinguished from age-matched controls with tasks of morphological awareness, speeded number naming and vocabulary skills, while performance on tasks of visual skills and phonological awareness failed to distinguish the two groups. Path analysis revealed that phonological awareness, morphological awareness and rapid naming were all uniquely associated with the three literacy tasks: character recognition, reading comprehension and dictation. Based on the same data, Wu (2004) further found that, compared with phonological (53%) and speed (45%) problems, the largest proportion (96%) of dyslexic children had morphological problems. Figure 3 shows all the children with

Fig. 3. Classification of dyslexic outliers by morphology, phonology, vocabulary and rapid

naming. (from Wu, 2004).

of dyslexic children has phonological deficits (29%) and visual deficits (27%).

dyslexia grouped by their deviant performance on the different tasks.

In contrast, Child-J, identified as 'deep dyslexic', made a relatively large percentage of semantic related errors (26%) in pronunciation. For example, he named the character 煎 /jian1/ *'fry',* which is with the phonetic 前 /qan2/, as 炖 /dun4/ *'braise',* a character which is semantically related with the target character煎*'fry'*, but with the phonetic 屯 /tun2/. He composed a compound word炖肉 /dun4-rou4/ *'stew',* (see Figure 2). It is clear that he ignored the phonological information provided by the phonetic 前 /qan2/ of the target character煎 /jian1/, but accessed the meaning of the target 煎*'fry'* and also the characters with the meanings related with *'fry'* were activated. Child-J's performance showed the characteristics of deep dyslexia. That is, his nonsemantic pathway was developmentally delayed or deficient, but his semantic pathway was relatively normal.

Fig. 2. An example of reading model for deep dyslexic Child J

The resulting patterns of the two children support the framework proposed by Yin and Weekes (2003) that surface dyslexia (Child-L) may be explained by developmental delay or deficit in the *semantic* pathway and deep dyslexia (Child J) can be explained by delay or deficit in the *nonsemantic* pathway in reading acquisition. The impairment in different pathways could explain the fact that child L could not distinguish the target from homophone characters, and child J could not utilize sublexical phonetic information in pronunciation. The response patterns of the dyslexic children were simulated and confirmed by the results from a triangle model in Chinese (Yang, McCandliss, Shu, & Zevin, 2008).

Phonological deficit has been treated as the main cause of developmental dyslexia and sufficient to explain poor reading performance in alphabetic languages (Bradley & Bryant, 1983; Ramus, 2003; Snowling, 2000; Ziegler, Bertrand, Tórth, Csépe, Reis, Faísca, Saine, Lyytinen, Vaessen, & Blomert, 2010). However, the important links of cognitive skills with reading success and failure vary across orthographies (Ziegler & Goswami, 2005; Lyytinen, Erskine, Tolvanen, Torppa, Poikkeus, & Lyytinen, 2006). What are the core deficits for dyslexic children in Chinese?

In contrast, Child-J, identified as 'deep dyslexic', made a relatively large percentage of semantic related errors (26%) in pronunciation. For example, he named the character 煎 /jian1/ *'fry',* which is with the phonetic 前 /qan2/, as 炖 /dun4/ *'braise',* a character which is semantically related with the target character煎*'fry'*, but with the phonetic 屯 /tun2/. He composed a compound word炖肉 /dun4-rou4/ *'stew',* (see Figure 2). It is clear that he ignored the phonological information provided by the phonetic 前 /qan2/ of the target character煎 /jian1/, but accessed the meaning of the target 煎*'fry'* and also the characters with the meanings related with *'fry'* were activated. Child-J's performance showed the characteristics of deep dyslexia. That is, his nonsemantic pathway was developmentally

delayed or deficient, but his semantic pathway was relatively normal.

Fig. 2. An example of reading model for deep dyslexic Child J

dyslexic children in Chinese?

The resulting patterns of the two children support the framework proposed by Yin and Weekes (2003) that surface dyslexia (Child-L) may be explained by developmental delay or deficit in the *semantic* pathway and deep dyslexia (Child J) can be explained by delay or deficit in the *nonsemantic* pathway in reading acquisition. The impairment in different pathways could explain the fact that child L could not distinguish the target from homophone characters, and child J could not utilize sublexical phonetic information in pronunciation. The response patterns of the dyslexic children were simulated and confirmed by the results from a triangle model in Chinese (Yang, McCandliss, Shu, & Zevin, 2008).

Phonological deficit has been treated as the main cause of developmental dyslexia and sufficient to explain poor reading performance in alphabetic languages (Bradley & Bryant, 1983; Ramus, 2003; Snowling, 2000; Ziegler, Bertrand, Tórth, Csépe, Reis, Faísca, Saine, Lyytinen, Vaessen, & Blomert, 2010). However, the important links of cognitive skills with reading success and failure vary across orthographies (Ziegler & Goswami, 2005; Lyytinen, Erskine, Tolvanen, Torppa, Poikkeus, & Lyytinen, 2006). What are the core deficits for Research has revealed that phonological, naming-speed and orthographic deficits are important features in Chinese dyslexic children. Testing 147 Hong Kong children with dyslexia on a number of literacy and cognitive tasks, Ho, et al. (2004) found that rapid naming deficit (57%) and orthographic deficit (42%) were the most dominant types of cognitive deficits in Chinese developmental dyslexia, while the relatively small proportion of dyslexic children has phonological deficits (29%) and visual deficits (27%).

Shu, et al. (2006) specifically examined the role of morphological skills in Chinese dyslexia besides other cognitive skills. Comparing 75 dyslexic with 77 normal children from primary schools in Beijing, the study systematically examined their literacy skills (character naming, reading comprehension, and dictation), linguistic and nonlinguistic cognitive skills with morphological awareness, rapid naming, phonological awareness, verbal short-term memory, lexical vocabulary, visual spatial test, articulatory rate, visual attention and nonverbal short-term memory tasks. In the logistic regression analysis, dyslexic children were found to be best distinguished from age-matched controls with tasks of morphological awareness, speeded number naming and vocabulary skills, while performance on tasks of visual skills and phonological awareness failed to distinguish the two groups. Path analysis revealed that phonological awareness, morphological awareness and rapid naming were all uniquely associated with the three literacy tasks: character recognition, reading comprehension and dictation. Based on the same data, Wu (2004) further found that, compared with phonological (53%) and speed (45%) problems, the largest proportion (96%) of dyslexic children had morphological problems. Figure 3 shows all the children with dyslexia grouped by their deviant performance on the different tasks.

Fig. 3. Classification of dyslexic outliers by morphology, phonology, vocabulary and rapid naming. (from Wu, 2004).

Typical and Dyslexic Development in Learning to Read Chinese 23

Lei et al. (2011) reported a 10-year longitudinal study in Beijing which revealed the dynamic change of reading disabled children and their heterogeneous characteristics in development. 261 children were followed from 3 to 8 years old. They were administered 7 language and cognitive skills (Compound awareness, Grammatical skill, Nonword repetition, Syllable deletion, Morphological construction, Rapid automatized naming, Vocabulary definition) between ages three and six, and then literacy skills (Character recognition, and Reading fluency) were tested at age eight. Individual differences in developmental profiles across tasks were estimated using growth mixture modeling which identified not only the important early predictors but also different subgroups with different developmental trajectories. The results showed that there were four developmental trajectories from ages

three to six years and two of them were identified as poor readers (see Figure 4).

Note: CA-Compound awareness, GS-Grammatical skill, NR-Nonword repetition, SD-Syllable deletion, MC-Morphological construction, RN-Rapid automatized naming, VD-Vocabulary definition, CR-

The initial level and subsequent growth on three deficits together (phonological awareness, morphological awareness and rapid naming) from age three to six were best to predict their reading difficulties at age eight. Early language deficits in addition to a combination of deficits in phonological awareness, morphological awareness, and rapid naming might lead to more severe reading problems for Chinese children. The results from the longitudinal study support those from dyslexic and control group comparison studies (e.g., Shu et al., 2006), suggesting that phonological awareness, morphological awareness, and rapid naming should be simultaneously considered in Chinese, given the use of broad skills required to

Fig. 4. Subgroup members' average performance in the seven skills and in reading.

Character recognition, and RF-Reading fluency (from Lei, 2008).

learn to read this orthography.

The significance of morphological awareness was supported in a following study in which children with and without dyslexia were tested on the tasks including paired associative learning (visual-visual and visual-verbal PAL), phonological awareness, morphological awareness, rapid naming, verbal short-term memory and character recognition. The logistic regression demonstrated that morphological awareness, rapid naming and visual-verbal PAL uniquely distinguished children with and without dyslexia, even with other metalinguistic skills controlled (Li et al., 2009).

Researchers found that Chinese children with dyslexia tend to possess more than one kind of cognitive deficits. Ho, et al. (2002) reported that 20% of the dyslexic children have only one deficit and about 50% of dyslexic children possess more than two deficits. In Wu, et al. (2009) study, the results further confirmed that 24% of the dyslexic children were found to have only one deficit and about 80% of dyslexic children possessed more than one deficit.

#### **3.2 Early prediction of reading acquisition and impairment**

Dyslexia has been defined as a developmental disorder starting at childhood. Many factors interact to shape children's language and reading development before they start school. However, dyslexic children usually are diagnosed after they failed in learning to read at school. Could children with reading difficulties at school be identified at an earlier stage? Longitudinal research provides the best way to understand early prediction of reading acquisition and impairment. Longitudinal studies in alphabetic languages have revealed that slow vocabulary development, language grammatical skills, phonological awareness, rapid naming, and letter knowledge begin to differ between children with and without risk for dyslexia around 3 or 4 years old (Lyytinen et al., 2006). Research even reported that ERP response to speech sound at 6 month discriminated infants with familial risk for reading disorder at age 8 (Leppänen, Richardson, Pihko, Eklund, Guttorm, Aro, & Lyytinen,, 2002). What are the most effective early predictors for reading development and impairment in Chinese? Are we able to identify latent poor readers from early indicators?

In recent years, several studies explored those questions through longitudinal studies. Liu, McBride-Chang, Wong, Tardif, Stokes, Fletcher, and Shu (2009) investigated the extent to which language skills at ages 2 to 4 years could discriminate Hong Kong Chinese poor from adequate readers at age 7. It was found that children's performance at age 2 in vocabulary knowledge, at age 3 in Cantonese articulation, and age 4 receptive grammar skill, sentence imitation, and story comprehension can best predict the word recognition performance between the poor and adequate readers at age 7.

McBride-Chang, Lam, Lam, Doo, Wong, and Chow (2008) found that the group of Hong Kong children with a genetic risk for dyslexia showed particular difficulties in lexical tone detection, morphological awareness, and Chinese word reading, whereas the language delayed group performed more poorly in all tasks administered. Their follow-up study (McBridge-Chang, et al., 2011) further reported that 62% of the children with an early language delay subsequently manifested dyslexia and 50% of those with familial risk become dyslexic at school. The deficits which best distinguish dyslexic from nondyslexic children at age 7 were morphological awareness, rapid automatized naming, and word reading at age 5, suggesting that rapid automatized naming and morphological awareness are relatively strong correlates of developmental dyslexia in Chinese.

The significance of morphological awareness was supported in a following study in which children with and without dyslexia were tested on the tasks including paired associative learning (visual-visual and visual-verbal PAL), phonological awareness, morphological awareness, rapid naming, verbal short-term memory and character recognition. The logistic regression demonstrated that morphological awareness, rapid naming and visual-verbal PAL uniquely distinguished children with and without dyslexia, even with other

Researchers found that Chinese children with dyslexia tend to possess more than one kind of cognitive deficits. Ho, et al. (2002) reported that 20% of the dyslexic children have only one deficit and about 50% of dyslexic children possess more than two deficits. In Wu, et al. (2009) study, the results further confirmed that 24% of the dyslexic children were found to have only one deficit and about 80% of dyslexic children possessed more than one deficit.

Dyslexia has been defined as a developmental disorder starting at childhood. Many factors interact to shape children's language and reading development before they start school. However, dyslexic children usually are diagnosed after they failed in learning to read at school. Could children with reading difficulties at school be identified at an earlier stage? Longitudinal research provides the best way to understand early prediction of reading acquisition and impairment. Longitudinal studies in alphabetic languages have revealed that slow vocabulary development, language grammatical skills, phonological awareness, rapid naming, and letter knowledge begin to differ between children with and without risk for dyslexia around 3 or 4 years old (Lyytinen et al., 2006). Research even reported that ERP response to speech sound at 6 month discriminated infants with familial risk for reading disorder at age 8 (Leppänen, Richardson, Pihko, Eklund, Guttorm, Aro, & Lyytinen,, 2002). What are the most effective early predictors for reading development and impairment in

In recent years, several studies explored those questions through longitudinal studies. Liu, McBride-Chang, Wong, Tardif, Stokes, Fletcher, and Shu (2009) investigated the extent to which language skills at ages 2 to 4 years could discriminate Hong Kong Chinese poor from adequate readers at age 7. It was found that children's performance at age 2 in vocabulary knowledge, at age 3 in Cantonese articulation, and age 4 receptive grammar skill, sentence imitation, and story comprehension can best predict the word recognition performance

McBride-Chang, Lam, Lam, Doo, Wong, and Chow (2008) found that the group of Hong Kong children with a genetic risk for dyslexia showed particular difficulties in lexical tone detection, morphological awareness, and Chinese word reading, whereas the language delayed group performed more poorly in all tasks administered. Their follow-up study (McBridge-Chang, et al., 2011) further reported that 62% of the children with an early language delay subsequently manifested dyslexia and 50% of those with familial risk become dyslexic at school. The deficits which best distinguish dyslexic from nondyslexic children at age 7 were morphological awareness, rapid automatized naming, and word reading at age 5, suggesting that rapid automatized naming and morphological awareness

metalinguistic skills controlled (Li et al., 2009).

**3.2 Early prediction of reading acquisition and impairment** 

Chinese? Are we able to identify latent poor readers from early indicators?

are relatively strong correlates of developmental dyslexia in Chinese.

between the poor and adequate readers at age 7.

Lei et al. (2011) reported a 10-year longitudinal study in Beijing which revealed the dynamic change of reading disabled children and their heterogeneous characteristics in development. 261 children were followed from 3 to 8 years old. They were administered 7 language and cognitive skills (Compound awareness, Grammatical skill, Nonword repetition, Syllable deletion, Morphological construction, Rapid automatized naming, Vocabulary definition) between ages three and six, and then literacy skills (Character recognition, and Reading fluency) were tested at age eight. Individual differences in developmental profiles across tasks were estimated using growth mixture modeling which identified not only the important early predictors but also different subgroups with different developmental trajectories. The results showed that there were four developmental trajectories from ages three to six years and two of them were identified as poor readers (see Figure 4).

Note: CA-Compound awareness, GS-Grammatical skill, NR-Nonword repetition, SD-Syllable deletion, MC-Morphological construction, RN-Rapid automatized naming, VD-Vocabulary definition, CR-Character recognition, and RF-Reading fluency (from Lei, 2008).

Fig. 4. Subgroup members' average performance in the seven skills and in reading.

The initial level and subsequent growth on three deficits together (phonological awareness, morphological awareness and rapid naming) from age three to six were best to predict their reading difficulties at age eight. Early language deficits in addition to a combination of deficits in phonological awareness, morphological awareness, and rapid naming might lead to more severe reading problems for Chinese children. The results from the longitudinal study support those from dyslexic and control group comparison studies (e.g., Shu et al., 2006), suggesting that phonological awareness, morphological awareness, and rapid naming should be simultaneously considered in Chinese, given the use of broad skills required to learn to read this orthography.

Typical and Dyslexic Development in Learning to Read Chinese 25

Chow, Y.-W., McBride-Chang, C., & Burgess, S. (2005). Phonological Processing Skills and

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#### **4. Conclusions**

In summary, the research confirmed some universal aspects of reading acquisition in alphabetic languages and in Chinese. Just like in alphabetic languages, Chinese children with dyslexia have mainly deficits in the accuracy and speed of character or word recognition. Mastery of a writing system depends upon acquiring an adequate phonological knowledge of the language, especially in early age. Phonological awareness and namingspeed are the two deficits shared by both dyslexic children in Chinese and in alphabetic languages. The specific aspects of reading acquisition in Chinese are related with the characteristic of Chinese language and orthography. It makes morphological and orthographic awareness particularly important to consider in understanding Chinese reading development and dyslexia. Furthermore, most of Chinese children with dyslexia tend to have more than one kind of cognitive deficits. The longitudinal studies reveal that it is possible to identify the school-age poor readers from early stage. The effective predictors include phonological awareness, morphological awareness, rapid naming and oral vocabulary.

In the future, more basic research is needed in order to understand further the cognitive causes of reading failures of Chinese children and the underlying brain mechanism.

Although it has not been discussed in this chapter, systematic work is also needed to explore the role of family and education environment on children's reading acquisition and dyslexia; With family's support and better education environment, more effective assessments could be developed, and early predictors for which children with dyslexia or children at risk for dyslexia could be identified; and in turn better intervention programmes for both preschool and school children could be developed, which could improve dyslexic children's reading ability and reduce the risk of the reading failures.

#### **5. Acknowledgment**

The research work was supported by a grant from the Natural Science Foundation of China (30870758), by a grant from Fundamental Research Fund for the Central Universities. It also was a part of a project of Beijing Key Lab of Applied Experimental Psychology supported by the Beijing Educational Committee and Beijing Science and Technology Committee.

#### **6. References**


In summary, the research confirmed some universal aspects of reading acquisition in alphabetic languages and in Chinese. Just like in alphabetic languages, Chinese children with dyslexia have mainly deficits in the accuracy and speed of character or word recognition. Mastery of a writing system depends upon acquiring an adequate phonological knowledge of the language, especially in early age. Phonological awareness and namingspeed are the two deficits shared by both dyslexic children in Chinese and in alphabetic languages. The specific aspects of reading acquisition in Chinese are related with the characteristic of Chinese language and orthography. It makes morphological and orthographic awareness particularly important to consider in understanding Chinese reading development and dyslexia. Furthermore, most of Chinese children with dyslexia tend to have more than one kind of cognitive deficits. The longitudinal studies reveal that it is possible to identify the school-age poor readers from early stage. The effective predictors include phonological awareness, morphological awareness, rapid naming and oral

In the future, more basic research is needed in order to understand further the cognitive

Although it has not been discussed in this chapter, systematic work is also needed to explore the role of family and education environment on children's reading acquisition and dyslexia; With family's support and better education environment, more effective assessments could be developed, and early predictors for which children with dyslexia or children at risk for dyslexia could be identified; and in turn better intervention programmes for both preschool and school children could be developed, which could improve dyslexic

The research work was supported by a grant from the Natural Science Foundation of China (30870758), by a grant from Fundamental Research Fund for the Central Universities. It also was a part of a project of Beijing Key Lab of Applied Experimental Psychology supported by the Beijing Educational Committee and Beijing Science and

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**3** 

*Spain* 

Juan E. Jiménez

**The Role of Phonological Processing in** 

This chapter presents theoretical arguments and empirical evidence to support the idea that the phonological deficit in dyslexia in a language with a transparent orthography such as Spanish is at the phoneme level in the phonological awareness continuum, suggesting that a phonemic deficit is curtailing the development of phonological decoding. Results of two studies are presented to demonstrate the role of phonological processing in dyslexia in the Spanish language. The first study examines the dyslexic subtypes within the context of a reading-level match in a transparent orthography. In this research we explored whether developmental dyslexics form a homogeneous population, with a unique underlying impairment, or whether they form distinct subgroups. The second study examines the effects of a computer-assisted intervention designed to improve the visual word recognition

The classical phonological explanation ascribes dyslexics' reading deficit to a specific cognitive deficiency in phonological processing, primarily, in phonemic awareness and in

Nevertheless, other current non-phonological explanations according to which dyslexics' phonological deficit is secondary to more basic sensori-motor impairment: a deficiency in either rapid auditory processing, or in the visual magnocellular pathway, or in motor skills

Deficits in phonological awareness have been identified as the critical factor underlying the severe word decoding problems displayed by individuals with reading difficulties in languages with an opaque orthography such as English (Goswami & Bryant, 1990). Studies in English have found phonemic deficits in dyslexic children compared to children matched by chronological age (CA) or by reading level (RL) (Olson, 1994). In addition, dyslexic children appear to have more difficulty reading nonwords than nondisabled readers matched in age or in reading level supporting the deficit model in phonological processing (Rack, Snowling, & Olson, 1992). However, Goswami (2002, p. 150) suggests that "the consistency of the phoneme-grapheme correspondences in languages with a transparent orthography such as Spanish should facilitate the further development of both phonemic awareness and grapheme-phoneme recoding skills. These skills would, therefore, be expected to develop more slowly in dyslexic children learning to read in such consistent

of Spanish-speaking children identified with a learning disability (LD).

(see for a review, Sprenger-Charolles, Colé, & Serniclaes, 2006).

orthographies, but they would not be expected to be massively disrupted".

**1. Introduction** 

phonological short-term memory.

**Dyslexia in the Spanish Language** 

*University of La Laguna, The Canary Islands,* 

Ziegler, J. C., & Goswami, U. (2005). Reading acquisition, developmental dyslexia, and skilled reading across languages: A psycholinguistic grain size theory. *Psychological Bulletin, 131,* 3-29.

## **The Role of Phonological Processing in Dyslexia in the Spanish Language**

Juan E. Jiménez *University of La Laguna, The Canary Islands, Spain* 

#### **1. Introduction**

28 Dyslexia – A Comprehensive and International Approach

Ziegler, J. C., & Goswami, U. (2005). Reading acquisition, developmental dyslexia, and

*Bulletin, 131,* 3-29.

skilled reading across languages: A psycholinguistic grain size theory. *Psychological* 

This chapter presents theoretical arguments and empirical evidence to support the idea that the phonological deficit in dyslexia in a language with a transparent orthography such as Spanish is at the phoneme level in the phonological awareness continuum, suggesting that a phonemic deficit is curtailing the development of phonological decoding. Results of two studies are presented to demonstrate the role of phonological processing in dyslexia in the Spanish language. The first study examines the dyslexic subtypes within the context of a reading-level match in a transparent orthography. In this research we explored whether developmental dyslexics form a homogeneous population, with a unique underlying impairment, or whether they form distinct subgroups. The second study examines the effects of a computer-assisted intervention designed to improve the visual word recognition of Spanish-speaking children identified with a learning disability (LD).

The classical phonological explanation ascribes dyslexics' reading deficit to a specific cognitive deficiency in phonological processing, primarily, in phonemic awareness and in phonological short-term memory.

Nevertheless, other current non-phonological explanations according to which dyslexics' phonological deficit is secondary to more basic sensori-motor impairment: a deficiency in either rapid auditory processing, or in the visual magnocellular pathway, or in motor skills (see for a review, Sprenger-Charolles, Colé, & Serniclaes, 2006).

Deficits in phonological awareness have been identified as the critical factor underlying the severe word decoding problems displayed by individuals with reading difficulties in languages with an opaque orthography such as English (Goswami & Bryant, 1990). Studies in English have found phonemic deficits in dyslexic children compared to children matched by chronological age (CA) or by reading level (RL) (Olson, 1994). In addition, dyslexic children appear to have more difficulty reading nonwords than nondisabled readers matched in age or in reading level supporting the deficit model in phonological processing (Rack, Snowling, & Olson, 1992). However, Goswami (2002, p. 150) suggests that "the consistency of the phoneme-grapheme correspondences in languages with a transparent orthography such as Spanish should facilitate the further development of both phonemic awareness and grapheme-phoneme recoding skills. These skills would, therefore, be expected to develop more slowly in dyslexic children learning to read in such consistent orthographies, but they would not be expected to be massively disrupted".

The Role of Phonological Processing in Dyslexia in the Spanish Language 31

all studies included a standard measure of lexical processing (i.e., irregular word reading) because it is impossible to find enough irregular words in some of the languages (e.g., Spanish) included in the review. Findings indicated a higher incidence rate of phonological dyslexia in English in comparison to other languages (e.g., Wydell & Butterworth, 1999; Wydell & Kondo 2003) where researchers found a higher incidence of surface dyslexia. Note that surface dyslexia is characterized by impaired orthographic skills and fairly wellpreserved phonological skills (Stanovich, et al., 1997b), while a phonological dyslexia is characterized by impaired phonological skills and fairly well-preserved orthographic skills (Castles & Coltheart, 1993; Manis, Seidenberg, Doi, McBridge-Chang & Petersen, 1996;

Thus, studies that indicate the extent to which the dual-route hypothesis (i.e., differences between phonological and surface dyslexia (e.g., Manis, et al, 1996; Stanovich, et al, 1997b) is also applicable to languages with a transparent orthography, are still necessary. Moreover, studies designed to demonstrate that the consistency of mappings from graphemes to phonemes in different languages has a marked effect on the development of phonemic awareness and of grapheme-phoneme recoding strategies in dyslexic children are necessary. Two Spanish studies of dyslexic subtypes and computer-assisted practice on visual word recognition are presented here to provide empirical evidence in favor of the deficit model in phonological processing in a transparent orthography. Next we report results of the two

**2. Study 1: Identifying dyslexic subtypes in a transparent orthography** 

A question posed by reading researchers is whether readers with developmental dyslexia form a homogeneous group with a unique underlying impairment, or whether this group actually consists of distinct subgroups. In English, research indicates the existence of two distinct profiles of developmental dyslexia. In our own review of studies of dyslexic performance patterns, we have found the opposite pattern when we reviewed studies conducted in orthographies less opaque than English (e.g., Swedish: Wolff, 2009). These discrepancies between the Spanish versus the anglophone or francophone studies may be due to (a) linguistic factors, (b) the measures used, and (c) differences in the dyslexics' chronological age. Given that grapheme-phoneme correspondences are more regular in Spanish than in English and in French, Spanish-speaking dyslexics may manage to use the sublexical reading route with less difficulty than English-speaking or French speaking dyslexics. This could explain why fewer phonological dyslexics were found in languages that are less opaque than English. A similar trend was observed when time measures were used in Spanish or in French (Genard et al., 1998) suggesting that the phonological deficit of Spanish-speaking dyslexics manifests itself as slow processing more than in accuracy.

The study presented here was first published by Jiménez and Ramirez (2002) and replicated later by Jiménez, Rodríguez, and Ramírez (2009). It employed the same procedure used by Castles and Coltheart (1993) for identifying dyslexic subtypes based on pseudoword and irregular word reading. Given that Spanish does not have any irregular words, we compared the reaction times (RTs) of students reading high frequency words and pseudowords between the group of dyslexic children and the group of children similar in

Stanovich, Siegel & Gottardo, 1997b).

chronological-age, and reading-level (RL).

studies.

However, empirical evidence in Spanish indicates that dyslexic children exhibit the same difficulties in phonemic segmentation exhibited by older English dyslexic children (Jiménez, 1997). For example, Jiménez (1997) analyzed phoneme awareness within the context of a reading-level match design, demonstrating a deficit in the Spanish reading disabled (RD) children in phonemic tasks, but not in intrasyllabic tasks. In another study, Jiménez et al. (2005) examined the effects of linguistic complexity (e.g., complexity in the syllable structure) and task differences without taking into account verbal working memory. The assumption was that if students, identified as dyslexic, performed worse in a phonemic task compared to RL and CA matched children, the hypothesis of a phonemic deficit in explaining dyslexia in a transparent orthography would be confirmed. Results indicated that the complexity of the syllable structure had no particularly marked effect on the dyslexic children. Rather, the isolation task revealed the phonological deficit across all syllable structures.

Jiménez, García and Venegas (2008) examined whether phonological processes are the same or different in low literacy adults and children with or without reading disabilities in a transparent orthography. They selected a sample of 150 subjects organized into four different groups: (1) 53 low literacy adults, (2) 29 reading disabled children, (3) 27 younger normal readers at the same reading level as those with reading disabilities and low literacy adults, and (4) 41 normal readers matched in age with the reading disabled group. Phonological awareness tasks that included different complexities of the syllable structure (e.g., words with CV and CCV structure) were administered. Results indicated that the complexity of the syllable structure did not have a significant effect on low literacy adults. These adults appear to experience more difficulty in deleting phonemes irrespective of the complexity of the syllable structure.

Moreover, findings from studies that looked at whether phonological processes or lexical processes differentiated Spanish readers with and without reading difficulties indicated that the cause of the reading difficulties appeared to reside in the grapheme-phoneme decomposition procedure than in the lexical processes (Domínguez & Cuetos, 1992; Jiménez & Hernández-Valle, 2000; Rodrigo & Jiménez, 1999). This finding reinforces the hypothesis that the basis of reading problems is a difficulty in phonological processing, indicating that a lack of phonemic awareness is curtailing the acquisition of word recognition skill.

A major question posed by researchers relates to whether a major variable affecting the level of difficulty in learning to read also depends on the transparency/opacity of the writing system (e.g., Wydell & Butterworth, 1999). Specifically, the question relates to whether the effect of the transparency/opacity of the writing system is not only quantitative, but also qualitative. For instance, research indicated that English-speaking children perform reading tasks worse than do children who speak Spanish, French or German. A plausible reason is because the dissociation between sublexical and lexical procedures is greater for Englishspeaking children than for children who speak other languages. Sprenger-Charolles et al. (2006) reviewed cross-linguistic studies and longitudinal studies that examined the stability of dyslexic performance patterns across languages, and over time as reading develops. Group studies, single case studies, and multiple case studies conducted in various languages to evaluate the reliability and prevalence of the dyslexic performance pattern were included in the review. Assessments to determine the lexical and sublexical routes used both high frequency irregular word reading, and pseudoword reading. However, not

However, empirical evidence in Spanish indicates that dyslexic children exhibit the same difficulties in phonemic segmentation exhibited by older English dyslexic children (Jiménez, 1997). For example, Jiménez (1997) analyzed phoneme awareness within the context of a reading-level match design, demonstrating a deficit in the Spanish reading disabled (RD) children in phonemic tasks, but not in intrasyllabic tasks. In another study, Jiménez et al. (2005) examined the effects of linguistic complexity (e.g., complexity in the syllable structure) and task differences without taking into account verbal working memory. The assumption was that if students, identified as dyslexic, performed worse in a phonemic task compared to RL and CA matched children, the hypothesis of a phonemic deficit in explaining dyslexia in a transparent orthography would be confirmed. Results indicated that the complexity of the syllable structure had no particularly marked effect on the dyslexic children. Rather, the isolation task revealed the phonological deficit across all

Jiménez, García and Venegas (2008) examined whether phonological processes are the same or different in low literacy adults and children with or without reading disabilities in a transparent orthography. They selected a sample of 150 subjects organized into four different groups: (1) 53 low literacy adults, (2) 29 reading disabled children, (3) 27 younger normal readers at the same reading level as those with reading disabilities and low literacy adults, and (4) 41 normal readers matched in age with the reading disabled group. Phonological awareness tasks that included different complexities of the syllable structure (e.g., words with CV and CCV structure) were administered. Results indicated that the complexity of the syllable structure did not have a significant effect on low literacy adults. These adults appear to experience more difficulty in deleting phonemes irrespective of the

Moreover, findings from studies that looked at whether phonological processes or lexical processes differentiated Spanish readers with and without reading difficulties indicated that the cause of the reading difficulties appeared to reside in the grapheme-phoneme decomposition procedure than in the lexical processes (Domínguez & Cuetos, 1992; Jiménez & Hernández-Valle, 2000; Rodrigo & Jiménez, 1999). This finding reinforces the hypothesis that the basis of reading problems is a difficulty in phonological processing, indicating that a

A major question posed by researchers relates to whether a major variable affecting the level of difficulty in learning to read also depends on the transparency/opacity of the writing system (e.g., Wydell & Butterworth, 1999). Specifically, the question relates to whether the effect of the transparency/opacity of the writing system is not only quantitative, but also qualitative. For instance, research indicated that English-speaking children perform reading tasks worse than do children who speak Spanish, French or German. A plausible reason is because the dissociation between sublexical and lexical procedures is greater for Englishspeaking children than for children who speak other languages. Sprenger-Charolles et al. (2006) reviewed cross-linguistic studies and longitudinal studies that examined the stability of dyslexic performance patterns across languages, and over time as reading develops. Group studies, single case studies, and multiple case studies conducted in various languages to evaluate the reliability and prevalence of the dyslexic performance pattern were included in the review. Assessments to determine the lexical and sublexical routes used both high frequency irregular word reading, and pseudoword reading. However, not

lack of phonemic awareness is curtailing the acquisition of word recognition skill.

syllable structures.

complexity of the syllable structure.

all studies included a standard measure of lexical processing (i.e., irregular word reading) because it is impossible to find enough irregular words in some of the languages (e.g., Spanish) included in the review. Findings indicated a higher incidence rate of phonological dyslexia in English in comparison to other languages (e.g., Wydell & Butterworth, 1999; Wydell & Kondo 2003) where researchers found a higher incidence of surface dyslexia. Note that surface dyslexia is characterized by impaired orthographic skills and fairly wellpreserved phonological skills (Stanovich, et al., 1997b), while a phonological dyslexia is characterized by impaired phonological skills and fairly well-preserved orthographic skills (Castles & Coltheart, 1993; Manis, Seidenberg, Doi, McBridge-Chang & Petersen, 1996; Stanovich, Siegel & Gottardo, 1997b).

Thus, studies that indicate the extent to which the dual-route hypothesis (i.e., differences between phonological and surface dyslexia (e.g., Manis, et al, 1996; Stanovich, et al, 1997b) is also applicable to languages with a transparent orthography, are still necessary. Moreover, studies designed to demonstrate that the consistency of mappings from graphemes to phonemes in different languages has a marked effect on the development of phonemic awareness and of grapheme-phoneme recoding strategies in dyslexic children are necessary. Two Spanish studies of dyslexic subtypes and computer-assisted practice on visual word recognition are presented here to provide empirical evidence in favor of the deficit model in phonological processing in a transparent orthography. Next we report results of the two studies.

#### **2. Study 1: Identifying dyslexic subtypes in a transparent orthography**

A question posed by reading researchers is whether readers with developmental dyslexia form a homogeneous group with a unique underlying impairment, or whether this group actually consists of distinct subgroups. In English, research indicates the existence of two distinct profiles of developmental dyslexia. In our own review of studies of dyslexic performance patterns, we have found the opposite pattern when we reviewed studies conducted in orthographies less opaque than English (e.g., Swedish: Wolff, 2009). These discrepancies between the Spanish versus the anglophone or francophone studies may be due to (a) linguistic factors, (b) the measures used, and (c) differences in the dyslexics' chronological age. Given that grapheme-phoneme correspondences are more regular in Spanish than in English and in French, Spanish-speaking dyslexics may manage to use the sublexical reading route with less difficulty than English-speaking or French speaking dyslexics. This could explain why fewer phonological dyslexics were found in languages that are less opaque than English. A similar trend was observed when time measures were used in Spanish or in French (Genard et al., 1998) suggesting that the phonological deficit of Spanish-speaking dyslexics manifests itself as slow processing more than in accuracy.

The study presented here was first published by Jiménez and Ramirez (2002) and replicated later by Jiménez, Rodríguez, and Ramírez (2009). It employed the same procedure used by Castles and Coltheart (1993) for identifying dyslexic subtypes based on pseudoword and irregular word reading. Given that Spanish does not have any irregular words, we compared the reaction times (RTs) of students reading high frequency words and pseudowords between the group of dyslexic children and the group of children similar in chronological-age, and reading-level (RL).

The Role of Phonological Processing in Dyslexia in the Spanish Language 33

reading) based on grade 1 norms. Normal readers matched in age achieved a performance

**Measures**. We used three different phonological awareness tests (i.e., odd-word-out task, phoneme segmentation and phoneme reversal). The *Odd-word-out task* was designed to test the awareness of intrasyllabic units and was based on a similar measure by Bowey and Francis (1991). The difference between the Bowey and Francis measure and ours was that we used pictures. In the *Phoneme segmentation test*, children counted the phonemes of words presented orally. Children were aloud to use aids such as rods to count the phonemes they heard in words. In the *Phoneme reversal test* the children counted the phonemes of words by

**Procedure**. We used the same regression-based procedure introduced by Castles and Coltheart (1993) and used the same-aged normal readers' performance to identify subtypes of dyslexics. We used RTs to high frequency words and pseudowords, controlling for the number of letters. That is, the RT for each stimulus (word and pseudoword) was divided by the number of letters. We hypothesized that children who have greater RTs for familiar word reading compared to RTs for pseudoword reading would have difficulties using a lexical procedure to read words. On the other hand, children who would show longer latencies for pseudoword reading as compared to familiar word reading would have more difficulties in using a phonological route. To conduct this experiment, the program UNICEN was designed and used together with a device that detected the sounds within the broad band of the human voice but was not affected by the fairly high percentage of background noise. High-frequency words used in the experiment were selected on the basis of ratings generated from a normative study conducted by Guzmán and Jiménez (2001), who employed a sample of 3,000 words obtained from different texts of children's literature. Word familiarity was measured using these authors' procedure of frequency estimation, which involved the separation of the 3,000 words into different sets. Each set was printed and then different groups of 30 children rated each word on a 5-point scale, ranging from *least frequent* (1) to *most frequent* (5). The estimated frequency was calculated for each word by averaging the rating across all 30 judges. On the basis of these ratings, high-frequency words were selected. Pseudowords were extracted from research by de Vega, Carreiras, Gutiérrez, and Alonso-Quecuty (1990). The order of presentation of words and pseudowords was counterbalanced. Items were presented in random order within each set.

**Results**. We carried out two different analyses: (1) a comparison of dyslexic subgroups to the CA control group, and (2) a comparison of dyslexic subgroups to the RL control group. The first analysis allows us to know how the performance of the dyslexic children differs from normal readers of the same age (Manis, et al., 1996). The soft subtypes were defined by running a regression line with 90% confidence intervals through the Word RTs x Pseudoword RTs plot for the CA and RL control children. This regression line and confidence intervals were then superimposed on the scatterplot of the performance of the dyslexic sample. A surface dyslexic is a child who is an outlier when word RTs are plotted against pseudowords RTs, but is within the normal range when pseudowords RTs are

according to grade 3 norms.

reversing the order of segments in each word.

In total, there were 32 words and 48 pseudowords.

plotted against words RTs. Ph-Dys are defined conversely.

Some difficulties have been encountered in research using traditional research designs. So, for example, when reading-disabled subjects are matched in age with normal readers, differences between the groups on non-reading measures have been presumed to reflect deficits causally related to the reading failure of the reading-disabled group (Backman, Mamem, & Ferguson, 1984). When two groups that have different reading levels are compared, any differences found between them could be interpreted as a product rather than as a cause of such differences (Bryant & Goswami, 1986). However, if the children are at the same reading level, any differences between them cannot be attributed to one group being more successful readers than the other group. However, as has been suggested by Bryant and Goswami (1986) the studies that analyze correlates of reading disability should involve a combination of reading level and chronological age matched groups. In the threegroup design, there are two control groups in addition to the target group, one for reading level and one for chronological age. Thus, the paradigm allows not only comparison of children of different chronological ages with the same reading level as in the two-group approach, but also comparison within chronological age across reading levels. The addition of the third group, i.e., chronological age controls, allows examination of differing performance levels across two chronological age levels in normal children, as well as relative performance within chronological age and reading level-matched groups (Backman et al, 1984). As several authors have pointed out (Backman et al, 1984; Bryant & Goswami, 1986) positive results (a difference between reading disabled children and normal controls) in experiments that use a reading level match allows us to conclude that the measure under consideration is probably causally related to the reading disabilities. As has been suggested by Manis et al. (1996), "the developmental forms result in patterns that are not observed in normal readers at any age or level of reading acquisition – a *deviant* developmental pattern. Another possibility is that a subgroup might lag in a broad spectrum of reading skills and hence resemble younger normal readers – a *developmental delay* pattern" (p. 162).

Therefore, we conducted further exploration of the validity and reliability of the subgroup assignments by examining the performance on phonological awareness tasks. We predicted that if the subgrouping was valid, phonological dyslexics (Ph-Dys) should perform relatively poorly on the phonological awareness tasks compared to younger normal readers, supporting a specific deficit in phonological processing, whereas there should not be differences on the phonological awareness tasks between surface dyslexics (S-Dys) and younger normal readers.

#### **2.1 Method**

**Participants**. In the initial sample, teachers selected children who they believed were normally achieving readers or were reading-disabled. We assessed these children with different subtests of the Standardized Literacy Skills Test T.A.L.E. (Test de Análisis de Lectoescritura; Toro & Cervera, 1980). The study employed a reading-level-match design including three groups: (1) The reading-disabled sample consisted of 89 third-grade children who achieved a performance below the grade 3 norms (i.e., two years) on each of the subtests of TALE individually; (2) A control group of 37 normal readers matched in age with the reading-disabled group; (3) A control group of 39 younger children at the same reading level as the reading-disabled group. Both reading disabled and younger normal readers were matched on each of the subtests of TALE individually (i.e., letter, syllable, and word

Some difficulties have been encountered in research using traditional research designs. So, for example, when reading-disabled subjects are matched in age with normal readers, differences between the groups on non-reading measures have been presumed to reflect deficits causally related to the reading failure of the reading-disabled group (Backman, Mamem, & Ferguson, 1984). When two groups that have different reading levels are compared, any differences found between them could be interpreted as a product rather than as a cause of such differences (Bryant & Goswami, 1986). However, if the children are at the same reading level, any differences between them cannot be attributed to one group being more successful readers than the other group. However, as has been suggested by Bryant and Goswami (1986) the studies that analyze correlates of reading disability should involve a combination of reading level and chronological age matched groups. In the threegroup design, there are two control groups in addition to the target group, one for reading level and one for chronological age. Thus, the paradigm allows not only comparison of children of different chronological ages with the same reading level as in the two-group approach, but also comparison within chronological age across reading levels. The addition of the third group, i.e., chronological age controls, allows examination of differing performance levels across two chronological age levels in normal children, as well as relative performance within chronological age and reading level-matched groups (Backman et al, 1984). As several authors have pointed out (Backman et al, 1984; Bryant & Goswami, 1986) positive results (a difference between reading disabled children and normal controls) in experiments that use a reading level match allows us to conclude that the measure under consideration is probably causally related to the reading disabilities. As has been suggested by Manis et al. (1996), "the developmental forms result in patterns that are not observed in normal readers at any age or level of reading acquisition – a *deviant* developmental pattern. Another possibility is that a subgroup might lag in a broad spectrum of reading skills and

hence resemble younger normal readers – a *developmental delay* pattern" (p. 162).

younger normal readers.

**2.1 Method** 

Therefore, we conducted further exploration of the validity and reliability of the subgroup assignments by examining the performance on phonological awareness tasks. We predicted that if the subgrouping was valid, phonological dyslexics (Ph-Dys) should perform relatively poorly on the phonological awareness tasks compared to younger normal readers, supporting a specific deficit in phonological processing, whereas there should not be differences on the phonological awareness tasks between surface dyslexics (S-Dys) and

**Participants**. In the initial sample, teachers selected children who they believed were normally achieving readers or were reading-disabled. We assessed these children with different subtests of the Standardized Literacy Skills Test T.A.L.E. (Test de Análisis de Lectoescritura; Toro & Cervera, 1980). The study employed a reading-level-match design including three groups: (1) The reading-disabled sample consisted of 89 third-grade children who achieved a performance below the grade 3 norms (i.e., two years) on each of the subtests of TALE individually; (2) A control group of 37 normal readers matched in age with the reading-disabled group; (3) A control group of 39 younger children at the same reading level as the reading-disabled group. Both reading disabled and younger normal readers were matched on each of the subtests of TALE individually (i.e., letter, syllable, and word reading) based on grade 1 norms. Normal readers matched in age achieved a performance according to grade 3 norms.

**Measures**. We used three different phonological awareness tests (i.e., odd-word-out task, phoneme segmentation and phoneme reversal). The *Odd-word-out task* was designed to test the awareness of intrasyllabic units and was based on a similar measure by Bowey and Francis (1991). The difference between the Bowey and Francis measure and ours was that we used pictures. In the *Phoneme segmentation test*, children counted the phonemes of words presented orally. Children were aloud to use aids such as rods to count the phonemes they heard in words. In the *Phoneme reversal test* the children counted the phonemes of words by reversing the order of segments in each word.

**Procedure**. We used the same regression-based procedure introduced by Castles and Coltheart (1993) and used the same-aged normal readers' performance to identify subtypes of dyslexics. We used RTs to high frequency words and pseudowords, controlling for the number of letters. That is, the RT for each stimulus (word and pseudoword) was divided by the number of letters. We hypothesized that children who have greater RTs for familiar word reading compared to RTs for pseudoword reading would have difficulties using a lexical procedure to read words. On the other hand, children who would show longer latencies for pseudoword reading as compared to familiar word reading would have more difficulties in using a phonological route. To conduct this experiment, the program UNICEN was designed and used together with a device that detected the sounds within the broad band of the human voice but was not affected by the fairly high percentage of background noise. High-frequency words used in the experiment were selected on the basis of ratings generated from a normative study conducted by Guzmán and Jiménez (2001), who employed a sample of 3,000 words obtained from different texts of children's literature. Word familiarity was measured using these authors' procedure of frequency estimation, which involved the separation of the 3,000 words into different sets. Each set was printed and then different groups of 30 children rated each word on a 5-point scale, ranging from *least frequent* (1) to *most frequent* (5). The estimated frequency was calculated for each word by averaging the rating across all 30 judges. On the basis of these ratings, high-frequency words were selected. Pseudowords were extracted from research by de Vega, Carreiras, Gutiérrez, and Alonso-Quecuty (1990). The order of presentation of words and pseudowords was counterbalanced. Items were presented in random order within each set. In total, there were 32 words and 48 pseudowords.

**Results**. We carried out two different analyses: (1) a comparison of dyslexic subgroups to the CA control group, and (2) a comparison of dyslexic subgroups to the RL control group. The first analysis allows us to know how the performance of the dyslexic children differs from normal readers of the same age (Manis, et al., 1996). The soft subtypes were defined by running a regression line with 90% confidence intervals through the Word RTs x Pseudoword RTs plot for the CA and RL control children. This regression line and confidence intervals were then superimposed on the scatterplot of the performance of the dyslexic sample. A surface dyslexic is a child who is an outlier when word RTs are plotted against pseudowords RTs, but is within the normal range when pseudowords RTs are plotted against words RTs. Ph-Dys are defined conversely.

The Role of Phonological Processing in Dyslexia in the Spanish Language 35

p < .001) and surface dyslexics (t = 2.19; p < .05). The ANOVA on the phoneme segmentation task revealed significant differences [F (2, 105) = 3.26; p < .05], and the test indicated that the younger normal readers performed significantly better than the phonological dyslexics (t = 2.56; p < .01) and surface dyslexics (t = 3.80; p < .001). The ANOVA on the phoneme reversal revealed similar results [F (2, 105) = 5.95; p < .05] indicating again that younger normal readers scored significantly higher than surface

Studies in English have presented a consistent picture of developmental deviancy and developmental lag that appears to characterize the phonological and surface subtypes (e.g., Manis, et al., 1996; Stanovich et al., 1997b). Phonological dyslexia reflected true developmental deviancy. In contrast, surface dyslexia resembled a form of developmental delay. In the Spanish studies (Jiménez, et al., 2002; Jiménez, et al., 2009) surface and phonological subtypes both represent deviations from normal development. However, the results of the phonological awareness tasks did not validate the division of the dyslexic sample into these two subgroups. Both dyslexic subtypes exhibited significant discrepancies between pseudoword and familiar word reading but they shared the same phonological problems, because both performed more poorly than the younger children in analyzing the

In another study, Jiménez et al. (2009) examined the prevalence, cognitive profile, and home literacy experiences of dyslexic children with different subtypes in Spain. Just like in the other study, we examined the response of three groups (a) a chronological-age-matched group, (b) a reading-level control group, and (c) a dyslexic group. Using regression-based procedures, the author identified 8 phonological and 16 surface dyslexics from a sample of 35 dyslexic 4th-grade children by comparing them to chronological-age-matched controls on RTs for high frequency word and pseudoword reading. However, when the dyslexic subtypes were defined by reference to reading-level controls, 12 phonological dyslexics were defined but only 5 surface dyslexics were identified. Both dyslexic subtypes showed a deficit in phonological awareness, but children with surface dyslexia also showed a deficit in orthographical processing assessed by a homophone comprehension task. This deficit was associated with poor home literacy experiences because the group of parents with children matched in reading age, in comparison to parents with children with surface

Sprenger-Charolles, et al. (2000) found that the phonological impairment of the two dyslexic groups was quite severe, since it emerged even relative to younger average readers. Therefore, they suggested that these results are more in line with the hypothesis that a phonological deficit is at the core of developmental dyslexia than with Castles and Coltheart's idea that a "clear double dissociation exists between surface and phonological

Recently, Sprenger-Charrolles, Siegel, Jiménez, and Ziegler (2011) carried out a review of studies conducted in languages varying in the transparency of their orthography. They also concluded that the regression-based method appears to result in less reliable subtypes

dyslexics (t = 3, 84; p < .001) and phonological dyslexics (t = 3.72; p < .001).

**2.1.1 Discussion** 

phonemic structure of spoken words.

dyslexia, reported more literacy home experiences.

reading patterns" (1993, p. 174).

within and between languages.

If we compare our results with the English and French studies, the percentage of dyslexic subtypes were quite different. Table 1 shows the proportion of Ph-Dys and S-Dys identified in our study and the proportion in other studies. Castles and Coltheart (1993) found 55% Ph-Dys, Manis, et al. (1996) found 33.3% Ph-Dys, and Stanovich, et al. (1997b) found 25% Ph-Dys in their samples. In our study, we found 18% Ph-Dys and 53% of S-Dys, a greater proportion of S-Dys in comparison to Castles and Coltheart (30%), Manis, et al. (29%) and Stanovich, et al. (22%). Similarly, Genard, et al. (1998) found 56% of S-Dys, and only 4% of Ph-Dys. In general, controlling for CA, there were more Ph-Dys than S-Dys. Similarly, compared to RL controls, there were more Ph-Dys readers than S-Dys; however, the S-Dys profile almost disappeared.

On the other hand, in the Chinese orthography, Ho (2001) found that the incidence of S-Dys and Ph\_Dys differs. In general more Chinese dyslexic children have a surface dyslexia (26%) than Ph-Dys (13%), ascertaining our assumption that phonological dyslexia appears to be less common in Chinese than in English.


\*(PD:phonological dyslexics, SD:surface dyslexics, DD: double deficits ND: non-deficit)

Table 1. Classification of dyslexics based on regression method on CA control group

The second analysis focused on whether the performance of dyslexics resembled the performance of younger children learning to read at a normal rate (Manis, et al., 1996). RTs of the dyslexics were plotted so as to identify phonological dyslexics (children with high pseudoword RTs relative to word RTs). The Pseudoword RTs were plotted against the Word RTs. The regression line and confidence intervals are based on the data from the 39 RL controls. Overall, nineteen of the 48 surface dyslexics identified in the regression analysis for the CA group fell below the confidence limit for the RL control group. In contrast, the same 20 phonological dyslexics were identical to those identified from the CA regression lines.

With regard to the validity of subtypes, three separate analyses of variance (ANOVAs) for one factor (younger normal readers vs. phonological dyslexics vs. surface dyslexics) were conducted using the number of correct responses on each of the three phonological awareness tests as dependent variables. Bonferroni's correction was used to determine the acceptable alpha level for rejecting the null hypothesis.The ANOVA on the odd-word-out task was significant [F (2, 104) = 9.48; p < .001]. A multiple comparison test indicated that younger normal readers scored significantly higher than the phonological dyslexics (t = 4.50; p < .001) and surface dyslexics (t = 2.19; p < .05). The ANOVA on the phoneme segmentation task revealed significant differences [F (2, 105) = 3.26; p < .05], and the test indicated that the younger normal readers performed significantly better than the phonological dyslexics (t = 2.56; p < .01) and surface dyslexics (t = 3.80; p < .001). The ANOVA on the phoneme reversal revealed similar results [F (2, 105) = 5.95; p < .05] indicating again that younger normal readers scored significantly higher than surface dyslexics (t = 3, 84; p < .001) and phonological dyslexics (t = 3.72; p < .001).

#### **2.1.1 Discussion**

34 Dyslexia – A Comprehensive and International Approach

If we compare our results with the English and French studies, the percentage of dyslexic subtypes were quite different. Table 1 shows the proportion of Ph-Dys and S-Dys identified in our study and the proportion in other studies. Castles and Coltheart (1993) found 55% Ph-Dys, Manis, et al. (1996) found 33.3% Ph-Dys, and Stanovich, et al. (1997b) found 25% Ph-Dys in their samples. In our study, we found 18% Ph-Dys and 53% of S-Dys, a greater proportion of S-Dys in comparison to Castles and Coltheart (30%), Manis, et al. (29%) and Stanovich, et al. (22%). Similarly, Genard, et al. (1998) found 56% of S-Dys, and only 4% of Ph-Dys. In general, controlling for CA, there were more Ph-Dys than S-Dys. Similarly, compared to RL controls, there were more Ph-Dys readers than S-Dys; however, the S-Dys

On the other hand, in the Chinese orthography, Ho (2001) found that the incidence of S-Dys and Ph\_Dys differs. In general more Chinese dyslexic children have a surface dyslexia (26%) than Ph-Dys (13%), ascertaining our assumption that phonological dyslexia appears to be

*Studies* PD\* SD.\* D.D\*. ND.\* Variables

of letters

Castles & Coltheart. (1993) 55% 30% 6% 9% Accuracy Manis et al. (1996) 33% 29% 10% 28% Accuracy Stanovich et al. (1997) 25% 22% 28% 25% Accuracy Genard et al. (1998) 4% 56% 3% 37% Accuracy Sprenger et al. (2000) 52% 32% 3% 13% Reaction Times Jiménez & Ramírez. (2002) 18% 53% 3% 26% Reaction Times/number

\*(PD:phonological dyslexics, SD:surface dyslexics, DD: double deficits ND: non-deficit)

Table 1. Classification of dyslexics based on regression method on CA control group

The second analysis focused on whether the performance of dyslexics resembled the performance of younger children learning to read at a normal rate (Manis, et al., 1996). RTs of the dyslexics were plotted so as to identify phonological dyslexics (children with high pseudoword RTs relative to word RTs). The Pseudoword RTs were plotted against the Word RTs. The regression line and confidence intervals are based on the data from the 39 RL controls. Overall, nineteen of the 48 surface dyslexics identified in the regression analysis for the CA group fell below the confidence limit for the RL control group. In contrast, the same 20 phonological dyslexics were identical to those identified from the CA regression lines.

With regard to the validity of subtypes, three separate analyses of variance (ANOVAs) for one factor (younger normal readers vs. phonological dyslexics vs. surface dyslexics) were conducted using the number of correct responses on each of the three phonological awareness tests as dependent variables. Bonferroni's correction was used to determine the acceptable alpha level for rejecting the null hypothesis.The ANOVA on the odd-word-out task was significant [F (2, 104) = 9.48; p < .001]. A multiple comparison test indicated that younger normal readers scored significantly higher than the phonological dyslexics (t = 4.50;

profile almost disappeared.

less common in Chinese than in English.

Studies in English have presented a consistent picture of developmental deviancy and developmental lag that appears to characterize the phonological and surface subtypes (e.g., Manis, et al., 1996; Stanovich et al., 1997b). Phonological dyslexia reflected true developmental deviancy. In contrast, surface dyslexia resembled a form of developmental delay. In the Spanish studies (Jiménez, et al., 2002; Jiménez, et al., 2009) surface and phonological subtypes both represent deviations from normal development. However, the results of the phonological awareness tasks did not validate the division of the dyslexic sample into these two subgroups. Both dyslexic subtypes exhibited significant discrepancies between pseudoword and familiar word reading but they shared the same phonological problems, because both performed more poorly than the younger children in analyzing the phonemic structure of spoken words.

In another study, Jiménez et al. (2009) examined the prevalence, cognitive profile, and home literacy experiences of dyslexic children with different subtypes in Spain. Just like in the other study, we examined the response of three groups (a) a chronological-age-matched group, (b) a reading-level control group, and (c) a dyslexic group. Using regression-based procedures, the author identified 8 phonological and 16 surface dyslexics from a sample of 35 dyslexic 4th-grade children by comparing them to chronological-age-matched controls on RTs for high frequency word and pseudoword reading. However, when the dyslexic subtypes were defined by reference to reading-level controls, 12 phonological dyslexics were defined but only 5 surface dyslexics were identified. Both dyslexic subtypes showed a deficit in phonological awareness, but children with surface dyslexia also showed a deficit in orthographical processing assessed by a homophone comprehension task. This deficit was associated with poor home literacy experiences because the group of parents with children matched in reading age, in comparison to parents with children with surface dyslexia, reported more literacy home experiences.

Sprenger-Charolles, et al. (2000) found that the phonological impairment of the two dyslexic groups was quite severe, since it emerged even relative to younger average readers. Therefore, they suggested that these results are more in line with the hypothesis that a phonological deficit is at the core of developmental dyslexia than with Castles and Coltheart's idea that a "clear double dissociation exists between surface and phonological reading patterns" (1993, p. 174).

Recently, Sprenger-Charrolles, Siegel, Jiménez, and Ziegler (2011) carried out a review of studies conducted in languages varying in the transparency of their orthography. They also concluded that the regression-based method appears to result in less reliable subtypes within and between languages.

The Role of Phonological Processing in Dyslexia in the Spanish Language 37

**Procedure**. All the tests were administered by psychologists in a random order, to avoid any effect of the presentation of the material. Once the computer equipment was installed in the schools, the children were randomly assigned to the experimental and control conditions. We first carried out a general trial session, in which the children were trained in all of the TEDIS (Tratamiento Experimental de la Dislexia = Experimental Treatment of Dyslexia) program requirements. Once the treatment sessions started, the examiners were present just to guarantee the optimal technical functioning of the program. The children came to the computer room for 40 minutes per day during language arts time, to keep equivalent the reading instruction time for experimental subjects and for matched untrained controls in the same class. A core technical component in the TEDIS remedial program is the "talking" computer, which gives support and feedback through digitized speech. The TEDIS program provided feedback segmented into sub-word units (i.e., phonemes, syllables, onset-rime segments) which were sequentially highlighted and spoken by the computer. All children received orthographic and speech feedback that was presented in syllable or sub-syllable units. In each session the words were presented on the center of the screen. These words

were pronounced by a professional speech trainer and recorded on tape in a studio.

First of all, the computer segmented the word into sub-word units whereas a woman's voice was pronouncing them. Children were asked to attempt to pronounce each segment before clicking the mouse again to hear the speech support. Then, the subject had two options to choose, clicking with the mouse: (1) to repeat the same task with the same sub-word units, or (2) to pronounce the whole word. When the subject was able to pronounce the word correctly, the subjects had to press the keyboard to obtain the next word. When speech feedback was requested, the sub-word sound was immediately delivered through the headphones. When the subject asked for speech feedback, only the relevant word was presented on the screen. If the subject did not read the word, then he or she was asked to repeat the task again by the examiner. Only when the child had three failures with the same word, would the examiner press the keyboard and the presentation of a new word was shown. Every eight stimuli the program asked a multiple-choice comprehension question. Each child had to indicate with the mouse which of the pictures showed on the screen, was related to the target word. The children were allowed to use the speech-feedback option. Van Daal and Reitsma (1993) examined whether it is best to give feedback on all words or to allow the disabled readers to choose. It was found that reading disabled children in the intervention who were matched age did not learn less when the computer unsolicitedly delivered the spoken form of all words than when they were allowed to choose. In addition, the results of a series of small quasi-experimental studies indicated positive treatment effects, in which the dyslexics who received computer training with speech feedback, improved their performance in reading and spelling, compared to students who only had access to conventional special education (Lundberg, 1995). Fifteen sessions were the total of the TEDIS program. In each session, the reading materials consisted of 40 nouns and were divided as a function of the different linguistic parameters into (a) word length (short vs. long), (b) word frequency (familiar vs. nonfamiliar) and word linguistic structure (consonant-vowel (CV) vs. consonant-consonant-vowel (CCV)). During the computer-based word reading, we collected information about the number of accurately read words, number of speech feedback, and reading time. The reading time of each stimulus was registered given that the word appeared on the screen until the child pronounced it successfully.

In sum, we concluded that in a transparent orthography developmental dyslexics do form a homogeneous population with a unique underlying phonological impairment.

#### **3. Study 2: Computer speech-based remediation for reading disabilities in Spanish dyslexics**

An increasing number of researchers have used computers in experiments on the remediation of reading disabilities (e.g., Jones, Torgesen & Sexton, 1987; Olofsson, 1992; Olson & Wise, 1992; Torgesen & Barker, 1995; Van Daal & Reitsma, 1993; Van der Leij, 1994). It has been demonstrated that reading on the computer with speech feedback significantly improved disabled reader's phonological decoding and word recognition. With regard to the best instructional intervention for remediating reading disabilities, Swanson (1999) tested in his study whether certain models of instruction (e.g., direct instruction, strategy instruction, etc.) have broad effects across word-recognition and comprehension measures. He found that effect sizes were higher for word recognition when studies included direct instruction. Moreover**,** studies of computer-aided remediation for reading-disabled children demonstrated that word recognition skill improved when different forms of orthographic units were manipulated (Olson & Wise, 1992). The study presented here was first published by Jiménez et al. (2003). We had predicted that reading on the computer with speech feedback can provide a helpful remedial tool for children with RD in a transparent orthography.

#### **3.1 Method**

**Participants**. A sample of 73 Spanish children was obtained ranging between 7 years 1 month and 10 years 6 months of age. Using the standard-score discrepancy method, the children with reading difficulties were classified into two groups based on the difference, or lack thereof, between their scores on the IQ test and their standard scores on the Pseudoword subtest of the PROLEC (Cuetos, Rodríguez, & Ruano, 1996). Children were classified as having dyslexia if their pseudoword standard score was more than 15 points lower than their IQ score (N=14), and if their score on an IQ test was >80. Children were considered poor readers if their pseudoword score was less than 15 points lower than their IQ score (N=31), and if their score on an IQ test was >80. The overall sample was classified into three different groups: (1) an experimental group of 14 dyslexics (8 male, 6 female) who received computer-based reading practice; (2) an experimental group of 31 garden variety poor readers (GV) (17 male, 14 female) who also received the same type of practice, and (3) a control group of 28 reading-disabled children (20 male, 8 female) who did not receive computer-assisted practice.

**Measures**. We used the Standardized Reading Skills Test PROLEC. This test includes different reading subtests. We only administered the following subtests: (1) word reading, (2) pseudoword reading, and (3) text comprehension. Word and Pseudoword reading subtests required correct identification of ordinary words and pseudowords. Both subtests are based on the accuracy of the responses. The comprehension subtest includes a short story and questions which were given to the children after reading. We used the same phonological awareness tests as in Study 1 (i.e., odd-word-out task, phoneme segmentation and phoneme reversal).

In sum, we concluded that in a transparent orthography developmental dyslexics do form a

An increasing number of researchers have used computers in experiments on the remediation of reading disabilities (e.g., Jones, Torgesen & Sexton, 1987; Olofsson, 1992; Olson & Wise, 1992; Torgesen & Barker, 1995; Van Daal & Reitsma, 1993; Van der Leij, 1994). It has been demonstrated that reading on the computer with speech feedback significantly improved disabled reader's phonological decoding and word recognition. With regard to the best instructional intervention for remediating reading disabilities, Swanson (1999) tested in his study whether certain models of instruction (e.g., direct instruction, strategy instruction, etc.) have broad effects across word-recognition and comprehension measures. He found that effect sizes were higher for word recognition when studies included direct instruction. Moreover**,** studies of computer-aided remediation for reading-disabled children demonstrated that word recognition skill improved when different forms of orthographic units were manipulated (Olson & Wise, 1992). The study presented here was first published by Jiménez et al. (2003). We had predicted that reading on the computer with speech feedback can provide a helpful

**Participants**. A sample of 73 Spanish children was obtained ranging between 7 years 1 month and 10 years 6 months of age. Using the standard-score discrepancy method, the children with reading difficulties were classified into two groups based on the difference, or lack thereof, between their scores on the IQ test and their standard scores on the Pseudoword subtest of the PROLEC (Cuetos, Rodríguez, & Ruano, 1996). Children were classified as having dyslexia if their pseudoword standard score was more than 15 points lower than their IQ score (N=14), and if their score on an IQ test was >80. Children were considered poor readers if their pseudoword score was less than 15 points lower than their IQ score (N=31), and if their score on an IQ test was >80. The overall sample was classified into three different groups: (1) an experimental group of 14 dyslexics (8 male, 6 female) who received computer-based reading practice; (2) an experimental group of 31 garden variety poor readers (GV) (17 male, 14 female) who also received the same type of practice, and (3) a control group of 28 reading-disabled children (20 male, 8 female) who did not receive

**Measures**. We used the Standardized Reading Skills Test PROLEC. This test includes different reading subtests. We only administered the following subtests: (1) word reading, (2) pseudoword reading, and (3) text comprehension. Word and Pseudoword reading subtests required correct identification of ordinary words and pseudowords. Both subtests are based on the accuracy of the responses. The comprehension subtest includes a short story and questions which were given to the children after reading. We used the same phonological awareness tests as in Study 1 (i.e., odd-word-out task, phoneme segmentation

**3. Study 2: Computer speech-based remediation for reading disabilities in** 

homogeneous population with a unique underlying phonological impairment.

remedial tool for children with RD in a transparent orthography.

**Spanish dyslexics** 

**3.1 Method** 

computer-assisted practice.

and phoneme reversal).

**Procedure**. All the tests were administered by psychologists in a random order, to avoid any effect of the presentation of the material. Once the computer equipment was installed in the schools, the children were randomly assigned to the experimental and control conditions. We first carried out a general trial session, in which the children were trained in all of the TEDIS (Tratamiento Experimental de la Dislexia = Experimental Treatment of Dyslexia) program requirements. Once the treatment sessions started, the examiners were present just to guarantee the optimal technical functioning of the program. The children came to the computer room for 40 minutes per day during language arts time, to keep equivalent the reading instruction time for experimental subjects and for matched untrained controls in the same class. A core technical component in the TEDIS remedial program is the "talking" computer, which gives support and feedback through digitized speech. The TEDIS program provided feedback segmented into sub-word units (i.e., phonemes, syllables, onset-rime segments) which were sequentially highlighted and spoken by the computer. All children received orthographic and speech feedback that was presented in syllable or sub-syllable units. In each session the words were presented on the center of the screen. These words were pronounced by a professional speech trainer and recorded on tape in a studio.

First of all, the computer segmented the word into sub-word units whereas a woman's voice was pronouncing them. Children were asked to attempt to pronounce each segment before clicking the mouse again to hear the speech support. Then, the subject had two options to choose, clicking with the mouse: (1) to repeat the same task with the same sub-word units, or (2) to pronounce the whole word. When the subject was able to pronounce the word correctly, the subjects had to press the keyboard to obtain the next word. When speech feedback was requested, the sub-word sound was immediately delivered through the headphones. When the subject asked for speech feedback, only the relevant word was presented on the screen. If the subject did not read the word, then he or she was asked to repeat the task again by the examiner. Only when the child had three failures with the same word, would the examiner press the keyboard and the presentation of a new word was shown. Every eight stimuli the program asked a multiple-choice comprehension question. Each child had to indicate with the mouse which of the pictures showed on the screen, was related to the target word. The children were allowed to use the speech-feedback option. Van Daal and Reitsma (1993) examined whether it is best to give feedback on all words or to allow the disabled readers to choose. It was found that reading disabled children in the intervention who were matched age did not learn less when the computer unsolicitedly delivered the spoken form of all words than when they were allowed to choose. In addition, the results of a series of small quasi-experimental studies indicated positive treatment effects, in which the dyslexics who received computer training with speech feedback, improved their performance in reading and spelling, compared to students who only had access to conventional special education (Lundberg, 1995). Fifteen sessions were the total of the TEDIS program. In each session, the reading materials consisted of 40 nouns and were divided as a function of the different linguistic parameters into (a) word length (short vs. long), (b) word frequency (familiar vs. nonfamiliar) and word linguistic structure (consonant-vowel (CV) vs. consonant-consonant-vowel (CCV)). During the computer-based word reading, we collected information about the number of accurately read words, number of speech feedback, and reading time. The reading time of each stimulus was registered given that the word appeared on the screen until the child pronounced it successfully.

The Role of Phonological Processing in Dyslexia in the Spanish Language 39

ES = .35]. Subsequent test of simple main effect revealed that reading time was greater for dyslexics than for GV poor readers in nonfamiliar words during computer-based reading [F (13, 767) = 8.36, p < .001, MSE = 742.62]. A (2x2x15) Group (dyslexics, GV poor readers) x Word Length (short vs. long) x Word Set (1 vs. 15) mixed analysis of variance (ANOVA) was performed on the number of accurately read words, number of speech feedback, and reading time. There was a significant Group x Length x Word Set interaction [F (11, 561) = 3.21; p < .001, MSE = .68, ES = .28] when we analyzed the number of accurately read words. Subsequent test of simple main effect revealed that the dyslexic group was more affected by long words during computer-based reading [F (11, 561) = 5.50, p < .001, MSE = 1.17] (see

Fig. 2. Interaction between group and word length and word set on the number of accurately read words. DG = long words for dyslexia group; GVC Long = long words for garden-variety poor readers' group; DG Short = short words for dyslexia group; GVG Short

As suggested by Swanson (1999, p. 504) "there have been conceptual shifts regarding what underlies reading problems in children with LD, which in turn raised questions about the best instructional intervention for remediating such problems". Nowadays, there is consensus that many cases of reading disabilities are caused by difficulties in the visual word recognition. The majority of recent research suggests that word identification problems are basically phonological route problems (e.g., Olson, Kliegl, Davidson & Foltz, 1985; Perfetti, 1985; Rack, Snowling & Olson, 1992; Van Den Bos & Spelberg, 1994; Wagner & Torgesen, 1987). As reviewed above, many studies carried out in opaque orthographies using the Reading Level (RL) match design have found empirical evidence in favor of the deficit model in phonological processing, because dyslexics have more difficulty in reading nonwords than normal readers matched in age or in RL (Olson, Wise, Conners, Rack & Fulker, 1989; Stanovich & Siegel, 1994). Moreover, some empirical evidence exists that in languages with a transparent orthography, in which the reading disabled show severe difficulties in the use of the phonological route as they do in the English language (e.g., Jiménez, 1997; Jiménez & Hernández-Valle, 2000; Jiménez & Ramírez, 2002; Jiménez, et al.,

**Word Set** 

DG Long GVG Long DG Short GVG Short

= short words for garden-variety poor readers' group.

Figure 2).

**Number of Accurately** 

**Read Words**

**3.1.1 Discussion** 

17

18

19

20

#### **Results**

Pretest-posttest measures

A (3x2) Group (dyslexics, GV poor readers, control) x Moment (pretest, posttest) mixed analysis of variance (ANOVA) was performed on the word recognition and phonological awareness tasks. This analysis yielded a main effect of Time [F (1, 67) = 33.47; p<.001, MSE = 185.50, ES = .33]. In addition there was a significant interaction of Group x Moment [F (2, 67) = 4.23; p < .019, MSE = 23.43, ES = .11]. Tests of simple main effect confirmed that there was an improvement on word recognition in dyslexics [F (1, 67) = 23.2; p < .001, MSE = 128.57], and in GV poor readers [F (1, 67) = 10.48; p < .05, MSE = 58.06]. Dyslexics' baseline level was lower than the other groups; however, they reached the same level of performance in post test. Finally, there were no differences between pretest and posttest scores in the control group [F (1, 67) = 2.63; p = .10, MSE = 14.58] (See Figure 1).

Note: CG = Control Group; DG = Dyslexic Group; GVG= GV Poor Readers Group.

Fig. 1. Interaction between Group and Moment on Word Reading

With regard to phonological awareness measures, both the main effects of Group, [F (6,128) = .82, p <. 04, MSE = 146.56, ES = .09], and of Time, [F (3, 64) = .03, p < .001, MSE = 125.47, ES = .96] were significant. Also, a Group x Time interaction was significant [F (6, 128) = 18.39, p < .04, MSE = 4.0, ES = .09]. Subsequent tests of simple main effects confirmed that there were differences in the posttest between GV poor readers, the control group [F (3, 64) = .85, p < .01, MSE = 150.81], and GV poor readers and dyslexics [F (3, 64) = .87, p < .03, MSE = 125.43]. However, there were no differences between dyslexics and the control group at posttest [F (3, 64) =.91, p = .14, MSE = 109.32]. Again, dyslexic's baseline level was lower than the other groups; however, they reached the same level of performance in post test.

#### **Training sessions measures**

A (2x2x15) Group (dyslexics, GV poor readers) x Word Frequency (familiar vs. nonfamiliar) x Word Set (1 vs. 15) mixed analysis of variance (ANOVA) was performed on the number of accurately read words, number of speech feedback, and reading time. A Group x Word Frequency x Word Set interaction was significant [F (13, 767) = 2.11; p < .012, MSE = 36.72, ES = .35]. Subsequent test of simple main effect revealed that reading time was greater for dyslexics than for GV poor readers in nonfamiliar words during computer-based reading [F (13, 767) = 8.36, p < .001, MSE = 742.62]. A (2x2x15) Group (dyslexics, GV poor readers) x Word Length (short vs. long) x Word Set (1 vs. 15) mixed analysis of variance (ANOVA) was performed on the number of accurately read words, number of speech feedback, and reading time. There was a significant Group x Length x Word Set interaction [F (11, 561) = 3.21; p < .001, MSE = .68, ES = .28] when we analyzed the number of accurately read words. Subsequent test of simple main effect revealed that the dyslexic group was more affected by long words during computer-based reading [F (11, 561) = 5.50, p < .001, MSE = 1.17] (see Figure 2).

Fig. 2. Interaction between group and word length and word set on the number of accurately read words. DG = long words for dyslexia group; GVC Long = long words for garden-variety poor readers' group; DG Short = short words for dyslexia group; GVG Short = short words for garden-variety poor readers' group.

#### **3.1.1 Discussion**

38 Dyslexia – A Comprehensive and International Approach

A (3x2) Group (dyslexics, GV poor readers, control) x Moment (pretest, posttest) mixed analysis of variance (ANOVA) was performed on the word recognition and phonological awareness tasks. This analysis yielded a main effect of Time [F (1, 67) = 33.47; p<.001, MSE = 185.50, ES = .33]. In addition there was a significant interaction of Group x Moment [F (2, 67) = 4.23; p < .019, MSE = 23.43, ES = .11]. Tests of simple main effect confirmed that there was an improvement on word recognition in dyslexics [F (1, 67) = 23.2; p < .001, MSE = 128.57], and in GV poor readers [F (1, 67) = 10.48; p < .05, MSE = 58.06]. Dyslexics' baseline level was lower than the other groups; however, they reached the same level of performance in post test. Finally, there were no differences between pretest and posttest scores in the control

group [F (1, 67) = 2.63; p = .10, MSE = 14.58] (See Figure 1).

Note: CG = Control Group; DG = Dyslexic Group; GVG= GV Poor Readers Group.

With regard to phonological awareness measures, both the main effects of Group, [F (6,128) = .82, p <. 04, MSE = 146.56, ES = .09], and of Time, [F (3, 64) = .03, p < .001, MSE = 125.47, ES = .96] were significant. Also, a Group x Time interaction was significant [F (6, 128) = 18.39, p < .04, MSE = 4.0, ES = .09]. Subsequent tests of simple main effects confirmed that there were differences in the posttest between GV poor readers, the control group [F (3, 64) = .85, p < .01, MSE = 150.81], and GV poor readers and dyslexics [F (3, 64) = .87, p < .03, MSE = 125.43]. However, there were no differences between dyslexics and the control group at posttest [F (3, 64) =.91, p = .14, MSE = 109.32]. Again, dyslexic's baseline level was lower than the other groups; however, they reached the same level of performance in post test.

Pretest Posttest

CG DG GVG

A (2x2x15) Group (dyslexics, GV poor readers) x Word Frequency (familiar vs. nonfamiliar) x Word Set (1 vs. 15) mixed analysis of variance (ANOVA) was performed on the number of accurately read words, number of speech feedback, and reading time. A Group x Word Frequency x Word Set interaction was significant [F (13, 767) = 2.11; p < .012, MSE = 36.72,

Fig. 1. Interaction between Group and Moment on Word Reading

**Results** 

Pretest-posttest measures

**Training sessions measures** 

10

15

20

**Word Reading**

25

30

As suggested by Swanson (1999, p. 504) "there have been conceptual shifts regarding what underlies reading problems in children with LD, which in turn raised questions about the best instructional intervention for remediating such problems". Nowadays, there is consensus that many cases of reading disabilities are caused by difficulties in the visual word recognition. The majority of recent research suggests that word identification problems are basically phonological route problems (e.g., Olson, Kliegl, Davidson & Foltz, 1985; Perfetti, 1985; Rack, Snowling & Olson, 1992; Van Den Bos & Spelberg, 1994; Wagner & Torgesen, 1987). As reviewed above, many studies carried out in opaque orthographies using the Reading Level (RL) match design have found empirical evidence in favor of the deficit model in phonological processing, because dyslexics have more difficulty in reading nonwords than normal readers matched in age or in RL (Olson, Wise, Conners, Rack & Fulker, 1989; Stanovich & Siegel, 1994). Moreover, some empirical evidence exists that in languages with a transparent orthography, in which the reading disabled show severe difficulties in the use of the phonological route as they do in the English language (e.g., Jiménez, 1997; Jiménez & Hernández-Valle, 2000; Jiménez & Ramírez, 2002; Jiménez, et al.,

The Role of Phonological Processing in Dyslexia in the Spanish Language 41

However, the spelling-to-sound unit used in training may be a critical factor in determining the effectiveness of remedial instruction for RD. Consequently, various remedial studies carried out in English have tried to determine which is the size of the spelling-to-sound unit more optimal for computer speech-based training of RD (e.g., Lovett, Barron, Forbes, Cuksts, & Steinbach, 1994; Olson & Wise, 1992). For Spanish, the Syllable and Onset-Rime condition did not contribute to improve phonological decoding. This finding is not surprising because this type of units does not seem to be as relevant in a language where a direct correspondence between graphemes and phonemes does exist, and where the syllable boundaries are well defined. Therefore, Jiménez et al (2003) suggested that in a transparent orthography such as Spanish, remedial education may be more successful if it concentrates on the phoneme level more than on onset-rime units, in contrast to what has been suggested by Treiman (1992) in the English language. The improvements in the Phoneme group support the idea that the phonemic level plays an important role in dyslexia in a transparent orthography as Spanish. By forcing attention to individual letters within the word and with the speech feedback at the same time during the training, could provide the basis to improve phonemic segmentation skills, and promoting the grapheme-phoneme correspondences, an ability that is not achieved by the severe RD children. In relation to the Whole Word condition, interestingly, this unit also benefited word recognition ability. A possible explanation for this finding has to do with the fact that the dual route model of reading is functional in Spanish despite its orthographic transparency by which, in principle, all the words could be read by the phonological route. Some empirical data support the functionality of both routes in Spanish children (Defior, Justicia & Martos, 1996; Valle-Arroyo, 1989), suggesting no differences between the processes involved in the reading of Spanish and those implicated in opaque orthographies, such as English. In this sense, it is important to note that children who participated in this study were between 7-10 years old, an age in which we would expect the use of the orthographic routine of reading. The reason for the gains after treatment within this experimental condition may be explained by the fact that children could place their attention on the whole word present on the computer screen with the phonological speech feedback. This connection between the word and its individual sounds may have enhanced the connections between their

Wydell and Butterworth (1999) suggested that the effect of a phonological deficit on reading depends on the transparency of the orthography. Probably the most likely source of these difficulties is a deficit in representing phonological information at earlier developing levels of phonology: the syllable, onset, and rime. Goswami (2002) suggested that syllabic representation is basic to many languages, and that children's ability to recognize syllables and rhymes precedes learning a particular spelling system. This developmental view can readily explain cross-language differences in reading acquisition, and it can also explain cross-language differences in the manifestation of developmental dyslexia (see also Wydell & Butterworth, 1999; Wydell & Kondo, 2003 for a similar conclusion). Some of the processes underpinning language acquisition are disrupted in developmental dyslexia leading to deficits in the development of a phonological representation of words before literacy is acquired. According to this theoretical analysis, dyslexic children in all languages appear to have a phonological deficit at the syllable and rhyme levels prior to acquiring literacy. This

orthographic and phonological forms.

**4. Concluding discussion** 

2009), suggesting that a phonemic deficit is curtailing the development of phonological decoding. In addition, the degree of phonological reading deficit is not related to the degree of discrepancy between reading and IQ (for a review see, Stanovich & Siegel, 1994).

The results of this study indicated that computer-assisted practice proved to be as beneficial to the GV poor reader group as for the dyslexic group. We found that reading-disabled children with and without IQ-achievement discrepancy improved their performance on word reading, in comparison to the control group. Nevertheless, dyslexics had more difficulties than GV poor readers during computer-based word reading under conditions that required extensive phonological computation because they were more affected by low frequency words and long words. For another study, Jiménez et al. (2007) assessed the effects of four reading-training procedures for children with reading disabilities (RD) in Spain, with the aim of examining the effects of different spelling-to-sound units in computer speech-based reading. A sample of 82 Spanish children ranging between 7 years 1 month and 10 years 6 months, and whose pseudoword reading performance was below the 25th percentile and IQ >90 were selected. The subjects were randomly assigned to five groups: (1) the Whole-Word training group (WW) (n=16), (2) the Syllable training group (S) (n=16), (3) the Onset-Rime1 training group (OR) (n=17), (4) the Phoneme training group (P) (n =15), and (5) the untrained control group (n= 18). Children were pre- and post-tested in word recognition, reading comprehension, phonological awareness, and visual and phonological tasks. Results indicated that experimental groups who participated in the phoneme and whole-word condition improved their word recognition compared to the control group. In addition, dyslexics who participated in the phoneme, syllable and onset-rime conditions applied for more number of calls during computer-based word reading under conditions that required extensive phonological computation (low frequency words and long words). However, reading time was greater for long words in the phoneme group during computerbased reading. The authors concluded that reading on the computer with speech feedback can provide a helpful remedial tool for children with RD in a transparent orthography.

Regarding the best instructional intervention for remediating reading disabilities, Swanson (1999) tested in his study whether certain models of instruction (e.g., direct instruction, strategy instruction, etc.) have broad effects across word-recognition and comprehension measures. He found that effect sizes were higher for word recognition when studies included direct instruction. Additionally, an increasing number of researchers have used computers in experiments on the remediation of reading disabilities (e.g., Jones, Torgesen & Sexton, 1987; Olofsson, 1992; Olson & Wise, 1992; Torgesen & Barker, 1995; Van Daal & Reitsma, 1993; Van der Leij, 1994). It has been demonstrated that reading on the computer with speech feedback significantly improved disabled reader's phonological decoding and word recognition. Moreover**,** studies of computer-aided remediation for reading disabled children demonstrated that word recognition skill improved when different forms of orthographic units were manipulated (Olson & Wise, 1992).

In the teaching of reading, children can be trained on the print-to-sound translation by using linguistic units of different sizes: a word can be taught as a whole unit, in individual lettersound units, or in sublexical units of intermediate size (syllable, BOSS, onset-rime).

<sup>1</sup> The syllable in Spanish consists of an 'onset' (initial consonant or cluster) plus a 'rime' (vowel and any following consonants).

2009), suggesting that a phonemic deficit is curtailing the development of phonological decoding. In addition, the degree of phonological reading deficit is not related to the degree

The results of this study indicated that computer-assisted practice proved to be as beneficial to the GV poor reader group as for the dyslexic group. We found that reading-disabled children with and without IQ-achievement discrepancy improved their performance on word reading, in comparison to the control group. Nevertheless, dyslexics had more difficulties than GV poor readers during computer-based word reading under conditions that required extensive phonological computation because they were more affected by low frequency words and long words. For another study, Jiménez et al. (2007) assessed the effects of four reading-training procedures for children with reading disabilities (RD) in Spain, with the aim of examining the effects of different spelling-to-sound units in computer speech-based reading. A sample of 82 Spanish children ranging between 7 years 1 month and 10 years 6 months, and whose pseudoword reading performance was below the 25th percentile and IQ >90 were selected. The subjects were randomly assigned to five groups: (1) the Whole-Word training group (WW) (n=16), (2) the Syllable training group (S) (n=16), (3) the Onset-Rime1 training group (OR) (n=17), (4) the Phoneme training group (P) (n =15), and (5) the untrained control group (n= 18). Children were pre- and post-tested in word recognition, reading comprehension, phonological awareness, and visual and phonological tasks. Results indicated that experimental groups who participated in the phoneme and whole-word condition improved their word recognition compared to the control group. In addition, dyslexics who participated in the phoneme, syllable and onset-rime conditions applied for more number of calls during computer-based word reading under conditions that required extensive phonological computation (low frequency words and long words). However, reading time was greater for long words in the phoneme group during computerbased reading. The authors concluded that reading on the computer with speech feedback can provide a helpful remedial tool for children with RD in a transparent orthography.

Regarding the best instructional intervention for remediating reading disabilities, Swanson (1999) tested in his study whether certain models of instruction (e.g., direct instruction, strategy instruction, etc.) have broad effects across word-recognition and comprehension measures. He found that effect sizes were higher for word recognition when studies included direct instruction. Additionally, an increasing number of researchers have used computers in experiments on the remediation of reading disabilities (e.g., Jones, Torgesen & Sexton, 1987; Olofsson, 1992; Olson & Wise, 1992; Torgesen & Barker, 1995; Van Daal & Reitsma, 1993; Van der Leij, 1994). It has been demonstrated that reading on the computer with speech feedback significantly improved disabled reader's phonological decoding and word recognition. Moreover**,** studies of computer-aided remediation for reading disabled children demonstrated that word recognition skill improved when different forms of

In the teaching of reading, children can be trained on the print-to-sound translation by using linguistic units of different sizes: a word can be taught as a whole unit, in individual lettersound units, or in sublexical units of intermediate size (syllable, BOSS, onset-rime).

1 The syllable in Spanish consists of an 'onset' (initial consonant or cluster) plus a 'rime' (vowel and any

orthographic units were manipulated (Olson & Wise, 1992).

following consonants).

of discrepancy between reading and IQ (for a review see, Stanovich & Siegel, 1994).

However, the spelling-to-sound unit used in training may be a critical factor in determining the effectiveness of remedial instruction for RD. Consequently, various remedial studies carried out in English have tried to determine which is the size of the spelling-to-sound unit more optimal for computer speech-based training of RD (e.g., Lovett, Barron, Forbes, Cuksts, & Steinbach, 1994; Olson & Wise, 1992). For Spanish, the Syllable and Onset-Rime condition did not contribute to improve phonological decoding. This finding is not surprising because this type of units does not seem to be as relevant in a language where a direct correspondence between graphemes and phonemes does exist, and where the syllable boundaries are well defined. Therefore, Jiménez et al (2003) suggested that in a transparent orthography such as Spanish, remedial education may be more successful if it concentrates on the phoneme level more than on onset-rime units, in contrast to what has been suggested by Treiman (1992) in the English language. The improvements in the Phoneme group support the idea that the phonemic level plays an important role in dyslexia in a transparent orthography as Spanish. By forcing attention to individual letters within the word and with the speech feedback at the same time during the training, could provide the basis to improve phonemic segmentation skills, and promoting the grapheme-phoneme correspondences, an ability that is not achieved by the severe RD children. In relation to the Whole Word condition, interestingly, this unit also benefited word recognition ability. A possible explanation for this finding has to do with the fact that the dual route model of reading is functional in Spanish despite its orthographic transparency by which, in principle, all the words could be read by the phonological route. Some empirical data support the functionality of both routes in Spanish children (Defior, Justicia & Martos, 1996; Valle-Arroyo, 1989), suggesting no differences between the processes involved in the reading of Spanish and those implicated in opaque orthographies, such as English. In this sense, it is important to note that children who participated in this study were between 7-10 years old, an age in which we would expect the use of the orthographic routine of reading. The reason for the gains after treatment within this experimental condition may be explained by the fact that children could place their attention on the whole word present on the computer screen with the phonological speech feedback. This connection between the word and its individual sounds may have enhanced the connections between their orthographic and phonological forms.

#### **4. Concluding discussion**

Wydell and Butterworth (1999) suggested that the effect of a phonological deficit on reading depends on the transparency of the orthography. Probably the most likely source of these difficulties is a deficit in representing phonological information at earlier developing levels of phonology: the syllable, onset, and rime. Goswami (2002) suggested that syllabic representation is basic to many languages, and that children's ability to recognize syllables and rhymes precedes learning a particular spelling system. This developmental view can readily explain cross-language differences in reading acquisition, and it can also explain cross-language differences in the manifestation of developmental dyslexia (see also Wydell & Butterworth, 1999; Wydell & Kondo, 2003 for a similar conclusion). Some of the processes underpinning language acquisition are disrupted in developmental dyslexia leading to deficits in the development of a phonological representation of words before literacy is acquired. According to this theoretical analysis, dyslexic children in all languages appear to have a phonological deficit at the syllable and rhyme levels prior to acquiring literacy. This

The Role of Phonological Processing in Dyslexia in the Spanish Language 43

Empirical evidence indicates that computer-assisted practice can improve word recognition for reading disabled children compared to a control group. However, we also found that the performance of dyslexic children during computer-based word reading was also affected by

To conclude, the research findings presented here provide empirical support to the hypothesis based on a phonemic deficit in dyslexia in a transparent orthography. Moreover, the research findings demonstrate that reading by the computer with speech feedback may constitute a helpful remedial tool for children with RD. Consequently, both studies reported here provide empirical evidence about the role of phonological processing in dyslexia in the

The origin of this phonological deficit in developmental dyslexia is also open to debate. Sprenger-Charolles et al. (2006) examined the classical phonological explanation that ascribes dyslexics' reading deficit to a specific cognitive deficiency in phonological processing, primarily in phonemic awareness and in phonological short-term memory. They also examined the current non-phonological explanations that assume that the phonological deficit of dyslexics is secondary to more basic sensori-motor impairment: a deficiency in either rapid auditory processing, or in the visual magnocellular pathway, or in motor skills. The authors show why perceptual explanations of dyslexia should be based on alternative perceptual modes rather than on deficits, and they place the perceptual explanation in the framework of a three-stage model of speech perception. They argue that dyslexics' phonological deficits are secondary to more basic sensori-motor impairments. Overall, they concluded that the non-phonological explanations are rather weak, and they propose a new phonological explanation for dyslexia, based on a specific mode of speech perception. In sum, "allophonic perception offers a new perspective in the study of dyslexia. Therefore, further research is necessary to gain a better understanding of the way dyslexics perceive speech, and especially how they segment the speech stream. While allophonic theory constitutes a first step in this direction, it still has to be articulated with other dimensions of

This manuscript has been supported by a grant from Ministerio de Asuntos Exteriores y de Cooperación, AECID, number C/030692/10, Spain. We are grateful to Doris Baker for her careful editing and for the many invaluable corrections she proposed, both in content and on technical and stylistic matters. Correspondence should be addressed to Juan E. Jiménez, Departamento de Psicología Evolutiva y de la Educación, Universidad de La Laguna, Campus de Guajara, 38200 Islas Canarias, España. Electronic mail may be sent to

Backman, J., Mamen, M., & Ferguson, H.B. (1984). Reading level design: Conceptual and methodological issues in reading research. *Psychological Bulletin, 96*, 560-568. Bowey, J.A. y Francis, J. (1991). Phonological analysis as a function of age and exposure to

reading instruction. *Applied Psycholinguistics, 12*, 91-121.

low frequency words and long words.

language processing" (p. 172).

**5. Acknowledgment** 

ejimenez@ull.es

**6. References** 

Spanish language, consistent with other multiple case studies.

deficit leads to problems in acquiring letter-sound relationships and in restructuring the phonological lexicon to represent phoneme-level information.

Some linguists have suggested that different phonological units exist in the Spanish language (i.e., syllable, onset and rime). Jiménez and Ortiz (1993) designed a study to verify whether or not such linguistic realities are psychological realities as has been found in the English language. The results obtained suggested that children at the pre-reading stage are more sensitive to syllabic units, than to instrasyllabic and phonemic units. Moreover, they demonstrated that good readers did not differ from disabled readers and non readers at the syllabic awareness level, but they had higher levels of instrasyllabic awareness, and phonemic awareness. In languages like Spanish, onset-rime segmentation is equivalent to phonemic segmentation for many words (e.g., for a word like "loro", the onset-rimes are /l/ /O/ /r/ /O/ and so are the phonemes). In fact, Spanish children with reading disabilities do not use correspondences based on higher level units as onsets and rimes in visual word recognition (Jiménez, Alvarez, Estévez & Hernández-Valle, 2000). Goswami (2002) also suggested that dyslexic children learning to read in languages with a simple syllabic structure would probably have less difficulty in the acquisition of grapheme-phoneme recoding strategies. However, in the first study presented here both Spanish dyslexic subtype samples were impaired as a group relative to the CA group on phonological awareness tasks analyzed. Both dyslexic subtypes performed significantly worse than the RL group on the measures of phonological awareness suggesting that a phonemic deficit is curtailing the development of phonological decoding. We replicated the finding of a dyslexic deficit in an RL match that we found for previous studies conducted in a transparent orthography (i.e., Spanish) (Jiménez, 1997; Jiménez & Hernández-Valle, 2000).

On the other hand, Stanovich et al. (1997b) suggested that surface dyslexia may arise from a milder form of phonological deficit than phonological dyslexia; this type of difficulty could be influenced by the orthographic peculiarities of the language. We suggested that in a transparent orthography the difficulties with the phonological processing emerge more clearly, especially in surface dyslexia. Therefore, we suggest that the existence of dyslexic subtypes could be a consequence of the differences in the orthographic systems.

We would like to conclude this section by pointing out that in studies employing accuracybased measures of subtypes, the subjects have been selected on the basis of accuracy-based reading scores (Jiménez, 2010). But there is a pool of subjects who might have met ratebased but not accuracy-based criteria for inclusion in a dyslexia study. We do not know what kinds of cognitive and reading profiles rate-disabled children would show, because they are typically not included in subtype studies in English. Until these children are tested, it may be premature to argue that there are differences in the incidence of various subtypes across orthographies. The difference might be due to the accuracy vs. rate criterion of selecting subjects, rather than differences in the orthography, although both could be factors that affect the identification of a reading disability. Consequently, this issue is open to debate and it is exemplified by observations made by Share (2008): 'it remains to be seen to what extent the classic dual-route distinction between phonological and surface dyslexia, a purely accuracy-based dichotomy, relates to accuracy/speed differences, particularly in the case of more conventional (i.e. transparent) orthographies'.

Empirical evidence indicates that computer-assisted practice can improve word recognition for reading disabled children compared to a control group. However, we also found that the performance of dyslexic children during computer-based word reading was also affected by low frequency words and long words.

To conclude, the research findings presented here provide empirical support to the hypothesis based on a phonemic deficit in dyslexia in a transparent orthography. Moreover, the research findings demonstrate that reading by the computer with speech feedback may constitute a helpful remedial tool for children with RD. Consequently, both studies reported here provide empirical evidence about the role of phonological processing in dyslexia in the Spanish language, consistent with other multiple case studies.

The origin of this phonological deficit in developmental dyslexia is also open to debate. Sprenger-Charolles et al. (2006) examined the classical phonological explanation that ascribes dyslexics' reading deficit to a specific cognitive deficiency in phonological processing, primarily in phonemic awareness and in phonological short-term memory. They also examined the current non-phonological explanations that assume that the phonological deficit of dyslexics is secondary to more basic sensori-motor impairment: a deficiency in either rapid auditory processing, or in the visual magnocellular pathway, or in motor skills. The authors show why perceptual explanations of dyslexia should be based on alternative perceptual modes rather than on deficits, and they place the perceptual explanation in the framework of a three-stage model of speech perception. They argue that dyslexics' phonological deficits are secondary to more basic sensori-motor impairments. Overall, they concluded that the non-phonological explanations are rather weak, and they propose a new phonological explanation for dyslexia, based on a specific mode of speech perception. In sum, "allophonic perception offers a new perspective in the study of dyslexia. Therefore, further research is necessary to gain a better understanding of the way dyslexics perceive speech, and especially how they segment the speech stream. While allophonic theory constitutes a first step in this direction, it still has to be articulated with other dimensions of language processing" (p. 172).

#### **5. Acknowledgment**

42 Dyslexia – A Comprehensive and International Approach

deficit leads to problems in acquiring letter-sound relationships and in restructuring the

Some linguists have suggested that different phonological units exist in the Spanish language (i.e., syllable, onset and rime). Jiménez and Ortiz (1993) designed a study to verify whether or not such linguistic realities are psychological realities as has been found in the English language. The results obtained suggested that children at the pre-reading stage are more sensitive to syllabic units, than to instrasyllabic and phonemic units. Moreover, they demonstrated that good readers did not differ from disabled readers and non readers at the syllabic awareness level, but they had higher levels of instrasyllabic awareness, and phonemic awareness. In languages like Spanish, onset-rime segmentation is equivalent to phonemic segmentation for many words (e.g., for a word like "loro", the onset-rimes are /l/ /O/ /r/ /O/ and so are the phonemes). In fact, Spanish children with reading disabilities do not use correspondences based on higher level units as onsets and rimes in visual word recognition (Jiménez, Alvarez, Estévez & Hernández-Valle, 2000). Goswami (2002) also suggested that dyslexic children learning to read in languages with a simple syllabic structure would probably have less difficulty in the acquisition of grapheme-phoneme recoding strategies. However, in the first study presented here both Spanish dyslexic subtype samples were impaired as a group relative to the CA group on phonological awareness tasks analyzed. Both dyslexic subtypes performed significantly worse than the RL group on the measures of phonological awareness suggesting that a phonemic deficit is curtailing the development of phonological decoding. We replicated the finding of a dyslexic deficit in an RL match that we found for previous studies conducted in a transparent orthography (i.e., Spanish) (Jiménez, 1997; Jiménez &

On the other hand, Stanovich et al. (1997b) suggested that surface dyslexia may arise from a milder form of phonological deficit than phonological dyslexia; this type of difficulty could be influenced by the orthographic peculiarities of the language. We suggested that in a transparent orthography the difficulties with the phonological processing emerge more clearly, especially in surface dyslexia. Therefore, we suggest that the existence of dyslexic

We would like to conclude this section by pointing out that in studies employing accuracybased measures of subtypes, the subjects have been selected on the basis of accuracy-based reading scores (Jiménez, 2010). But there is a pool of subjects who might have met ratebased but not accuracy-based criteria for inclusion in a dyslexia study. We do not know what kinds of cognitive and reading profiles rate-disabled children would show, because they are typically not included in subtype studies in English. Until these children are tested, it may be premature to argue that there are differences in the incidence of various subtypes across orthographies. The difference might be due to the accuracy vs. rate criterion of selecting subjects, rather than differences in the orthography, although both could be factors that affect the identification of a reading disability. Consequently, this issue is open to debate and it is exemplified by observations made by Share (2008): 'it remains to be seen to what extent the classic dual-route distinction between phonological and surface dyslexia, a purely accuracy-based dichotomy, relates to accuracy/speed differences, particularly in the

subtypes could be a consequence of the differences in the orthographic systems.

case of more conventional (i.e. transparent) orthographies'.

phonological lexicon to represent phoneme-level information.

Hernández-Valle, 2000).

This manuscript has been supported by a grant from Ministerio de Asuntos Exteriores y de Cooperación, AECID, number C/030692/10, Spain. We are grateful to Doris Baker for her careful editing and for the many invaluable corrections she proposed, both in content and on technical and stylistic matters. Correspondence should be addressed to Juan E. Jiménez, Departamento de Psicología Evolutiva y de la Educación, Universidad de La Laguna, Campus de Guajara, 38200 Islas Canarias, España. Electronic mail may be sent to ejimenez@ull.es

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**4** 

*Japan* 

Norbert Maïonchi-Pino

**Phonological Restriction Knowledge in** 

*Tohoku University, Institute of Development, Aging and Cancer,* 

*Department of Developmental Cognitive Neuroscience & Department of Functional Brain Imaging, Sendai,* 

**Dyslexia: Universal or Language-Specific?** 

Developmental dyslexia is the most studied and well-documented of the specific learning disabilities in school-age children across languages, which reaches from 5-to-17.5% individuals (e.g., Shaywitz & Shaywitz, 2005; Snowling, 2001). There is now a consensus that developmental dyslexia stems from a genetic neurodevelopmental disorder that does not depend on inadequate intellectual or educational backgrounds (e.g., Lyon, Shaywitz, & Shaywitz, 2003; Sprenger-Charolles, Colé, Lacert, & Serniclaes, 2000; Vellutino, Fletcher, Snowling, & Scanlon, 2004). There is considerable evidence for a phonological deficit as the major correlate of language disabilities in dyslexia, which underpins the cognitive disorder (e.g., Ramus, Rosen, Dakin, Day, Castellote, White, & Frith, 2003; Ziegler & Goswami, 2005). However, an outstanding, long-lasting question that remains unclear, even unanswered, is what underlies the phonological deficit in dyslexia (e.g., Ramus, 2001). Three main directions have been proposed to account for the phonological deficit: 1) limited phonological short-term memory; 2) degraded, under-specified or, conversely, overspecified phonological representations; 3) speech perception disorders. However, the degraded, under-specified phonological representation hypothesis that is basically referred to accounts for the dyslexics' phonological deficit has been recently challenged: it has been suggested that the dyslexics' phonological deficit relies on difficulties to store, access, and retrieve the phonological representations (e.g., Ahissar, 2007; Ramus & Szenkovits, 2008; Szenkovits & Ramus, 2005). To date, to reconcile both views, it has been proposed that the phonological deficit results in multi-dimensional difficulties that include difficulties to learn and manipulate the speech units as well as difficulties to store, access, and retrieve the phonological representations (e.g., Snowling, 2001; Ziegler, Castel, Pech-Geogel, George, Alario, & Perry, 2008). Despite this tentative proposal, there is no consensus. Here, I propose to draw an up-to-date portrait of an alternative option that has not been studied so far to disentangle whether another possible source of the phonological deficit in dyslexia may be

envisaged: Are dyslexics sensitive to *universal* phonological knowledge?

Overall, what the past studies have revealed is that the phonological deficit has no clear-cut well-specified origins. Within the phonological deficit hypothesis, typically, it has been

**2. On the possible origins of the phonological deficit** 

**1. Introduction** 


## **Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific?**

#### Norbert Maïonchi-Pino

*Tohoku University, Institute of Development, Aging and Cancer, Department of Developmental Cognitive Neuroscience & Department of Functional Brain Imaging, Sendai, Japan* 

#### **1. Introduction**

46 Dyslexia – A Comprehensive and International Approach

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Wagner, R.K., & Torgesen, J.K., (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. *Psychological Bulletin, 101*, 192-212. Wydell, T.N. & Butterworth, B.L. (1999). A case study of an English-Japanese bilingual with

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Gough, L. Ehri, & R. Treiman (Eds.), *Reading acquisition* (pp. 65-106). Hillsdale, NJ:

readers in computer-based reading practice. *Reading and Writing: An* 

disorders. In K.P. Van den Bos, L.S. Siegel, D.J. Bakker y D.L. Share (Eds.). *Current directions in dyslexia research* (pp.201-219). Lisse, Netherlands: Swets & Zeitlinger. Van der Leij, A., (1994). Effects of computer-assisted instruction on word and pseudoword

reading of reading-disabled student. In K.P. Van den Bos, L.S. Siegel, D.J. Bakker y D.L. Share (Eds.). *Current directions in dyslexia research* (pp.251-267). Lisse,

approximation for reading: A follow-up study on an English-Japanese bilingual

intervention outcomes. *Journal of Learning Disabilities, 32*, 504-532.

of reading disabilities. *Learning Disability Quarterly, 18*, 76-87.

and spelling. A dual route model] *Cognitiva, 2,* 35-63.

difference model. *Journal of Educational Psychology*, *86*, 24-53.

reliability of phonological, surface, and mixed profiles in dyslexia: A review of studies conducted in languages varying in orthographic depth. *Scientific Studies of* 

reading disabilities: A regression-based test of the phonological-core variable-

subtypes. In C.Hulme & M.Snowling (Eds.). *Biology, cognition and intervention* (pp.

and surface subtypes of reading disability. *Journal of Educational Psychology, 89*, 114-

*dyslexia*. New York: Psychology Press.

108-130). London: Whurr Publishers Ltd.

*Reading*, 15, 6, 498-521

Madrid: Aprendizaje Visor.

*Interdisciplinary Journal, 5*, 243-259.

Netherlands: Swets & Zeitlinger.

monolingual dyslexia. *Cognition*, 70, 273–305.

127.

LEA.

Developmental dyslexia is the most studied and well-documented of the specific learning disabilities in school-age children across languages, which reaches from 5-to-17.5% individuals (e.g., Shaywitz & Shaywitz, 2005; Snowling, 2001). There is now a consensus that developmental dyslexia stems from a genetic neurodevelopmental disorder that does not depend on inadequate intellectual or educational backgrounds (e.g., Lyon, Shaywitz, & Shaywitz, 2003; Sprenger-Charolles, Colé, Lacert, & Serniclaes, 2000; Vellutino, Fletcher, Snowling, & Scanlon, 2004). There is considerable evidence for a phonological deficit as the major correlate of language disabilities in dyslexia, which underpins the cognitive disorder (e.g., Ramus, Rosen, Dakin, Day, Castellote, White, & Frith, 2003; Ziegler & Goswami, 2005). However, an outstanding, long-lasting question that remains unclear, even unanswered, is what underlies the phonological deficit in dyslexia (e.g., Ramus, 2001). Three main directions have been proposed to account for the phonological deficit: 1) limited phonological short-term memory; 2) degraded, under-specified or, conversely, overspecified phonological representations; 3) speech perception disorders. However, the degraded, under-specified phonological representation hypothesis that is basically referred to accounts for the dyslexics' phonological deficit has been recently challenged: it has been suggested that the dyslexics' phonological deficit relies on difficulties to store, access, and retrieve the phonological representations (e.g., Ahissar, 2007; Ramus & Szenkovits, 2008; Szenkovits & Ramus, 2005). To date, to reconcile both views, it has been proposed that the phonological deficit results in multi-dimensional difficulties that include difficulties to learn and manipulate the speech units as well as difficulties to store, access, and retrieve the phonological representations (e.g., Snowling, 2001; Ziegler, Castel, Pech-Geogel, George, Alario, & Perry, 2008). Despite this tentative proposal, there is no consensus. Here, I propose to draw an up-to-date portrait of an alternative option that has not been studied so far to disentangle whether another possible source of the phonological deficit in dyslexia may be envisaged: Are dyslexics sensitive to *universal* phonological knowledge?

#### **2. On the possible origins of the phonological deficit**

Overall, what the past studies have revealed is that the phonological deficit has no clear-cut well-specified origins. Within the phonological deficit hypothesis, typically, it has been

Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific? 49

universal phonological well-formedness), I here envisage the universal phonological sonority-related *markedness* to provide further arguments on the origin of the dyslexics' phonological deficit: universal or language-dependent and degraded/under-specified

Native phonological knowledge includes a phonological grammar that embeds languagespecific phonemes and phonotactic restrictions that constrain the co-occurrence of sound sequences to perceive and produce sentences (e.g., de Lacy, 2007). In normally-developing newborns and adults, this is a well-known phenomenon that listeners tend to misperceive and repair phonotactically-illegal sound sequences in their native language. Given that the perceptual system becomes, early-on, attuned to sounds and phonotactic restrictions relevant to the native language (e.g., Jusczyk, Friederici, Wessels, Svenkerud, Jusczyk, 1993; Kuhl, Andrusko, Chistovich, Chistovich, Kozhevnikova, Ryskina, Stolyarova, Sundberg, Lacerda, 1997), it has been argued that the perceptual repair could result from: 1) a perceptual assimilation of acoustic-phonetic properties of nonnative sound sequences into native ones or to the phonetically-close ones (e.g., /dla/ in /gla/; in English: Best, 1995; in French: Hallé, Seguí, Frauenfelder, & Meunier, 1998); 2) a compensation for coarticulation since sound sequences such as /dla/ are more difficult to perceive and articulate than /gla/ (e.g., Wright, 2004); 3) a perceptual fit to the phonotactic probablities (e.g., Bonte, Mitterer, Zellagui, Poelmans, & Blomert, 2005); 4) an *illusory epenthetic vowel*; an epenthesis may be a consonant or a vowel present in the phoneme inventory of a target-language, which is inserted to restore a native phonotactically-legal sound sequence (e.g., /dəl/ in English: Berent, Steriade, Lennertz, & Vaknin, 2007; /buz/ in Japanese: Dupoux, Kakehi, Hirose, Pallier, & Mehler, 1999; /dil/ in Portuguese: Dupoux, Parlato, Frota, Hirose, & Peperkamp, 2011). However, in dyslexic adults or children, data remain rare, and focus on phonotactic probabilities (e.g., Bonte, Poelmans, & Blomert, 2007) or, recently, on compensation for place assimilation (e.g., Marshall, Ramus, & van der Lely, in press) and voicing assimilation (e.g., Szenkovits, Darma, Darcy, & Ramus, submitted). Ramus and collaborators thus showed that French dyslexics assimilated phonotactically-illegal sound sequences into phonotacticallylegal ones to the same extent as controls. This suggests that dyslexics are able to normally acquire native phonological grammar, and questions the degraded phonological grammar

phonological representations or difficulties to access them?

**3. Why the phonological grammar is of interest?** 

and representations (for counter-arguments, see Bonte et al., 2007).

As hypothesized within the Optimality Theory framework (Prince & Smolensky, 1993; 1997; 2004), sound sequences that are phonotactically-illegal clusters such as /ʁb/ are more likely rejected compared to phonotactically-legal clusters such as /bʁ/ since all speakers are supposed to have universal phonological knowledge on grammatical restrictions irrespective to their (acoustic-)phonetic properties and phonotactic probabilities. However, whether dyslexics have universal phonological knowledge on grammatical restrictions

**3.1 A phonological grammar?** 

**3.2 An unexplored alternative** 

remain unexplored.

suggested that the core deficit children face is rooted in degraded, under-specified phonological representation (e.g., Boada & Pennington, 2006; Elbro & Jensen, 2005; Snowling, 2001).

In a non-negligible proportion, dyslexics' phonological deficit originates in impairments to process auditory information (i.e., ≈ 50%; Ramus et al., 2003). Typically, to account for the degraded nature of the phonological representations, it has been hypothesized that the dyslexics' perceptual system could not turn to be attuned to the native phonemic categories as shown with impairments in categorical perception (e.g., Adlard & Hazan, 1998; Mody, Studdert-Kennedy, & Brady, 1997; Veuillet, Magnan, Écalle, Thai-Van, & Collet, 2007). The categorical perception refers to the tendency to perceive a sound as a member of a category (e.g., /b/ or /p/). Thus, the variants of the same phoneme within a category are more likely perceived as being similar to each other compared to phonemes from other categories (i.e., /bh/ is more likely judged as similar to /b/ than /p/ while /ph/ is more likely judged as similar to /p/ than /b/. Scientifically-speaking, the categorical perception can be described as "the degree to which acoustic differences between variants of the same phoneme are less perceptible than differences of the same acoustic magnitude between two different phonemes" (Serniclaes et al., 2004, p. 337). Indeed, dyslexics have been shown to be impaired the processing of relevant acoustic-phonetic characteristics in their native language such as the voicing (e.g., /ba/ - /pa/; Bogliotti, Serniclaes, Messaoud-Galusi, & Sprenger-Charolles, 2008; Hoonhorst, Colin, Markessis, Radeau, Deltenre, & Serniclaes, 2009; Serniclaes, Sprenger-Charolles, Carré, & Démonet, 2001; Serniclaes, van Heghe, Mousty, Carré, & Sprenger-Charolles, 2004). Lower performances in between-categories perception but higher performances in within-categories perception compared to both chronological age-matched and reading level-matched controls have been interpreted as an allophonic mode of speech perception1. In other words, dyslexics have difficulties to discriminate two phonemes that belong to two different categories as determined by the voicing (i.e., /ba/ vs. /pa/; low between-boundaries performance) whereas they can discriminate two variants of a same phoneme even if one of the variant does not exist in the native language (e.g., /p/ and /ph/; high within-boundaries performance). Hence, dyslexics' phonological representations would be over-specified since dyslexics would maintain acoustic-phonetic contrasts that are irrelevant in their native language and should be deactivated early in life (e.g., Saffran, Werker, & Werner, 2006; Werker & Tees, 1984). To be unable to discriminate relevant acoustic-phonetic duration-based contrasts in their native language (i.e., voicing; e.g., /b/ vs. /p/) would induce degraded, under-specified phonological representations and subsequent difficulties to use grapheme-to-phoneme correspondences (e.g., Bogliotti et al., 2008; Serniclaes et al., 2004). Alternatively, the phonological deficit could stem from difficulties in the time-course aspects of pre-lexical phonetic-phonological processing rather than from impaired phonological-lexical representations (e.g., Blomert, Mitterer, & Paffen, 2004; Nittrouer, 1999).

To determine whether the dyslexic's perceptual system is tuned to process finely-sharpened universal phonological representations (i.e., sound sequences that respect or not the

<sup>1</sup> An allophone is a contextual variant of a same phoneme which may be not distinguished within a same phonemic category (e.g., /r/ and /ʁ/ in French). For instance, in French, replacing /r/ with /ʁ/ in /pri/ 'price' will not change its meaning while replacing /r/ or /ʁ/ with /l/ will, i.e., /pli/ ' wrinkle'. Allophones are language-dependent.

universal phonological well-formedness), I here envisage the universal phonological sonority-related *markedness* to provide further arguments on the origin of the dyslexics' phonological deficit: universal or language-dependent and degraded/under-specified phonological representations or difficulties to access them?

#### **3. Why the phonological grammar is of interest?**

#### **3.1 A phonological grammar?**

48 Dyslexia – A Comprehensive and International Approach

suggested that the core deficit children face is rooted in degraded, under-specified phonological representation (e.g., Boada & Pennington, 2006; Elbro & Jensen, 2005;

In a non-negligible proportion, dyslexics' phonological deficit originates in impairments to process auditory information (i.e., ≈ 50%; Ramus et al., 2003). Typically, to account for the degraded nature of the phonological representations, it has been hypothesized that the dyslexics' perceptual system could not turn to be attuned to the native phonemic categories as shown with impairments in categorical perception (e.g., Adlard & Hazan, 1998; Mody, Studdert-Kennedy, & Brady, 1997; Veuillet, Magnan, Écalle, Thai-Van, & Collet, 2007). The categorical perception refers to the tendency to perceive a sound as a member of a category (e.g., /b/ or /p/). Thus, the variants of the same phoneme within a category are more likely perceived as being similar to each other compared to phonemes from other categories (i.e., /bh/ is more likely judged as similar to /b/ than /p/ while /ph/ is more likely judged as similar to /p/ than /b/. Scientifically-speaking, the categorical perception can be described as "the degree to which acoustic differences between variants of the same phoneme are less perceptible than differences of the same acoustic magnitude between two different phonemes" (Serniclaes et al., 2004, p. 337). Indeed, dyslexics have been shown to be impaired the processing of relevant acoustic-phonetic characteristics in their native language such as the voicing (e.g., /ba/ - /pa/; Bogliotti, Serniclaes, Messaoud-Galusi, & Sprenger-Charolles, 2008; Hoonhorst, Colin, Markessis, Radeau, Deltenre, & Serniclaes, 2009; Serniclaes, Sprenger-Charolles, Carré, & Démonet, 2001; Serniclaes, van Heghe, Mousty, Carré, & Sprenger-Charolles, 2004). Lower performances in between-categories perception but higher performances in within-categories perception compared to both chronological age-matched and reading level-matched controls have been interpreted as an allophonic mode of speech perception1. In other words, dyslexics have difficulties to discriminate two phonemes that belong to two different categories as determined by the voicing (i.e., /ba/ vs. /pa/; low between-boundaries performance) whereas they can discriminate two variants of a same phoneme even if one of the variant does not exist in the native language (e.g., /p/ and /ph/; high within-boundaries performance). Hence, dyslexics' phonological representations would be over-specified since dyslexics would maintain acoustic-phonetic contrasts that are irrelevant in their native language and should be deactivated early in life (e.g., Saffran, Werker, & Werner, 2006; Werker & Tees, 1984). To be unable to discriminate relevant acoustic-phonetic duration-based contrasts in their native language (i.e., voicing; e.g., /b/ vs. /p/) would induce degraded, under-specified phonological representations and subsequent difficulties to use grapheme-to-phoneme correspondences (e.g., Bogliotti et al., 2008; Serniclaes et al., 2004). Alternatively, the phonological deficit could stem from difficulties in the time-course aspects of pre-lexical phonetic-phonological processing rather than from impaired phonological-lexical

representations (e.g., Blomert, Mitterer, & Paffen, 2004; Nittrouer, 1999).

wrinkle'. Allophones are language-dependent.

To determine whether the dyslexic's perceptual system is tuned to process finely-sharpened universal phonological representations (i.e., sound sequences that respect or not the

1 An allophone is a contextual variant of a same phoneme which may be not distinguished within a same phonemic category (e.g., /r/ and /ʁ/ in French). For instance, in French, replacing /r/ with /ʁ/ in /pri/ 'price' will not change its meaning while replacing /r/ or /ʁ/ with /l/ will, i.e., /pli/ '

Snowling, 2001).

Native phonological knowledge includes a phonological grammar that embeds languagespecific phonemes and phonotactic restrictions that constrain the co-occurrence of sound sequences to perceive and produce sentences (e.g., de Lacy, 2007). In normally-developing newborns and adults, this is a well-known phenomenon that listeners tend to misperceive and repair phonotactically-illegal sound sequences in their native language. Given that the perceptual system becomes, early-on, attuned to sounds and phonotactic restrictions relevant to the native language (e.g., Jusczyk, Friederici, Wessels, Svenkerud, Jusczyk, 1993; Kuhl, Andrusko, Chistovich, Chistovich, Kozhevnikova, Ryskina, Stolyarova, Sundberg, Lacerda, 1997), it has been argued that the perceptual repair could result from: 1) a perceptual assimilation of acoustic-phonetic properties of nonnative sound sequences into native ones or to the phonetically-close ones (e.g., /dla/ in /gla/; in English: Best, 1995; in French: Hallé, Seguí, Frauenfelder, & Meunier, 1998); 2) a compensation for coarticulation since sound sequences such as /dla/ are more difficult to perceive and articulate than /gla/ (e.g., Wright, 2004); 3) a perceptual fit to the phonotactic probablities (e.g., Bonte, Mitterer, Zellagui, Poelmans, & Blomert, 2005); 4) an *illusory epenthetic vowel*; an epenthesis may be a consonant or a vowel present in the phoneme inventory of a target-language, which is inserted to restore a native phonotactically-legal sound sequence (e.g., /dəl/ in English: Berent, Steriade, Lennertz, & Vaknin, 2007; /buz/ in Japanese: Dupoux, Kakehi, Hirose, Pallier, & Mehler, 1999; /dil/ in Portuguese: Dupoux, Parlato, Frota, Hirose, & Peperkamp, 2011). However, in dyslexic adults or children, data remain rare, and focus on phonotactic probabilities (e.g., Bonte, Poelmans, & Blomert, 2007) or, recently, on compensation for place assimilation (e.g., Marshall, Ramus, & van der Lely, in press) and voicing assimilation (e.g., Szenkovits, Darma, Darcy, & Ramus, submitted). Ramus and collaborators thus showed that French dyslexics assimilated phonotactically-illegal sound sequences into phonotacticallylegal ones to the same extent as controls. This suggests that dyslexics are able to normally acquire native phonological grammar, and questions the degraded phonological grammar and representations (for counter-arguments, see Bonte et al., 2007).

#### **3.2 An unexplored alternative**

As hypothesized within the Optimality Theory framework (Prince & Smolensky, 1993; 1997; 2004), sound sequences that are phonotactically-illegal clusters such as /ʁb/ are more likely rejected compared to phonotactically-legal clusters such as /bʁ/ since all speakers are supposed to have universal phonological knowledge on grammatical restrictions irrespective to their (acoustic-)phonetic properties and phonotactic probabilities. However, whether dyslexics have universal phonological knowledge on grammatical restrictions remain unexplored.

Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific? 51

clusters with a sonority plateau are less marked than onset clusters with a sonority low-fall (e.g., /ft/, *s* = -1), which are less marked than onset clusters with a sonority high-fall (e.g., /ʁb/, *s* = -3). Hence, monotically, markedness increases and well-formedness decreases from sonority high-rise (unmarked structures) to sonority high-fall (marked structures).

As I mentioned above, there is plenty of work to refine our understanding of where the phonological deficit comes from. Does the phonological deficit arise from degraded, underspecified phonological representations? If the phonological representations are intact, do dyslexic children have intact universal phonological representations? To provide innovative arguments in speech perception in dyslexia, I designed a preliminary syllable count task to pit the universal phonological knowledge on grammatical restrictions in French dyslexic children. I tested the (mis)perception of marked, grammatically ill-formed unattested onset clusters in French dyslexic compared to chronological age-matched controls and reading level-matched controls. Children were aurally-administered monosyllabic C1C2VC3 pseudowords (e.g., /pkal/) and their disyllabic C1uC2VC3 counterparts (e.g., /pukal/). All C1C2 clusters within monosyllabic pseudowords were constructed by splicing out the /u/. Onset clusters (C1C2) were classified as high-fall, low-fall, plateau, low-rise or high-rise.

Given the markedness constraints (i.e., avoid marked, grammatically ill-formed outputs such as /ʁb/) and the faithfulness constraints (i.e., map the input /ʁb/ to the output /ʁb/), the misperception of C1C2 clusters should increase as markedness increases. Hence, if perceptual confusion depends on universal markedness-related knowledge as determined by sonority profiles, /gmal/ (high-rise SP, the most marked) should be more misperceived as disyllabic than /pkal/ (plateau SP), which in turn, should be more misperceived than /ʁbal/ (high-fall SP, the least marked) in both chronological age-matched and reading levelmatched controls. However, since dyslexics are supposed to have degraded, underspecified phonological representations, phonological sonority-related markedness effects

and phonological repair with an illusory epenthetic vowel should not be observed.

Five French dyslexic children with no comorbid attention deficit hyperactivity disorder (ADHD) were tested in this experiment. Dyslexic children were compared to five chronological age-matched controls and five reading level-matched controls. Control children were recruited from an urban public elementary school. All children were tested after parents returned a consent form. Dyslexic children were diagnosed as dyslexics around two years prior this experiment (*M* = 29 months; *SD* = 4 months) by a speech and language therapist. All children were French native speakers with no second language learning, middle class, and right-handed2. They reported no hearing disorders. Reading level and IQs

2 Children's right-handedness was assessed with the Edinburgh Handedness Inventory (Oldfield, 1971)

**4. The present study** 

**5. Experiment 1** 

**5.1.1 Participants** 

and all scored between +0.80 and +1.

**5.1 Method** 

#### **3.2.1 Phonological** *markedness* **and sonority profile**

Phonotactic restrictions straightforwardly rule how sound sequences co-occur. It has been shown that sound sequences depend on the sonority of phonemes (e.g., Clements, 1990). Sonority is a scalar acoustic-phonetic property that refers to the sound's "[…] loudness relative to that of other sounds with the same length, stress, and pitch" (Ladefoged, 1975, p. 221). Under this definition, Fig. 1 presents that sonority hierarchically ranks consonants from the high-sonority phonemes (i.e., from liquid to nasal) to low-sonority ones (i.e., from fricative, /f/, /z/, /ʃ/… to occlusive, /b/, /t/, /g/…). Also, the linguistic structures are supposed to conform to a sonority-based organization as proposed by the *sonority sequencing principle* (e.g., Clements, 1990; Selkirk, 1984): syllables favor a structure with an onset maximally growing in sonority towards the vowel and falling minimally to the coda. Hence, universally-optimal CV syllables that bear high-sonority onsets (e.g., /la/) tend to be avoided in the phonotactics of languages to favor low-sonority ones (e.g., /ta/) whereas, in syllables that do contain a coda, high-sonority codas (e.g., /al/) tend to be preferred to lowsonority ones (e.g., /at/; see Selkirk, 1984). Using a sonority-based distribution of syllables which combines the sonority and the sonority sequencing principle, it is possible to assess the universal phonological knowledge on grammatical restrictions.


Fig. 1. Sonority scale adapted from Clements (1990) and Selkirk (1984).

#### **3.2.2 Sonority-related** *markedness* **as a universal phonological knowledge**

As proposed within the Optimality Theory framework (Prince & Smolensky, 1993; 1997; 2004), all listeners undergo universal *markedness* and *faithfulness constraints*. Markedness constraints are phonological grammatical restrictions that disfavor some grammatically illformed structures (e.g., /ʁb/) whereas faithfulness constraints are constraints that require mapping the input to the output (e.g., mapping the input /ʁb/ to the output /ʁb/). If the input is grammatically well-formed (e.g., /bʁ/), its acoustic-phonetic properties are faithfully encoded and mapped to the output /bʁ/. But, if the input is grammatically illformed (e.g., /ʁb/), the input fails to be faithfully encoded and mapped to the output /ʁb/. Accordingly, a grammatically ill-formed input is recoded as a grammatically well-formed output that could trigger a perceptual confusion (e.g., the insertion of an illusory vowel; i.e., an epenthetic vowel such as /ə/). In the view of the Optimality Theory (Prince & Smolensky, 1993; 1997; 2004), universal low-frequency structures -the grammatically illformed ones- (e.g., /ʁb/) that transgress markedness constraints are labeled as *marked* whereas universal high-frequency structures -the grammatically well-formed ones- (e.g., /bʁ/) are labeled as *unmarked*. Thus, onset clusters with a sonority high-rise (e.g., /bʁ/, *s* = +3) are less marked than onset clusters with a sonority low-rise (e.g., /sm/, *s* = +1), which are less marked than onset clusters with a sonority plateau (e.g., /kb/, *s* = 0). Then, onset

#### **4. The present study**

50 Dyslexia – A Comprehensive and International Approach

Phonotactic restrictions straightforwardly rule how sound sequences co-occur. It has been shown that sound sequences depend on the sonority of phonemes (e.g., Clements, 1990). Sonority is a scalar acoustic-phonetic property that refers to the sound's "[…] loudness relative to that of other sounds with the same length, stress, and pitch" (Ladefoged, 1975, p. 221). Under this definition, Fig. 1 presents that sonority hierarchically ranks consonants from the high-sonority phonemes (i.e., from liquid to nasal) to low-sonority ones (i.e., from fricative, /f/, /z/, /ʃ/… to occlusive, /b/, /t/, /g/…). Also, the linguistic structures are supposed to conform to a sonority-based organization as proposed by the *sonority sequencing principle* (e.g., Clements, 1990; Selkirk, 1984): syllables favor a structure with an onset maximally growing in sonority towards the vowel and falling minimally to the coda. Hence, universally-optimal CV syllables that bear high-sonority onsets (e.g., /la/) tend to be avoided in the phonotactics of languages to favor low-sonority ones (e.g., /ta/) whereas, in syllables that do contain a coda, high-sonority codas (e.g., /al/) tend to be preferred to lowsonority ones (e.g., /at/; see Selkirk, 1984). Using a sonority-based distribution of syllables which combines the sonority and the sonority sequencing principle, it is possible to assess

**3.2.1 Phonological** *markedness* **and sonority profile** 

the universal phonological knowledge on grammatical restrictions.

Fig. 1. Sonority scale adapted from Clements (1990) and Selkirk (1984).

**3.2.2 Sonority-related** *markedness* **as a universal phonological knowledge** 

As proposed within the Optimality Theory framework (Prince & Smolensky, 1993; 1997; 2004), all listeners undergo universal *markedness* and *faithfulness constraints*. Markedness constraints are phonological grammatical restrictions that disfavor some grammatically illformed structures (e.g., /ʁb/) whereas faithfulness constraints are constraints that require mapping the input to the output (e.g., mapping the input /ʁb/ to the output /ʁb/). If the input is grammatically well-formed (e.g., /bʁ/), its acoustic-phonetic properties are faithfully encoded and mapped to the output /bʁ/. But, if the input is grammatically illformed (e.g., /ʁb/), the input fails to be faithfully encoded and mapped to the output /ʁb/. Accordingly, a grammatically ill-formed input is recoded as a grammatically well-formed output that could trigger a perceptual confusion (e.g., the insertion of an illusory vowel; i.e., an epenthetic vowel such as /ə/). In the view of the Optimality Theory (Prince & Smolensky, 1993; 1997; 2004), universal low-frequency structures -the grammatically illformed ones- (e.g., /ʁb/) that transgress markedness constraints are labeled as *marked* whereas universal high-frequency structures -the grammatically well-formed ones- (e.g., /bʁ/) are labeled as *unmarked*. Thus, onset clusters with a sonority high-rise (e.g., /bʁ/, *s* = +3) are less marked than onset clusters with a sonority low-rise (e.g., /sm/, *s* = +1), which are less marked than onset clusters with a sonority plateau (e.g., /kb/, *s* = 0). Then, onset As I mentioned above, there is plenty of work to refine our understanding of where the phonological deficit comes from. Does the phonological deficit arise from degraded, underspecified phonological representations? If the phonological representations are intact, do dyslexic children have intact universal phonological representations? To provide innovative arguments in speech perception in dyslexia, I designed a preliminary syllable count task to pit the universal phonological knowledge on grammatical restrictions in French dyslexic children. I tested the (mis)perception of marked, grammatically ill-formed unattested onset clusters in French dyslexic compared to chronological age-matched controls and reading level-matched controls. Children were aurally-administered monosyllabic C1C2VC3 pseudowords (e.g., /pkal/) and their disyllabic C1uC2VC3 counterparts (e.g., /pukal/). All C1C2 clusters within monosyllabic pseudowords were constructed by splicing out the /u/. Onset clusters (C1C2) were classified as high-fall, low-fall, plateau, low-rise or high-rise.

Given the markedness constraints (i.e., avoid marked, grammatically ill-formed outputs such as /ʁb/) and the faithfulness constraints (i.e., map the input /ʁb/ to the output /ʁb/), the misperception of C1C2 clusters should increase as markedness increases. Hence, if perceptual confusion depends on universal markedness-related knowledge as determined by sonority profiles, /gmal/ (high-rise SP, the most marked) should be more misperceived as disyllabic than /pkal/ (plateau SP), which in turn, should be more misperceived than /ʁbal/ (high-fall SP, the least marked) in both chronological age-matched and reading levelmatched controls. However, since dyslexics are supposed to have degraded, underspecified phonological representations, phonological sonority-related markedness effects and phonological repair with an illusory epenthetic vowel should not be observed.

#### **5. Experiment 1**

#### **5.1 Method**

#### **5.1.1 Participants**

Five French dyslexic children with no comorbid attention deficit hyperactivity disorder (ADHD) were tested in this experiment. Dyslexic children were compared to five chronological age-matched controls and five reading level-matched controls. Control children were recruited from an urban public elementary school. All children were tested after parents returned a consent form. Dyslexic children were diagnosed as dyslexics around two years prior this experiment (*M* = 29 months; *SD* = 4 months) by a speech and language therapist. All children were French native speakers with no second language learning, middle class, and right-handed2. They reported no hearing disorders. Reading level and IQs

 2 Children's right-handedness was assessed with the Edinburgh Handedness Inventory (Oldfield, 1971) and all scored between +0.80 and +1.

Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific? 53

obtained by splicing out step-by-step the vowel /u/ with Praat software (Boersma & Weenink, 2011). Visual and auditory inspection of the waveforms minimized the /u/ coarticulation-based traces in the C1 and C2. Mean duration was 197.3 ms (*SD* = 16.1) for the

This experiment was designed, compiled and run using E-Prime 2.0 Professional software (Schneider, Eschman, & Zuccolotto, 2002) on Sony X-series laptop computers under Windows 7 OS. Children wore Sennheiser HD 25-1 II headphones (16 Hz-22 kHz range, 70 Ω impedance) and were presented pseudowords binaurally at 70 dB SPL. Trials consisted in the presentation of a vertically-centered exclamation mark (i.e., '+') for 500 ms, followed after a 200-ms blank screen by a pseudoword. A 1,000-ms delay separated two consecutive trials. Children were requested to decide as quickly and as accurately as possible whether the pseudoword had one or two syllables (numpad 1 = one syllable, numpad 2 = two syllables). Children were first trained with a practice list of 16 trials with corrective feedback. No feedback was given for the experimental trials. Trials were randomized. The

I report first the results from two 5 x 2 x 3 mixed-design repeated measures ANOVAs with Statistica software by subject (*F*1) and by item (*F*2) on response times and response accuracy (~ 84.1% of the data). ANOVAs were run with Group (dyslexics vs. chronological agematched controls vs. reading level-matched controls) as between-subject factor and Sonority profile (high-fall vs. low-fall vs. plateau vs. low-rise vs. high-rise) and Syllable structure

The *d'* (Tanner & Swets, 1954) was calculated to assess the discrimination sensitivity threshold. Student *t* tests on the *d'* computed for each group show that the discrimination sensitivity threshold does not differ between dyslexic children (*M* = 1.94, *SD* = 0.12), chronological age-matched controls (*M* = 2.18, *SD* = 0.18) and reading level-matched controls (*M* = 1.92, *SD* = 0.27), *ps* > .1. No children had a *d'* = 0 ± 5% (i.e., random responses). The *β*, which estimates the criterion decision, did not differ between children, *ps* > .1. Response times and response accuracy were correlated in dyslexic children, *r* = -.68, *t*(4) = - 3.30, *p* < .006, in chronological age-matched controls, *r* = -.73, *t*(4) = -4.02, *p* < .001, and in

C1C2 clusters and 79.8 ms (*SD* = 11.2) for the vowel /u/.

**5.1.3 Procedure** 

**5.2 Results** 

Table 2. Monosyllabic pseudowords used as a function of sonority profiles.

software automatically recorded response times and response accuracy.

(monosyllabic vs. disyllabic) as within-subject factors.

reading level-matched controls, *r* = -.72, *t*(4) = -3.88, *p* < .008.

were assessed prior to the experiment. Student *t* tests confirmed that verbal and performance IQs significantly differed between dyslexics and chronological age-matched controls, *t*(8) = -3.96, *p* < .005, *t*(8) = 3.10, *p* < .02 respectively; they also differed on reading level, *t*(8) = 9.09, *p* < .0001, but did not differ on chronological age, *p* > .1. Chronological age significantly differed between dyslexic children and reading level-matched controls, *t*(8) = 8.71, *p* < .0001; neither reading level nor verbal and performance IQs significantly differed, *p* > .1.Chronological age as well as reading level and verbal IQ significantly differed between chronological age-matched and reading level-matched controls, *t*(8) = 8.92, *p* < .0001, *t*(8) = 10.56, *p* < .0001, *t*(8) = 2.33, *p* < .05, respectively. Difference was marginally significant for the performance IQ, *t*(8) = 2.01, *p* < .08. Our research was approved by the Regional School Management Office. Profiles are presented in Table 13.


Table 1. Chronological and reading level ages, range, verbal and performance IQs for dyslexic children, chronological age-matched, and reading level-matched controls.

#### **5.1.2 Stimuli**

Forty stimuli were selected. They were twenty monosyllabic C1C2VC3 pseudowords and their disyllabic C1uC2VC3 counterparts, which shared their VC3 rhyme (i.e., /al/) but differed on the structure of their C1C2 clusters (Table 2). Onset clusters were unattested in French. I subdivided them into five sonority profiles (SPs) as follows: high-fall (e.g., /ʁbal/), low-fall (e.g., /fkal/), plateau (e.g., /pkal/), low-rise (e.g., /kfal/), and high-rise (e.g., /zʁal/). Onset cluster markedness progresses from high-fall SPs (the most marked, the grammatically worst ill-formed) to high-rise SPs (the least marked, the grammatically most well-formed). Each SP contained four different C1C2 clusters, repeated eight times within each SP; overall, there were 4 C1C2 x 5 SPs x 8 repetitions x 2 conditions (mono- and disyllabic pseudowords) = 320 stimuli. To exclude some possible phonological biases such as compensation for assimilation or coarticulation, I did not include homorganic consonants (i.e., consonants that share the same place of articulation) and consonants that differ in voicing within C1C2 onset clusters. However, C1 and C2 could differ in mode of articulation. Disyllabic C1uC2VC3 counterparts were recorded by a female native speaker of French. All sounds were digitally recorded with a Sennheiser e865s microphone through a Tascam US-144MK II external audio interface, sampled at a 44 kHz rate, converted with a 16-bit resolution, and bandpass filtered (0 Hz to 5,000 Hz). C1u first syllable in disyllabic pseudowords systematically carried stress. Monosyllabic C1C2VC3 pseudowords were

<sup>3</sup> Note: *N*: number of participants; chronological and reading level ages are in months; ranges are years, months; standard deviations within parentheses; significant difference with dyslexic children: \*\*\* *p* < .0001, \*\* *p* < .005, \* *p* < .02; Reading level as determined by the Alouette test (Lefavrais, 1967); PIQ as measured by Raven's Progressive Matrices for French children (PM 38; Raven, 1998); VIQ as measured by WISC-III for French children (Wechsler, 1996).

obtained by splicing out step-by-step the vowel /u/ with Praat software (Boersma & Weenink, 2011). Visual and auditory inspection of the waveforms minimized the /u/ coarticulation-based traces in the C1 and C2. Mean duration was 197.3 ms (*SD* = 16.1) for the C1C2 clusters and 79.8 ms (*SD* = 11.2) for the vowel /u/.


Table 2. Monosyllabic pseudowords used as a function of sonority profiles.

#### **5.1.3 Procedure**

52 Dyslexia – A Comprehensive and International Approach

were assessed prior to the experiment. Student *t* tests confirmed that verbal and performance IQs significantly differed between dyslexics and chronological age-matched controls, *t*(8) = -3.96, *p* < .005, *t*(8) = 3.10, *p* < .02 respectively; they also differed on reading level, *t*(8) = 9.09, *p* < .0001, but did not differ on chronological age, *p* > .1. Chronological age significantly differed between dyslexic children and reading level-matched controls, *t*(8) = 8.71, *p* < .0001; neither reading level nor verbal and performance IQs significantly differed, *p* > .1.Chronological age as well as reading level and verbal IQ significantly differed between chronological age-matched and reading level-matched controls, *t*(8) = 8.92, *p* < .0001, *t*(8) = 10.56, *p* < .0001, *t*(8) = 2.33, *p* < .05, respectively. Difference was marginally significant for the performance IQ, *t*(8) = 2.01, *p* < .08. Our research was approved by the Regional School

Table 1. Chronological and reading level ages, range, verbal and performance IQs for dyslexic children, chronological age-matched, and reading level-matched controls.

Forty stimuli were selected. They were twenty monosyllabic C1C2VC3 pseudowords and their disyllabic C1uC2VC3 counterparts, which shared their VC3 rhyme (i.e., /al/) but differed on the structure of their C1C2 clusters (Table 2). Onset clusters were unattested in French. I subdivided them into five sonority profiles (SPs) as follows: high-fall (e.g., /ʁbal/), low-fall (e.g., /fkal/), plateau (e.g., /pkal/), low-rise (e.g., /kfal/), and high-rise (e.g., /zʁal/). Onset cluster markedness progresses from high-fall SPs (the most marked, the grammatically worst ill-formed) to high-rise SPs (the least marked, the grammatically most well-formed). Each SP contained four different C1C2 clusters, repeated eight times within each SP; overall, there were 4 C1C2 x 5 SPs x 8 repetitions x 2 conditions (mono- and disyllabic pseudowords) = 320 stimuli. To exclude some possible phonological biases such as compensation for assimilation or coarticulation, I did not include homorganic consonants (i.e., consonants that share the same place of articulation) and consonants that differ in voicing within C1C2 onset clusters. However, C1 and C2 could differ in mode of articulation. Disyllabic C1uC2VC3 counterparts were recorded by a female native speaker of French. All sounds were digitally recorded with a Sennheiser e865s microphone through a Tascam US-144MK II external audio interface, sampled at a 44 kHz rate, converted with a 16-bit resolution, and bandpass filtered (0 Hz to 5,000 Hz). C1u first syllable in disyllabic pseudowords systematically carried stress. Monosyllabic C1C2VC3 pseudowords were

3 Note: *N*: number of participants; chronological and reading level ages are in months; ranges are years, months; standard deviations within parentheses; significant difference with dyslexic children: \*\*\* *p* < .0001, \*\* *p* < .005, \* *p* < .02; Reading level as determined by the Alouette test (Lefavrais, 1967); PIQ as measured by Raven's Progressive Matrices for French children (PM 38; Raven, 1998); VIQ as measured

Management Office. Profiles are presented in Table 13.

**5.1.2 Stimuli** 

by WISC-III for French children (Wechsler, 1996).

This experiment was designed, compiled and run using E-Prime 2.0 Professional software (Schneider, Eschman, & Zuccolotto, 2002) on Sony X-series laptop computers under Windows 7 OS. Children wore Sennheiser HD 25-1 II headphones (16 Hz-22 kHz range, 70 Ω impedance) and were presented pseudowords binaurally at 70 dB SPL. Trials consisted in the presentation of a vertically-centered exclamation mark (i.e., '+') for 500 ms, followed after a 200-ms blank screen by a pseudoword. A 1,000-ms delay separated two consecutive trials. Children were requested to decide as quickly and as accurately as possible whether the pseudoword had one or two syllables (numpad 1 = one syllable, numpad 2 = two syllables). Children were first trained with a practice list of 16 trials with corrective feedback. No feedback was given for the experimental trials. Trials were randomized. The software automatically recorded response times and response accuracy.

#### **5.2 Results**

I report first the results from two 5 x 2 x 3 mixed-design repeated measures ANOVAs with Statistica software by subject (*F*1) and by item (*F*2) on response times and response accuracy (~ 84.1% of the data). ANOVAs were run with Group (dyslexics vs. chronological agematched controls vs. reading level-matched controls) as between-subject factor and Sonority profile (high-fall vs. low-fall vs. plateau vs. low-rise vs. high-rise) and Syllable structure (monosyllabic vs. disyllabic) as within-subject factors.

The *d'* (Tanner & Swets, 1954) was calculated to assess the discrimination sensitivity threshold. Student *t* tests on the *d'* computed for each group show that the discrimination sensitivity threshold does not differ between dyslexic children (*M* = 1.94, *SD* = 0.12), chronological age-matched controls (*M* = 2.18, *SD* = 0.18) and reading level-matched controls (*M* = 1.92, *SD* = 0.27), *ps* > .1. No children had a *d'* = 0 ± 5% (i.e., random responses). The *β*, which estimates the criterion decision, did not differ between children, *ps* > .1. Response times and response accuracy were correlated in dyslexic children, *r* = -.68, *t*(4) = - 3.30, *p* < .006, in chronological age-matched controls, *r* = -.73, *t*(4) = -4.02, *p* < .001, and in reading level-matched controls, *r* = -.72, *t*(4) = -3.88, *p* < .008.

Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific? 55

To ensure that the perceptual confusion response patterns are not due to coarticulationbased artifacts relative to traces of spliced /u/ from the C1uC2 clusters, I examined the nature of the misperception *a posteriori*. Dyslexic children as well as controls were posttested. Children were asked to report whether or not they heard a vowel, and if so, which one, within monosyllabic pseudowords (n = 160). The task was quite similar, except that for each error, a visual feedback was displayed and children were therefore asked to press on the vowel they thought they heard (i.e., /a/, /i/, /u/, /o/, /e/, /ɛ/, /y/, /ə/, or not a vowel). Response patterns showed that when French dyslexic children misperceived the C1C2 clusters, they reported an epenthetic /ə/ (*M* = 80.0 ± 4.4) more frequently than other vowels (*M* = 3.5 ± 4.7), *t*(4) = 24.69, p <.0001). Response patterns were similar in chronological agematched controls (*M* = 83.9 ± 5.5 vs. *M* = 5.8 ± 2.9, *t*(4) = 18.37, *p* < .0001) and in reading level-

Fig. 3. Mean response accuracy (in %) to the Sonority profile x Syllable structure interaction for the dyslexic children (DY), chronological age-matched controls (CA) and reading level-

As in the Berent et al.'s studies (2007; 2008), I submitted children' response accuracy to the C1C2 clusters to a linear hierarchically-forced stepwise regression analysis4. I first forced in the C1C2 cluster length (in ms); then, I forced in the statistical properties of biphones and triphones respectively (I considered C1VC2 triphones with a vowel /ə/ that was the most reported epenthetic vowel in children), the bigram frequency (Peereman, Lété, & Sprenger-Charolles, 2007), and the phonotactic transitional probabilities (Crouzet, 2000). The analysis revealed that markedness, which was entered last, accounts for significant unique variance in dyslexic children (Adjusted R2 = .276, *p* < .0001, *β* = .62),, chronological age-matched

4 I used the statistical properties extracted from an oral frequency-based database in French (Gendrot,

matched controls (RL).

2011).

matched controls (*M* = 81.7 ± 6.2 vs. *M* = 2.6 ± 3.8, *t*(4) = 27.00, *p* < .0001).

The analysis revealed a significant main effect of Group in response times only, *F*1(4, 48) = 40.09, *p* < .0001, η<sup>2</sup> p = 0.62, *F*2 (4, 310) = 31.21, *p* < .0001, η<sup>2</sup> p = 0.36; indicating that dyslexic children (1,759 ms) were systematically slower to respond compared to chronological agematched controls (1,213 ms) and reading level-matched controls (1,509 ms), *t*(8) = 29.11, *p* < .0001, *t*(8) = 13.46, *p* < .001, respectively.

The Sonority profile x Syllable structure interaction was significant in response times (Fig. 2), *F*1(4, 48) = 40.09, *p* < .0001, η<sup>2</sup> p = 0.62, *F*2 (4, 310) = 31.21, *p* < .0001, η<sup>2</sup> p = 0.36 and response accuracy (Fig. 3), *F*1 (4, 48) = 32.69, *p* < .0001, η<sup>2</sup> p = 0.73, *F*2(4, 310) = 28.55, *p* < .0001, η<sup>2</sup> p = 0.29. Fisher's LSD post-hoc tests (Bonferroni's adjusted α-level for significance, *p* < .001) revealed that responses to more marked onset clusters with high-fall SPs (e.g., /ʁbal/) were slower and less accurate relative to the less marked onset clusters with plateau SPs (e.g., /pkal/), which in turn, were slower and less accurate than high-rise SPs (e.g., /gmal/). Responses to low-fall SPs (e.g., /fkal/) were slower and less accurate than low-rise SPs (e.g., /kfal/). Responses to disyllabic counterparts of grammatically worst ill-formed onset clusters with high-fall SPs (e.g., /ʁubal/) were faster and more accurate relative to disyllabic counterparts of less marked onset clusters with plateau SPs (e.g., /pukal/), which in turn, were faster and more accurate than high-rise SPs (e.g., /gumal/). Responses to low-fall SPs (e.g., /fukal/) were faster and more accurate than low-rise SPs (e.g., /kufal/).

Neither the Group nor the Syllable structure main effects were significant in response accuracy. The three-way Sonority profile x Syllable structure x Group interaction did not significantly interact in response times, *F*s < 1, *p* > .1 and response accuracy, *F*s < 1, *p* > .1.

Fig. 2. Mean response times (in ms) to the Sonority profile x Syllable structure interaction for the dyslexic children (DY), chronological age-matched controls (CA) and reading levelmatched controls (RL).

The analysis revealed a significant main effect of Group in response times only, *F*1(4, 48) =

children (1,759 ms) were systematically slower to respond compared to chronological agematched controls (1,213 ms) and reading level-matched controls (1,509 ms), *t*(8) = 29.11, *p* <

The Sonority profile x Syllable structure interaction was significant in response times (Fig.

0.29. Fisher's LSD post-hoc tests (Bonferroni's adjusted α-level for significance, *p* < .001) revealed that responses to more marked onset clusters with high-fall SPs (e.g., /ʁbal/) were slower and less accurate relative to the less marked onset clusters with plateau SPs (e.g., /pkal/), which in turn, were slower and less accurate than high-rise SPs (e.g., /gmal/). Responses to low-fall SPs (e.g., /fkal/) were slower and less accurate than low-rise SPs (e.g., /kfal/). Responses to disyllabic counterparts of grammatically worst ill-formed onset clusters with high-fall SPs (e.g., /ʁubal/) were faster and more accurate relative to disyllabic counterparts of less marked onset clusters with plateau SPs (e.g., /pukal/), which in turn, were faster and more accurate than high-rise SPs (e.g., /gumal/). Responses to low-fall SPs

Neither the Group nor the Syllable structure main effects were significant in response accuracy. The three-way Sonority profile x Syllable structure x Group interaction did not significantly interact in response times, *F*s < 1, *p* > .1 and response accuracy, *F*s < 1, *p* > .1.

Fig. 2. Mean response times (in ms) to the Sonority profile x Syllable structure interaction for the dyslexic children (DY), chronological age-matched controls (CA) and reading level-

p = 0.62, *F*2 (4, 310) = 31.21, *p* < .0001, η<sup>2</sup>

p = 0.36; indicating that dyslexic

p = 0.73, *F*2(4, 310) = 28.55, *p* < .0001, η<sup>2</sup>

p = 0.36 and response

p =

p = 0.62, *F*2 (4, 310) = 31.21, *p* < .0001, η<sup>2</sup>

(e.g., /fukal/) were faster and more accurate than low-rise SPs (e.g., /kufal/).

40.09, *p* < .0001, η<sup>2</sup>

.0001, *t*(8) = 13.46, *p* < .001, respectively.

accuracy (Fig. 3), *F*1 (4, 48) = 32.69, *p* < .0001, η<sup>2</sup>

2), *F*1(4, 48) = 40.09, *p* < .0001, η<sup>2</sup>

matched controls (RL).

To ensure that the perceptual confusion response patterns are not due to coarticulationbased artifacts relative to traces of spliced /u/ from the C1uC2 clusters, I examined the nature of the misperception *a posteriori*. Dyslexic children as well as controls were posttested. Children were asked to report whether or not they heard a vowel, and if so, which one, within monosyllabic pseudowords (n = 160). The task was quite similar, except that for each error, a visual feedback was displayed and children were therefore asked to press on the vowel they thought they heard (i.e., /a/, /i/, /u/, /o/, /e/, /ɛ/, /y/, /ə/, or not a vowel). Response patterns showed that when French dyslexic children misperceived the C1C2 clusters, they reported an epenthetic /ə/ (*M* = 80.0 ± 4.4) more frequently than other vowels (*M* = 3.5 ± 4.7), *t*(4) = 24.69, p <.0001). Response patterns were similar in chronological agematched controls (*M* = 83.9 ± 5.5 vs. *M* = 5.8 ± 2.9, *t*(4) = 18.37, *p* < .0001) and in reading levelmatched controls (*M* = 81.7 ± 6.2 vs. *M* = 2.6 ± 3.8, *t*(4) = 27.00, *p* < .0001).

Fig. 3. Mean response accuracy (in %) to the Sonority profile x Syllable structure interaction for the dyslexic children (DY), chronological age-matched controls (CA) and reading levelmatched controls (RL).

As in the Berent et al.'s studies (2007; 2008), I submitted children' response accuracy to the C1C2 clusters to a linear hierarchically-forced stepwise regression analysis4. I first forced in the C1C2 cluster length (in ms); then, I forced in the statistical properties of biphones and triphones respectively (I considered C1VC2 triphones with a vowel /ə/ that was the most reported epenthetic vowel in children), the bigram frequency (Peereman, Lété, & Sprenger-Charolles, 2007), and the phonotactic transitional probabilities (Crouzet, 2000). The analysis revealed that markedness, which was entered last, accounts for significant unique variance in dyslexic children (Adjusted R2 = .276, *p* < .0001, *β* = .62),, chronological age-matched

<sup>4</sup> I used the statistical properties extracted from an oral frequency-based database in French (Gendrot, 2011).

Phonological Restriction Knowledge in Dyslexia: Universal or Language-Specific? 57

well-formed, phonological sequence) and universal phonological representations to avoid a transgression of grammatical well-formedness of phonological sequence. Thus, the children' misperception of marked onset clusters could be attributed to universal phonologicallyconstrained preferences that follow sonority-related markedness constraints. Since sonorityrelated markedness relies on acoustic-phonetic cues that might require efficient abilities to perceive, store and process brief acoustic-phonetic information (e.g., Hayes & Steriade, 2004; for counter-argument on the phonetic basis of sonority, see Clements, 2006), and since dyslexic children are as sensitive as controls to this phonological marker, our results compete to reconsider the degraded, under-specified phonological representation hypothesis to further explore the phonological access deficit hypothesis (e.g., Ramus &

Dyslexic children therefore have intact universal phonological sonority-related sensitivity and efficient language-dependent abilities to underlie both the (mis)perception of phonotactically-illegal clusters and the phonological repair processes, respectively. Further, acoustic-phonetic cues as well as statistical properties do not exhibit straightforward influence, but I do not discard that both contribute to the markedness-related misperception. Further, in our experiment, it remains unresolved whether Peperkamp's position (2007, p. 634-635) is true: "the role of the grammar in phonological perception is not to repair phonologically illegal structure but rather to undo the effect of native phonological processes, and that perceptual repairs take place at a lower, phonetic, processing level". Although I acknowledge that extensive research is important to refine our results, I point out that, as suggested by Ramus & Szenkovits (2008) or Szenkovits et al. (submitted) dyslexics' phonological deficit accommodates with a deficit in storing and accessing the

I thank gratefully the head teachers, teachers, speech and language therapists, parents and children who participated in these experiments. I also thank gratefully Pr. Yasuyuki Taki and Dr. Hiroshi Hashizume from the Dept. of Developmental Cognitive Neuroscience (Tohoku University), Drs. Satoru Yokoyama and Kei Takahashi as well as Pr. Ryuta Kawashima from the Dept. of Functional Brain Imaging (Tohoku University), and Prs. Annie Magnan and Jean Écalle from the Laboratoire d'Étude des Mécanismes Cognitifs (Université Lyon 2) for supporting this study. This work was supported by the Japan Society for the Promotion of Science via a 2-year Postdoctoral Fellowship for Foreign Researcher

Adlard, A. & Hazan,V. (1998). Speech perception abilities in children with developmental dyslexia. *The Quarterly Journal of Experimental Psychology, 51A,* pp. 153-177. Ahissar, M. (2007). Dyslexia and the anchoring-decit hypothesis. *Trends in Cognitive* 

Szenkovits, 2008).

**7. Conclusion** 

phonological representations.

awarded to Norbert Maïonchi-Pino.

*Sciences, 11,* pp. 458-465.

**9. References** 

**8. Acknowledgments** 

controls (Adjusted R2 = .258, *p* < .005, *β* = .55) and reading level-matched controls (Adjusted R2 = .394, *p* < .0001, *β* = .76).

#### **6. Discussion**

As can be seen throughout this chapter, the dyslexics' phonological deficit has unresolved issues. However, the degraded, under-specified phonological representation hypothesis as a failure in the perception of finely-sharped acoustic-phonetic cues appears to be somehow misleading (e.g., Ramus & Szenkovits, 2008). To solve the intricate problem of the nature of the dyslexics' phonological deficit, I tried to assess whether -and how- the phonological representations are difficult to be accessed, either language-specific or universal, in French dyslexic children compared to chronological age-matched and reading level-matched controls.

The results provide major, innovative responses to a twofold debate: about the nature of the phonological deficit in dyslexics and about the universal phonological knowledge on grammatical restrictions. Crucially, I first observed that the (mis)perception of unattested onset clusters relies on universal sonority-related phonological knowledge on grammatical restrictions. Indeed, response patterns indicate a markedness-modulated misperception of monosyllabic pseudowords as disyllabic ones: as markedness increased from high-rise SP to high-fall SP, perceptual confusion was prone to increase. Also, response patterns were reversed to their disyllabic counterparts: as markedness increased, perceptual confusion decreased. Furthermore, there was no speed-accuracy trade-off: as response accuracy increased, response times decreased.

*A posteriori* measures confirmed that monosyllabic pseudowords were not perceptuallyconfused due to coarticulation-based artefacts relative to traces of the spliced vowel /u/: monosyllabic pseudowords are more likely phonologically-repaired with an illusory epenthetic vowel /ə/. Since the vowel /ə/ represents a high-frequency vowel in French, a linear hierarchically-forced stepwise regression analysis discarded a straightforward influence of statistical properties and acoustic-phonetic cues on the misperception and the phonological repair by an illusory epenthetic vowel. Neither the C1C2 cluster length, nor the frequency of biphones and triphones explain our results: sonority-related markedness accounts for significant unique variance.

Surprisingly, Group effects were absent; French dyslexic children were as sensitive as both chronological age-matched and reading level-matched controls to the phonological sonorityrelated markedness of C1C2 onset clusters and, as well as controls, they phonologically repaired unattested marked C1C2 clusters into attested unmarked ones with an epenthetic /ə/ vowel: this is in accordance with recent results of Maïonchi-Pino, Yokoyama, Takahashi, Écalle, Magnan, & Kawashima (2011) in French adult native speakers (in English, also see Berent et al., 2007; 2008). Of interest, dyslexic children did not differ from both control groups on their response accuracy and discrimination sensitivity threshold (*d'*); however, response times were slower. This suggests that dyslexic children have normal, intact universal phonological constraints and robust phonological representations of their native language; they are able to efficiently recode grammatical ill-formed sequences (i.e., to do that, children insert an epenthetic vowel /ə/ that tends to restore an attested, grammatical well-formed, phonological sequence) and universal phonological representations to avoid a transgression of grammatical well-formedness of phonological sequence. Thus, the children' misperception of marked onset clusters could be attributed to universal phonologicallyconstrained preferences that follow sonority-related markedness constraints. Since sonorityrelated markedness relies on acoustic-phonetic cues that might require efficient abilities to perceive, store and process brief acoustic-phonetic information (e.g., Hayes & Steriade, 2004; for counter-argument on the phonetic basis of sonority, see Clements, 2006), and since dyslexic children are as sensitive as controls to this phonological marker, our results compete to reconsider the degraded, under-specified phonological representation hypothesis to further explore the phonological access deficit hypothesis (e.g., Ramus & Szenkovits, 2008).

#### **7. Conclusion**

56 Dyslexia – A Comprehensive and International Approach

controls (Adjusted R2 = .258, *p* < .005, *β* = .55) and reading level-matched controls (Adjusted

As can be seen throughout this chapter, the dyslexics' phonological deficit has unresolved issues. However, the degraded, under-specified phonological representation hypothesis as a failure in the perception of finely-sharped acoustic-phonetic cues appears to be somehow misleading (e.g., Ramus & Szenkovits, 2008). To solve the intricate problem of the nature of the dyslexics' phonological deficit, I tried to assess whether -and how- the phonological representations are difficult to be accessed, either language-specific or universal, in French dyslexic children compared to chronological age-matched and reading level-matched

The results provide major, innovative responses to a twofold debate: about the nature of the phonological deficit in dyslexics and about the universal phonological knowledge on grammatical restrictions. Crucially, I first observed that the (mis)perception of unattested onset clusters relies on universal sonority-related phonological knowledge on grammatical restrictions. Indeed, response patterns indicate a markedness-modulated misperception of monosyllabic pseudowords as disyllabic ones: as markedness increased from high-rise SP to high-fall SP, perceptual confusion was prone to increase. Also, response patterns were reversed to their disyllabic counterparts: as markedness increased, perceptual confusion decreased. Furthermore, there was no speed-accuracy trade-off: as response accuracy

*A posteriori* measures confirmed that monosyllabic pseudowords were not perceptuallyconfused due to coarticulation-based artefacts relative to traces of the spliced vowel /u/: monosyllabic pseudowords are more likely phonologically-repaired with an illusory epenthetic vowel /ə/. Since the vowel /ə/ represents a high-frequency vowel in French, a linear hierarchically-forced stepwise regression analysis discarded a straightforward influence of statistical properties and acoustic-phonetic cues on the misperception and the phonological repair by an illusory epenthetic vowel. Neither the C1C2 cluster length, nor the frequency of biphones and triphones explain our results: sonority-related markedness

Surprisingly, Group effects were absent; French dyslexic children were as sensitive as both chronological age-matched and reading level-matched controls to the phonological sonorityrelated markedness of C1C2 onset clusters and, as well as controls, they phonologically repaired unattested marked C1C2 clusters into attested unmarked ones with an epenthetic /ə/ vowel: this is in accordance with recent results of Maïonchi-Pino, Yokoyama, Takahashi, Écalle, Magnan, & Kawashima (2011) in French adult native speakers (in English, also see Berent et al., 2007; 2008). Of interest, dyslexic children did not differ from both control groups on their response accuracy and discrimination sensitivity threshold (*d'*); however, response times were slower. This suggests that dyslexic children have normal, intact universal phonological constraints and robust phonological representations of their native language; they are able to efficiently recode grammatical ill-formed sequences (i.e., to do that, children insert an epenthetic vowel /ə/ that tends to restore an attested, grammatical

R2 = .394, *p* < .0001, *β* = .76).

increased, response times decreased.

accounts for significant unique variance.

**6. Discussion** 

controls.

Dyslexic children therefore have intact universal phonological sonority-related sensitivity and efficient language-dependent abilities to underlie both the (mis)perception of phonotactically-illegal clusters and the phonological repair processes, respectively. Further, acoustic-phonetic cues as well as statistical properties do not exhibit straightforward influence, but I do not discard that both contribute to the markedness-related misperception. Further, in our experiment, it remains unresolved whether Peperkamp's position (2007, p. 634-635) is true: "the role of the grammar in phonological perception is not to repair phonologically illegal structure but rather to undo the effect of native phonological processes, and that perceptual repairs take place at a lower, phonetic, processing level". Although I acknowledge that extensive research is important to refine our results, I point out that, as suggested by Ramus & Szenkovits (2008) or Szenkovits et al. (submitted) dyslexics' phonological deficit accommodates with a deficit in storing and accessing the phonological representations.

#### **8. Acknowledgments**

I thank gratefully the head teachers, teachers, speech and language therapists, parents and children who participated in these experiments. I also thank gratefully Pr. Yasuyuki Taki and Dr. Hiroshi Hashizume from the Dept. of Developmental Cognitive Neuroscience (Tohoku University), Drs. Satoru Yokoyama and Kei Takahashi as well as Pr. Ryuta Kawashima from the Dept. of Functional Brain Imaging (Tohoku University), and Prs. Annie Magnan and Jean Écalle from the Laboratoire d'Étude des Mécanismes Cognitifs (Université Lyon 2) for supporting this study. This work was supported by the Japan Society for the Promotion of Science via a 2-year Postdoctoral Fellowship for Foreign Researcher awarded to Norbert Maïonchi-Pino.

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**5** 

*France* 

**Antisaccades in Dyslexic Children: Evidence for** 

**Immaturity of Oculomotor Cortical Structures** 

*2Service de Psychopathologie de l'enfant et de l'adolescent. Hôpital Robert Debré, Paris,* 

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Neuropsychological studies have shown an important role of the frontal cortices during performing antisaccades. For instance, Everling and Munoz (2000), and Funahashi et al. (1993) revealed that several frontal structures (frontal eye field, dorsolateral cortex and supplementary eye field) are more activated during antisaccade tasks than during prosaccades (a saccade made towards the peripheral target). Furthermore, Matsuda et al. (2004) reported increased activity in the inferior parietal cortex during antisaccade tasks compared to prosaccades. Interestingly, Ettinger et al. (2008) showed activity in such area during a period preceeding the antisaccade generation, suggesting an inhibitory role of this region. Other studies found out that the parietal cortex (some regions in the intraparietal

**1. Introduction** 

Maria Pia Bucci1, Naziha Nassibi1, Christophe-Loic Gerard2,

Emmanuel Bui-Quoc3 and Magali Seassau4

*3Service OPH, Hôpital Robert Debré, Paris,* 

*4e(ye)BRAIN, Ivry-sur-Seine,* 

*1Laboratoire de Psychologie et Neuropsychologie Cognitives, FRE 3292 CNRS - Université Paris Descartes, Paris,* 


## **Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures**

Maria Pia Bucci1, Naziha Nassibi1, Christophe-Loic Gerard2,

Emmanuel Bui-Quoc3 and Magali Seassau4

*1Laboratoire de Psychologie et Neuropsychologie Cognitives, FRE 3292 CNRS - Université Paris Descartes, Paris, 2Service de Psychopathologie de l'enfant et de l'adolescent. Hôpital Robert Debré, Paris, 3Service OPH, Hôpital Robert Debré, Paris, 4e(ye)BRAIN, Ivry-sur-Seine, France* 

#### **1. Introduction**

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The antisaccade task has been introduced for the first time by Hallet (1978) in order to explore the ability of the brain to control behaviour flexibly. Antisaccades are voluntary saccades during which subjects have to inhibit the movement towards a peripheral visual target. Usually subjects fixate a central fixation point, which is then extinguished and the peripheral target is presented. Subjects are instructed to generate a saccade of the same amplitude to the opposite direction, as quickly and accurately as possible. It is generally assumed that the sudden appearance of the target in an antisaccade task automatically triggers a motor program for a prosaccade in this direction, and that errors occur when certain endogenous processes fail to inhibit or cancel this program (Everling & Fischer, 1998). It is argued that correct antisaccade latencies are increased compared to prosaccade latencies because the application of the inhibitory processes is time consuming (Olk & Kingstone, 2003). Everling and Fischer (1998) argued that antisaccade performance requires two intact subprocesses: 1) the ability to suppress a reflexive saccade towards the target; 2) the ability to generate a voluntary saccade in the opposite direction. In clinical research, increased antisaccade error rates are often interpreted as reflecting failures in inhibitory processing (Crawford, Bennett, Lekwuwa, Shaunak, & Deakin, 2002; Hutton et al., 2008).

Neuropsychological studies have shown an important role of the frontal cortices during performing antisaccades. For instance, Everling and Munoz (2000), and Funahashi et al. (1993) revealed that several frontal structures (frontal eye field, dorsolateral cortex and supplementary eye field) are more activated during antisaccade tasks than during prosaccades (a saccade made towards the peripheral target). Furthermore, Matsuda et al. (2004) reported increased activity in the inferior parietal cortex during antisaccade tasks compared to prosaccades. Interestingly, Ettinger et al. (2008) showed activity in such area during a period preceeding the antisaccade generation, suggesting an inhibitory role of this region. Other studies found out that the parietal cortex (some regions in the intraparietal

Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures 63

this test below 2 standard deviations of normalized values; and a normal mean intelligence quotient, between 85 and 115 (IQ, evaluated with WISC IV). The mean age of the dyslexic children was 11.19 ± 0.2 years, the mean IQ was 100 ± 6 and the mean reading age was 8 ± 1 years. A carefully selected age-matched (29 children, mean age 11.6 ± 0.17) and reading agematched (24 children, mean age 7.8 ± 0.19) groups of non-dyslexic children were selected. These children had to satisfy the following criteria: no known neurological or psychiatric abnormalities, no history of reading difficulty, no visual impairment or difficulty with near vision. For the two groups of non-dyslexic children reading capabilities were in normal range. Both the similitude test of the WISC IV assessing the verbal capability, and the matrix test of the WISC IV assessing the logic capability were performed. Normal range for both tests is 10 ± 3 (Wechsler intelligence scale for children—fourth edition, 2004). The selected reading age-matched group was normal for verbal (11.78 ± 0.8) and for logic (9.97 ± 0.6) capabilities. The selected age-matched group was also normal (10.36 ± 0.4 for verbal and

Both non-dyslexic and dyslexic children underwent an ophthalmologic and orthoptic examination in order to evaluate their visual function (median values shown in Table 1). All children had normal binocular vision (60 sec of arc or better), which was evaluated with the TNO random dot test. Visual acuity was normal (≥20/20) for all children, dyslexic as well as non dyslexic. The near point of convergence was normal for all three groups of children tested (≤ 5 cm). Moreover, an orthoptic evaluation of vergence fusion capability using prisms and Maddox rod was carried out at far and at near distance. At far distance, the divergence and convergence amplitudes were similar in the three groups of children examined. In contrast, at near distance, the divergence and convergence amplitudes were significantly different in the dyslexic group with respect to the other two groups of non dyslexic children. ANOVA showed significant main effects of group, F(2,71) = 6.36, p < 0.003 and of the divergence and convergence amplitudes, F(2,71) = 3.18, p < 0.04., respectively). The LSD test showed that the dyslexic group had significantly smaller value of divergence and convergence amplitudes with respect to the two groups of non-dyslexic children (younger

Finally, phoria (i.e. latent deviation of one eye when the other eye is covered, using the

**D 10-13** 63 3 0 Exo 1 4 10 15 32 **ND 7-9** 45 2 0 Exo 2 4 14\* 16 40\* **ND 10-13** 40 2 0 Exo 2 6 13\* 17 40\* Note: dyslexic children, D 10-13; non-dyslexic children chronological age matched, ND 10-13; and nondyslexic children reading age matched, ND 7-9. Median values of: binocular vision (Stereoacuity test, TNO measured in seconds of arc); near point of convergence, NPC measured in cm; Heterophoria at far and near distance, measured in prism diopters; Exo = exophoria; Vergence fusional amplitudes (divergence and convergence) at far and at near distance, measured in prism diopters. Asterisks indicate that value is significantly different with respect to the group of dyslexic children (p<0.01).

**Phoria Near** 

**Div Far** 

**Div Near**  **Conv Far** 

**Conv Near** 

cover-uncover test) was normal for all three groups of children tested.

**Far** 

Table 1. Clinical characteristic of the three groups of children examined

**TNO NPC Phoria** 

11.89 ± 0.5 for logic).

and older).

sulcus) is responsible for the vector inversion required to generate an antisaccade to the correct location (Clementz et al., 2007; Zhang & Barash, 2000).

Several researchers have focused on the development of the ability to perform antisaccades. For example, as suggested in Luna's exhaustive review (Luna et al., 2008) exhaustive review, the maturity of the cortical structures devoted to eye movement performances is reached at 14-15 years. Consequently, the improvements in antisaccade performance continue during adolescence even though the ability to successfully inhibit a saccade toward a new target is already present at 8 years old (Johnson, 1995).

Moreover, the antisaccade task has also been used as important clinical tool for investigating dysfunction in various neurological and psychiatric disorders (Leigh and Kennard, 2004). Patients with discrete lesions of the dorsolateral cortex and in the frontal eye field have difficulty in performing correctly the antisaccade task (Guitton et al., 1985; Walker et al., 1998; Gaymard et al., 1999; Davidson et al., 1999).

The antisaccade task has been extensively studied in dyslexic children by the Fischer's group. Indeed, Biscaldi et al. (2000) and Fischer & Hartnegg (2000a) compared the performance in an antisaccade task between dyslexic children and non-dyslexic children of similar age. These authors reported an increased number of directional errors and several saccades being missed in dyslexic children. Furthermore, Fischer and Hartnegg (2000b) showed that this poorer performance in dyslexic children could be improved by training, leading to obtain a performance similar to that reported in non-dyslexic children. Therefore, although some evidence exists suggesting impaired inhibitory processing in dyslexic children, such a deficit can be overcome by training.

Based on all these findings we aimed to explore whether the poor antisaccade performance reported in dyslexic children could be a consequence of immaturity of cortical structures responsible of triggering and execution of saccadic eye movements rather than a congenital deficit of these areas. Indeed, the fact that dyslexic children are able to improve antisaccade performance with training as shown by Fischer and Hartnegg (2000b) is in line with the hypothesis of a delayed maturation of the oculomotor system in such type of subjects (Bucci et al., 2008).

In the present study we compared antisaccade performance in three different groups of children: (i) dyslexic children; (ii) age-matched non-dyslexic children; (iii) reading agematched non-dyslexic children.

#### **2. Materials and methods**

#### **2.1 Participants**

Twenty-one dyslexic children were recruited from the pediatric hospital where they were referred for a complete evaluation of their dyslexia state with an extensive examination including neurological/psychological and phonological capabilities. For each child the time required to read a text, its comprehension, and the capacity of reading word/pseudowords was evaluated by using the L2MA battery (Chevrie-Muller et al., 1997). This is a standard test developed by the Applied Psychology Centre of Paris (Centre de Psychologie Appliquée de Paris), and is used everywhere in France. Inclusion criteria for dyslexic were: scores on

sulcus) is responsible for the vector inversion required to generate an antisaccade to the

Several researchers have focused on the development of the ability to perform antisaccades. For example, as suggested in Luna's exhaustive review (Luna et al., 2008) exhaustive review, the maturity of the cortical structures devoted to eye movement performances is reached at 14-15 years. Consequently, the improvements in antisaccade performance continue during adolescence even though the ability to successfully inhibit a saccade toward a new target is

Moreover, the antisaccade task has also been used as important clinical tool for investigating dysfunction in various neurological and psychiatric disorders (Leigh and Kennard, 2004). Patients with discrete lesions of the dorsolateral cortex and in the frontal eye field have difficulty in performing correctly the antisaccade task (Guitton et al., 1985; Walker et al.,

The antisaccade task has been extensively studied in dyslexic children by the Fischer's group. Indeed, Biscaldi et al. (2000) and Fischer & Hartnegg (2000a) compared the performance in an antisaccade task between dyslexic children and non-dyslexic children of similar age. These authors reported an increased number of directional errors and several saccades being missed in dyslexic children. Furthermore, Fischer and Hartnegg (2000b) showed that this poorer performance in dyslexic children could be improved by training, leading to obtain a performance similar to that reported in non-dyslexic children. Therefore, although some evidence exists suggesting impaired inhibitory processing in dyslexic

Based on all these findings we aimed to explore whether the poor antisaccade performance reported in dyslexic children could be a consequence of immaturity of cortical structures responsible of triggering and execution of saccadic eye movements rather than a congenital deficit of these areas. Indeed, the fact that dyslexic children are able to improve antisaccade performance with training as shown by Fischer and Hartnegg (2000b) is in line with the hypothesis of a delayed maturation of the oculomotor system in such type of subjects (Bucci

In the present study we compared antisaccade performance in three different groups of children: (i) dyslexic children; (ii) age-matched non-dyslexic children; (iii) reading age-

Twenty-one dyslexic children were recruited from the pediatric hospital where they were referred for a complete evaluation of their dyslexia state with an extensive examination including neurological/psychological and phonological capabilities. For each child the time required to read a text, its comprehension, and the capacity of reading word/pseudowords was evaluated by using the L2MA battery (Chevrie-Muller et al., 1997). This is a standard test developed by the Applied Psychology Centre of Paris (Centre de Psychologie Appliquée de Paris), and is used everywhere in France. Inclusion criteria for dyslexic were: scores on

correct location (Clementz et al., 2007; Zhang & Barash, 2000).

already present at 8 years old (Johnson, 1995).

1998; Gaymard et al., 1999; Davidson et al., 1999).

children, such a deficit can be overcome by training.

et al., 2008).

**2.1 Participants** 

matched non-dyslexic children.

**2. Materials and methods** 

this test below 2 standard deviations of normalized values; and a normal mean intelligence quotient, between 85 and 115 (IQ, evaluated with WISC IV). The mean age of the dyslexic children was 11.19 ± 0.2 years, the mean IQ was 100 ± 6 and the mean reading age was 8 ± 1 years. A carefully selected age-matched (29 children, mean age 11.6 ± 0.17) and reading agematched (24 children, mean age 7.8 ± 0.19) groups of non-dyslexic children were selected. These children had to satisfy the following criteria: no known neurological or psychiatric abnormalities, no history of reading difficulty, no visual impairment or difficulty with near vision. For the two groups of non-dyslexic children reading capabilities were in normal range. Both the similitude test of the WISC IV assessing the verbal capability, and the matrix test of the WISC IV assessing the logic capability were performed. Normal range for both tests is 10 ± 3 (Wechsler intelligence scale for children—fourth edition, 2004). The selected reading age-matched group was normal for verbal (11.78 ± 0.8) and for logic (9.97 ± 0.6) capabilities. The selected age-matched group was also normal (10.36 ± 0.4 for verbal and 11.89 ± 0.5 for logic).

Both non-dyslexic and dyslexic children underwent an ophthalmologic and orthoptic examination in order to evaluate their visual function (median values shown in Table 1). All children had normal binocular vision (60 sec of arc or better), which was evaluated with the TNO random dot test. Visual acuity was normal (≥20/20) for all children, dyslexic as well as non dyslexic. The near point of convergence was normal for all three groups of children tested (≤ 5 cm). Moreover, an orthoptic evaluation of vergence fusion capability using prisms and Maddox rod was carried out at far and at near distance. At far distance, the divergence and convergence amplitudes were similar in the three groups of children examined. In contrast, at near distance, the divergence and convergence amplitudes were significantly different in the dyslexic group with respect to the other two groups of non dyslexic children. ANOVA showed significant main effects of group, F(2,71) = 6.36, p < 0.003 and of the divergence and convergence amplitudes, F(2,71) = 3.18, p < 0.04., respectively). The LSD test showed that the dyslexic group had significantly smaller value of divergence and convergence amplitudes with respect to the two groups of non-dyslexic children (younger and older).


Finally, phoria (i.e. latent deviation of one eye when the other eye is covered, using the cover-uncover test) was normal for all three groups of children tested.

Note: dyslexic children, D 10-13; non-dyslexic children chronological age matched, ND 10-13; and nondyslexic children reading age matched, ND 7-9. Median values of: binocular vision (Stereoacuity test, TNO measured in seconds of arc); near point of convergence, NPC measured in cm; Heterophoria at far and near distance, measured in prism diopters; Exo = exophoria; Vergence fusional amplitudes (divergence and convergence) at far and at near distance, measured in prism diopters. Asterisks indicate that value is significantly different with respect to the group of dyslexic children (p<0.01).

Table 1. Clinical characteristic of the three groups of children examined

Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures 65

out at the beginning of eye movements recordings. During the calibration procedure, children were asked to fixate a grid of 13 points (diameter 0.5 deg) mapping the screen. Each calibration point required a fixation of 250 ms to be validated. A polynomial function with five parameters was used to fit the calibration data and to determine the visual angles. After the calibration procedure, the antisaccade task was presented to the child. Duration of the task was kept short (lasting a couple of minutes) allowing an accurate evaluation of eye

Fig. 2. Mobile Eyebrain Tracker (Mobile EBT®) used to record eye movements from both

The software MeyeAnalysis (provided with the eye tracker) was used to extract saccadic eye movements from the data. It determines automatically the onset and the end of each saccade. All detected saccades were verified afterwards by the investigator and

The latency and the gain (saccade amplitude/mirror target amplitude) of correct responses and of wrong responses, as well as the percentage of correct antisaccade responses were analyzed in the three different groups of children. Saccades with latencies inferior to 100 ms

Statistical analysis was performed by a three-way ANOVAs using the three groups of children (dyslexics and non-dyslexics, chronological and reading-age matched) as inter-

The ANOVA showed a main effect of age (F(2,71)=130.9, p<0.001). Post hoc comparisons showed that reading age matched non-dyslexic children (ND 7-9) were significantly younger than the two other groups (p<0.001). There was no age difference between the group of dyslexic children (D 10-13) and the group of chronological age-matched non

movement recordings.

eyes in children.

**2.5 Data analysis** 

subject factor.

**3. Results** 

corrected/discarded if necessary.

were counted but not included in the analysis.

dyslexic children (ND 10-13) (p=0.22).

The investigation adhered to the principles of the Declaration of Helsinki and was approved by our Institutional Human Experimentation Committee. Informed consent was obtained from the children's parents after explaining the procedure for the experiment to them.

#### **2.2 Oculomotor paradigm**

Stimuli were presented on a PC screen of 22″, its resolution was 1920×1080 and the refresh rate was 60 Hz. The stimulus consisted in a red filled circle subtending a visual angle of 0.5 deg. The trial consisted of a target positioned at the center of the screen for a variable delay between 2000 and 3500 ms. The central target disappeared and after a period of 200 ms (= gap period), a lateral target (green filled circle) appeared at 22.8 degrees, randomly to the left or to the right of the center, and stayed on for 1000 ms. After this duration, the central fixation target appeared again, signalling the beginning of the next trial as shown in Figure 1. The lateral target appeared randomly to the left or right and each direction was presented an equal number of times (i.e., 15 each). Children were instructed to look at the central fixation point, then to trigger a saccade as soon as possible in the opposite direction and symmetrically to the lateral target. Thus, when the target moved to the right, the child had to look at the same distance to the left side. When the target returned to the center, the child was instructed to follow it back to the center. An initial training block of trials was given to ensure that the instructions were understood.

Note: When the green target appears, the child has to make a saccade to it mirror position as quickly as possible. The duration of each trial was between 3200 and 4700 ms.

Fig. 1. Schematic trial of the antisaccade task.

#### **2.3 Eye movements recording**

Eye movements were recorded with the Mobile Eyebrain Tracker (Mobile EBT**®**, e(ye)BRAIN, www.eye-brain.com), an eye-tracking device CE marked for medical purpose (see Figure 2). The Mobile EBT® benefits from cameras that capture the movements of each eye independently. Recording frequency was set up to 300 Hz.

#### **2.4 Procedure**

Children were seated in a chair in a dark room with the head leaning on a forehead and chin support; viewing was binocular; the viewing distance was 58 cm. Calibration was carried out at the beginning of eye movements recordings. During the calibration procedure, children were asked to fixate a grid of 13 points (diameter 0.5 deg) mapping the screen. Each calibration point required a fixation of 250 ms to be validated. A polynomial function with five parameters was used to fit the calibration data and to determine the visual angles. After the calibration procedure, the antisaccade task was presented to the child. Duration of the task was kept short (lasting a couple of minutes) allowing an accurate evaluation of eye movement recordings.

Fig. 2. Mobile Eyebrain Tracker (Mobile EBT®) used to record eye movements from both eyes in children.

#### **2.5 Data analysis**

64 Dyslexia – A Comprehensive and International Approach

The investigation adhered to the principles of the Declaration of Helsinki and was approved by our Institutional Human Experimentation Committee. Informed consent was obtained from the children's parents after explaining the procedure for the experiment to them.

Stimuli were presented on a PC screen of 22″, its resolution was 1920×1080 and the refresh rate was 60 Hz. The stimulus consisted in a red filled circle subtending a visual angle of 0.5 deg. The trial consisted of a target positioned at the center of the screen for a variable delay between 2000 and 3500 ms. The central target disappeared and after a period of 200 ms (= gap period), a lateral target (green filled circle) appeared at 22.8 degrees, randomly to the left or to the right of the center, and stayed on for 1000 ms. After this duration, the central fixation target appeared again, signalling the beginning of the next trial as shown in Figure 1. The lateral target appeared randomly to the left or right and each direction was presented an equal number of times (i.e., 15 each). Children were instructed to look at the central fixation point, then to trigger a saccade as soon as possible in the opposite direction and symmetrically to the lateral target. Thus, when the target moved to the right, the child had to look at the same distance to the left side. When the target returned to the center, the child was instructed to follow it back to the center. An initial training block of trials was given to

Note: When the green target appears, the child has to make a saccade to it mirror position as quickly as

200 ms

2000-3500 ms Time = 3200-4700 ms

1000 ms

Eye movements were recorded with the Mobile Eyebrain Tracker (Mobile EBT**®**, e(ye)BRAIN, www.eye-brain.com), an eye-tracking device CE marked for medical purpose (see Figure 2). The Mobile EBT® benefits from cameras that capture the movements of each

Children were seated in a chair in a dark room with the head leaning on a forehead and chin support; viewing was binocular; the viewing distance was 58 cm. Calibration was carried

**2.2 Oculomotor paradigm** 

ensure that the instructions were understood.

possible. The duration of each trial was between 3200 and 4700 ms.

eye independently. Recording frequency was set up to 300 Hz.

Fig. 1. Schematic trial of the antisaccade task.

**2.3 Eye movements recording** 

**2.4 Procedure** 

The software MeyeAnalysis (provided with the eye tracker) was used to extract saccadic eye movements from the data. It determines automatically the onset and the end of each saccade. All detected saccades were verified afterwards by the investigator and corrected/discarded if necessary.

The latency and the gain (saccade amplitude/mirror target amplitude) of correct responses and of wrong responses, as well as the percentage of correct antisaccade responses were analyzed in the three different groups of children. Saccades with latencies inferior to 100 ms were counted but not included in the analysis.

Statistical analysis was performed by a three-way ANOVAs using the three groups of children (dyslexics and non-dyslexics, chronological and reading-age matched) as intersubject factor.

#### **3. Results**

The ANOVA showed a main effect of age (F(2,71)=130.9, p<0.001). Post hoc comparisons showed that reading age matched non-dyslexic children (ND 7-9) were significantly younger than the two other groups (p<0.001). There was no age difference between the group of dyslexic children (D 10-13) and the group of chronological age-matched non dyslexic children (ND 10-13) (p=0.22).

Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures 67

Fig. 4. Mean latency of wrong prosaccades (towards the target) for dyslexic children 10-13 years old (D 10-13) and non dyslexic children 7-9 years (ND 7-9) and 10-13 years old (ND 10-

Fig. 5. Gain (amplitude of eye movements/amplitude of the attended position target) for antisaccades and wrong prosaccades for dyslexic children 10-13 years old (D 10-13) and non

dyslexic children (younger and older, 7-9 (ND 7-9) and 10-13 years old (ND 10-13),

Note: Vertical lines indicate standard error.

Note: Vertical lines indicate standard error.

respectively).

13).

Figure 3 shows the mean latency of antisaccades for each group of children examined (dyslexic children 10-13 years (D 10-13), non dyslexic children, 7-9 (ND 7-9), and 10-13 years old (ND 10-13) respectively).

The mean latency value for correct antisaccades was 337 ± 14.7 ms for the group of dyslexic children and 353 ± 14.0 ms and 282 ± 12.5 ms for the group of younger and older non dyslexic children respectively.

Note: Vertical lines indicate standard error. \*\*\* = p<0.01.

Fig. 3. Mean latency of antisaccades for dyslexic children 10-13 years old (D 10-13) and non dyslexic children 7-9 years old (ND 7-9) and 10-13 years old (ND 10-13), respectively.

The ANOVA showed a significant main effect of group, F(2,71) = 8.18, p<0.0006 on the latency of antisaccades. Post hoc comparison showed that the latency of antisaccades of the older group of non-dyslexic children was significant shorter with respect to the group of dyslexic children (p<0.01) and to the younger group of non dyslexics (p<0.0001). The latency of dyslexics was similar to that of non-dyslexic reading age matched children (ND 7-9) (p=0.73).

The mean latency value measured for saccades in the wrong direction (prosaccades towards the target) is showed in Figure 4. The mean value was 196 ± 10.2 ms for the group of dyslexic children and 182 ± 9.5 ms and 175 ± 8.8 ms for the group of younger and older non dyslexic children. The ANOVA showed no significant main effect of group (F(2,71) = 1.18, p=0.31).

For each group of children tested we counted also the frequency of anticipatory saccades (latency < 100 ms). The ANOVA did not show group effect (F(2,71)=1.60, p=0.20). Dyslexic children (D 10-13) made 5.7 ± 1.4 % of anticipatory saccades; while reading age matched (ND 7-9) and chronological age matched non-dyslexic children (ND 10-13) made 3.8 ± 1.3 and 2.4 ± 1.2 % of anticipatory saccades, respectively.

In Figure 5 the gain of correct and wrong antisaccade trials are shown for the different groups of children. The ANOVA revealed that a main effect of group was approaching significant for the gain of the antisaccades (F(2,71) = 2.97, p<0.057) but this was not significant for the wrong prosaccades (F(2,86) = 0.72, p=0.48).

Note: Vertical lines indicate standard error.

66 Dyslexia – A Comprehensive and International Approach

Figure 3 shows the mean latency of antisaccades for each group of children examined (dyslexic children 10-13 years (D 10-13), non dyslexic children, 7-9 (ND 7-9), and 10-13 years

The mean latency value for correct antisaccades was 337 ± 14.7 ms for the group of dyslexic children and 353 ± 14.0 ms and 282 ± 12.5 ms for the group of younger and older non

\*\*\*

Fig. 3. Mean latency of antisaccades for dyslexic children 10-13 years old (D 10-13) and non dyslexic children 7-9 years old (ND 7-9) and 10-13 years old (ND 10-13), respectively.

The ANOVA showed a significant main effect of group, F(2,71) = 8.18, p<0.0006 on the latency of antisaccades. Post hoc comparison showed that the latency of antisaccades of the older group of non-dyslexic children was significant shorter with respect to the group of dyslexic children (p<0.01) and to the younger group of non dyslexics (p<0.0001). The latency of dyslexics was similar to that of non-dyslexic reading age matched children (ND 7-9)

The mean latency value measured for saccades in the wrong direction (prosaccades towards the target) is showed in Figure 4. The mean value was 196 ± 10.2 ms for the group of dyslexic children and 182 ± 9.5 ms and 175 ± 8.8 ms for the group of younger and older non dyslexic children. The ANOVA showed no significant main effect of group (F(2,71) = 1.18, p=0.31).

For each group of children tested we counted also the frequency of anticipatory saccades (latency < 100 ms). The ANOVA did not show group effect (F(2,71)=1.60, p=0.20). Dyslexic children (D 10-13) made 5.7 ± 1.4 % of anticipatory saccades; while reading age matched (ND 7-9) and chronological age matched non-dyslexic children (ND 10-13) made 3.8 ± 1.3

In Figure 5 the gain of correct and wrong antisaccade trials are shown for the different groups of children. The ANOVA revealed that a main effect of group was approaching significant for the gain of the antisaccades (F(2,71) = 2.97, p<0.057) but this was not significant

old (ND 10-13) respectively).

dyslexic children respectively.

(p=0.73).

Note: Vertical lines indicate standard error. \*\*\* = p<0.01.

and 2.4 ± 1.2 % of anticipatory saccades, respectively.

for the wrong prosaccades (F(2,86) = 0.72, p=0.48).

Fig. 4. Mean latency of wrong prosaccades (towards the target) for dyslexic children 10-13 years old (D 10-13) and non dyslexic children 7-9 years (ND 7-9) and 10-13 years old (ND 10- 13).

Fig. 5. Gain (amplitude of eye movements/amplitude of the attended position target) for antisaccades and wrong prosaccades for dyslexic children 10-13 years old (D 10-13) and non dyslexic children (younger and older, 7-9 (ND 7-9) and 10-13 years old (ND 10-13), respectively).

Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures 69

is well known, particularly in the case of children, that latency value depends on the subject's attention and motivation (Clark, 1999). In the present study child had to perform an antisaccade task and the latency here reported for prosaccades is due to a wrong response. Note that a similar finding has been also reported from the study of Munoz et al.

The new important finding of the present study comes from the comparison between dyslexic children with reading age matched non-dyslexic children. Indeed, the oculomotor behavior of the group of dyslexic children 10-13 years old was similar to that observed in the group of reading age matched non-dyslexic children (7-9 years old). Both the latency values of correct antisaccades and the error rate in the antisaccade task of dyslexic children 10-13 years old were similar to those found in reading age matched non dyslexic children (7-9

During saccade latency, it is assumed that several processes occur such as the shift of the visual attention to the new stimulus, the disengagement of oculomotor fixation, and the computation of the new parameters (Fischer & Ramsperger, 1984; Findlay & Walker, 1999). These processes involve different cortical and sub-cortical areas (see Leigh & Zee, 2006 for a full review). The longer saccade latency has frequently been attributed to an underdeveloped related cortex, and some investigations have also suggested that increased latency of saccades is related to difficulty in controlling visual fixation (Munoz et al., 1998). To perform an antisaccade it is necessary to first inhibit the reflexive response towards the stimulus, and then to prepare a voluntary saccade in the opposite direction (antisaccade). Klein (2001), and Klein and Foerster (2001) reported that the capability to inhibit this type of saccade as well as the circuitry controlling cognitive processes is present as early as at 6 years old. They suggested that what is immature in young children is the capability to use such cognitive facilities, leading to a partially correct antisaccade response but to an overall

Malone and Iacono (2002) hypothesized that although young children have adequate working memory capability to perform correctly on the antisaccade task, they might not be capable of maintaining these instructions continuously throughout the course of the experiment. This may explain why young children in the current study showed long

On the other hand, it is also well known that the parietal cortex, the frontal eye field, the supplementary eye fields and the prefrontal cortex play important roles in antisaccade performance (Luna et al., 2008; McDowell et al., 2008). Further, the inferior parietal cortex has been suggested to be important for the inhibitory period preceding an antisaccade movement (Ettinger et al., 2008) and regions in the intraparietal sulcus (within parietal cortex) could be responsible for generating a correct antisaccade response (Clementz et al.,

Based on all the available evidences, we postulate the hypothesis that in dyslexic children the delayed maturation of all these structures could lead to longer latencies and increased error rate in the antisaccade task, similar to those reported in reading age matched non-

(1998).

years old).

impaired general performance for this task.

2007; Nyffeler et al., 2007).

dyslexic children.

latencies and a high error rate in the antisaccade task.

The mean error rate was also examined (see Figure 6). The mean error rate was 50.8 ± 4.4 % for the group of dyslexic children and 63.3 ± 4.2 % and 30.3 ± 3.8% respectively for the group of younger and older non dyslexic children.

Note: Vertical lines indicate standard error. \*\*\* = p<.0003.

Fig. 6. Mean error rate in antisaccades for dyslexic children 10-13 years old (D 10-13) and non dyslexic children (younger and older, 7-9 (ND 7-9) and 10-13 years old (ND 10-13), respectively).

The ANOVA on error rate showed a significant main effect of group, F(2,86) = 17.88, p<0.0001. Post hoc comparison showed that the error rate for the older group of non-dyslexic children was significantly lower with respect to the other groups of children: p<0.003 for the dyslexics and p<0.0001 for the younger non dyslexic children. There was no difference between the non-dyslexic younger group and the dyslexic group (p=0.10).

#### **4. Discussion**

The present study showed first that dyslexic children performed the antisaccade task differently to chronological age matched non-dyslexic children: the latency values of correct antisaccades were longer; furthermore the error rate for dyslexic children was significantly higher compared to that of non dyslexic children of similar age. Secondly, this study showed that in non-dyslexic children the performance in the antisaccade task improved with age.

Both results lend support to the previous studies conducted by Fischer's group with dyslexic children (Biscaldi et al., 2000; Fischer & Hartnegg, 2000a) and also other studies with normal children conducted by Fukushima et al. (2000) and by Irving et al. (2009). Note also that in this study the mean latency values of wrong prosaccades were similar in all three groups of children tested. This finding is only apparently in contrast with developmental evidences showing that latency of saccades is age dependent (see Leigh & Zee, 2006 for review). Indeed, in all developmental studies exploring latency of saccades, children had to saccades as quickly as possible to the target (by making a prosaccade) and it

The mean error rate was also examined (see Figure 6). The mean error rate was 50.8 ± 4.4 % for the group of dyslexic children and 63.3 ± 4.2 % and 30.3 ± 3.8% respectively for the group

\*\*\*

Fig. 6. Mean error rate in antisaccades for dyslexic children 10-13 years old (D 10-13) and non dyslexic children (younger and older, 7-9 (ND 7-9) and 10-13 years old (ND 10-13),

The ANOVA on error rate showed a significant main effect of group, F(2,86) = 17.88, p<0.0001. Post hoc comparison showed that the error rate for the older group of non-dyslexic children was significantly lower with respect to the other groups of children: p<0.003 for the dyslexics and p<0.0001 for the younger non dyslexic children. There was no difference

The present study showed first that dyslexic children performed the antisaccade task differently to chronological age matched non-dyslexic children: the latency values of correct antisaccades were longer; furthermore the error rate for dyslexic children was significantly higher compared to that of non dyslexic children of similar age. Secondly, this study showed that in non-dyslexic children the performance in the antisaccade task improved

Both results lend support to the previous studies conducted by Fischer's group with dyslexic children (Biscaldi et al., 2000; Fischer & Hartnegg, 2000a) and also other studies with normal children conducted by Fukushima et al. (2000) and by Irving et al. (2009). Note also that in this study the mean latency values of wrong prosaccades were similar in all three groups of children tested. This finding is only apparently in contrast with developmental evidences showing that latency of saccades is age dependent (see Leigh & Zee, 2006 for review). Indeed, in all developmental studies exploring latency of saccades, children had to saccades as quickly as possible to the target (by making a prosaccade) and it

between the non-dyslexic younger group and the dyslexic group (p=0.10).

of younger and older non dyslexic children.

Note: Vertical lines indicate standard error. \*\*\* = p<.0003.

respectively).

**4. Discussion** 

with age.

is well known, particularly in the case of children, that latency value depends on the subject's attention and motivation (Clark, 1999). In the present study child had to perform an antisaccade task and the latency here reported for prosaccades is due to a wrong response. Note that a similar finding has been also reported from the study of Munoz et al. (1998).

The new important finding of the present study comes from the comparison between dyslexic children with reading age matched non-dyslexic children. Indeed, the oculomotor behavior of the group of dyslexic children 10-13 years old was similar to that observed in the group of reading age matched non-dyslexic children (7-9 years old). Both the latency values of correct antisaccades and the error rate in the antisaccade task of dyslexic children 10-13 years old were similar to those found in reading age matched non dyslexic children (7-9 years old).

During saccade latency, it is assumed that several processes occur such as the shift of the visual attention to the new stimulus, the disengagement of oculomotor fixation, and the computation of the new parameters (Fischer & Ramsperger, 1984; Findlay & Walker, 1999). These processes involve different cortical and sub-cortical areas (see Leigh & Zee, 2006 for a full review). The longer saccade latency has frequently been attributed to an underdeveloped related cortex, and some investigations have also suggested that increased latency of saccades is related to difficulty in controlling visual fixation (Munoz et al., 1998).

To perform an antisaccade it is necessary to first inhibit the reflexive response towards the stimulus, and then to prepare a voluntary saccade in the opposite direction (antisaccade). Klein (2001), and Klein and Foerster (2001) reported that the capability to inhibit this type of saccade as well as the circuitry controlling cognitive processes is present as early as at 6 years old. They suggested that what is immature in young children is the capability to use such cognitive facilities, leading to a partially correct antisaccade response but to an overall impaired general performance for this task.

Malone and Iacono (2002) hypothesized that although young children have adequate working memory capability to perform correctly on the antisaccade task, they might not be capable of maintaining these instructions continuously throughout the course of the experiment. This may explain why young children in the current study showed long latencies and a high error rate in the antisaccade task.

On the other hand, it is also well known that the parietal cortex, the frontal eye field, the supplementary eye fields and the prefrontal cortex play important roles in antisaccade performance (Luna et al., 2008; McDowell et al., 2008). Further, the inferior parietal cortex has been suggested to be important for the inhibitory period preceding an antisaccade movement (Ettinger et al., 2008) and regions in the intraparietal sulcus (within parietal cortex) could be responsible for generating a correct antisaccade response (Clementz et al., 2007; Nyffeler et al., 2007).

Based on all the available evidences, we postulate the hypothesis that in dyslexic children the delayed maturation of all these structures could lead to longer latencies and increased error rate in the antisaccade task, similar to those reported in reading age matched nondyslexic children.

Antisaccades in Dyslexic Children: Evidence for Immaturity of Oculomotor Cortical Structures 71

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Furthermore, it should be noted that the limited fusional amplitude in divergence and convergence capabilities reported in dyslexic children with respect to the two groups of non dyslexic children found with the orthoptic tests is also in favour of a general immaturity of the cortical structures controlling the oculomotor system. Indeed, fusional vergence capabilities are age dependent (Scheiman et al., 1989; von Norrden and Campos, 2006) and at the cortical level some studies showed evidence of vergence control. For instance, the study of Gamlin & Yoon (2000) identified an area close to frontal eye field containing cells that discharge before and during vergence movements. More recently, Quinlan and Culham (2007) with an fMRI study showed an activation of parietal and occipital cortex while humans performed convergence. Thus, in the light of the existing physiological evidence for cortical control of vergence both in monkeys and in humans, the results of the clinical tests presented here in dyslexics suggest immaturity of the neuro-physiological circuitry responsible for generating vergence movements that are closer to the structures for generating saccades.

Finally, it should be noted that orthoptic training is widely used by clinicians for improving vergence capabilities (e.g., von Noorden & Campos, 2006). van Leeuven et al. (1999) and Bucci et al. (2004) reported objective studies on eye movements recordings in children, showing an improvement of vergence eye movements performance after orthoptic training. Consequently, orthoptic training could be applied also for dyslexic population.

#### **5. Conclusion and future directions**

The deficits in oculomotor behavior reported in dyslexic children seem to be due to the immaturity of their adaptive mechanism. We believe that visual attentional training along with oculomotor training could help dyslexic children to override such deficiencies allowing an appropriate control of the triggering and execution of saccadic eye movements. We hope to develop new training techniques resulting from this principle to help dyslexic children.

#### **6. Acknowledgments**

We thank the medical doctor and nurses of "Service de Psychopathologie de l'enfant et de l'adolescent", Robert Debré Hospital (Paris, France), Eliane Delouvrier, Camille de Solages, teachers, parents and children for their participation.

#### **7. References**


Furthermore, it should be noted that the limited fusional amplitude in divergence and convergence capabilities reported in dyslexic children with respect to the two groups of non dyslexic children found with the orthoptic tests is also in favour of a general immaturity of the cortical structures controlling the oculomotor system. Indeed, fusional vergence capabilities are age dependent (Scheiman et al., 1989; von Norrden and Campos, 2006) and at the cortical level some studies showed evidence of vergence control. For instance, the study of Gamlin & Yoon (2000) identified an area close to frontal eye field containing cells that discharge before and during vergence movements. More recently, Quinlan and Culham (2007) with an fMRI study showed an activation of parietal and occipital cortex while humans performed convergence. Thus, in the light of the existing physiological evidence for cortical control of vergence both in monkeys and in humans, the results of the clinical tests presented here in dyslexics suggest immaturity of the neuro-physiological circuitry responsible for generating vergence movements that are closer to the structures for

Finally, it should be noted that orthoptic training is widely used by clinicians for improving vergence capabilities (e.g., von Noorden & Campos, 2006). van Leeuven et al. (1999) and Bucci et al. (2004) reported objective studies on eye movements recordings in children, showing an improvement of vergence eye movements performance after orthoptic training.

The deficits in oculomotor behavior reported in dyslexic children seem to be due to the immaturity of their adaptive mechanism. We believe that visual attentional training along with oculomotor training could help dyslexic children to override such deficiencies allowing an appropriate control of the triggering and execution of saccadic eye movements. We hope to develop new training techniques resulting from this principle to help dyslexic children.

We thank the medical doctor and nurses of "Service de Psychopathologie de l'enfant et de l'adolescent", Robert Debré Hospital (Paris, France), Eliane Delouvrier, Camille de Solages,

Biscaldi M, Fischer B & Hartnegg K. (2000). Voluntary saccadic control in dyslexia.

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Consequently, orthoptic training could be applied also for dyslexic population.

generating saccades.

**6. Acknowledgments** 

**7. References** 

**5. Conclusion and future directions** 

teachers, parents and children for their participation.

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**6** 

*1Spain 2France* 

**Sequential** *Versus* **Simultaneous Processing** 

Despite the large number of studies conducted on developmental dyslexia, the cause(s) of the disorder still remain(s) unclear. Researchers in this field still struggle to understand the reason why abnormal reading acquisition occurs in children who receive appropriate environmental opportunities to achieve a good education, and present normal intellectual efficiency. This introduction will focus on the presentation of the phonological hypothesis, and then move onto the presentation of the visual attention span hypothesis, which predicts at least two proximal causes to developmental dyslexia. Setting the theoretical framework for these hypotheses will help to understand why sequential and simultaneous dimensions for visual and auditory processing may have independent roles to play in typical and

**1.1 The phonological hypothesis: The only core deficit of the reading disorder** 

The phonological hypothesis (e.g., Snowling, 2000), probably the most well-known hypothesis among those formulated so far, predicts that an impairment in various phonological components (e.g., phonological short-term memory, phonological awareness, and phonological fluency) and sub-lexical processing (i.e., at the level of units smaller than the word such as graphemes, syllables or morphemes) would be detrimental for the acquisition of the skills necessary to decode new words, and acquire fluent reading (see

This hypothesis suggests that difficulties in acquiring phonological awareness and the alphabetic principle would prevent letter-to-sound mapping from developing normally. Consequently, a phonological disorder would affect reading acquisition, impairing the abilities necessary to map sub-lexical and lexical orthographic forms to their auditory counterparts. In support to the phonological deficit hypothesis, studies on typical children provided reliable evidence for a causal link between phonological skills development and reading acquisition (see however Castles & Coltheart, 2004 for a counter-argument about this causality). For example, longitudinal studies have shown that phonological skills predict later reading performance (e.g., Hulme et al., 2002). Phonology-based training

**1. Introduction** 

atypical reading development.

Vellutino et al., 2004 for a review).

**Deficits in Developmental Dyslexia** 

*2Laboratoire de Psychologie et Neurocognition, CNRS UMR 5105,* 

Marie Lallier1 and Sylviane Valdois2

*1Basque Center on Cognition, Brain and Language,* 


## **Sequential** *Versus* **Simultaneous Processing Deficits in Developmental Dyslexia**

Marie Lallier1 and Sylviane Valdois2 *1Basque Center on Cognition, Brain and Language, 2Laboratoire de Psychologie et Neurocognition, CNRS UMR 5105, 1Spain 2France* 

#### **1. Introduction**

72 Dyslexia – A Comprehensive and International Approach

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Despite the large number of studies conducted on developmental dyslexia, the cause(s) of the disorder still remain(s) unclear. Researchers in this field still struggle to understand the reason why abnormal reading acquisition occurs in children who receive appropriate environmental opportunities to achieve a good education, and present normal intellectual efficiency. This introduction will focus on the presentation of the phonological hypothesis, and then move onto the presentation of the visual attention span hypothesis, which predicts at least two proximal causes to developmental dyslexia. Setting the theoretical framework for these hypotheses will help to understand why sequential and simultaneous dimensions for visual and auditory processing may have independent roles to play in typical and atypical reading development.

#### **1.1 The phonological hypothesis: The only core deficit of the reading disorder**

The phonological hypothesis (e.g., Snowling, 2000), probably the most well-known hypothesis among those formulated so far, predicts that an impairment in various phonological components (e.g., phonological short-term memory, phonological awareness, and phonological fluency) and sub-lexical processing (i.e., at the level of units smaller than the word such as graphemes, syllables or morphemes) would be detrimental for the acquisition of the skills necessary to decode new words, and acquire fluent reading (see Vellutino et al., 2004 for a review).

This hypothesis suggests that difficulties in acquiring phonological awareness and the alphabetic principle would prevent letter-to-sound mapping from developing normally. Consequently, a phonological disorder would affect reading acquisition, impairing the abilities necessary to map sub-lexical and lexical orthographic forms to their auditory counterparts. In support to the phonological deficit hypothesis, studies on typical children provided reliable evidence for a causal link between phonological skills development and reading acquisition (see however Castles & Coltheart, 2004 for a counter-argument about this causality). For example, longitudinal studies have shown that phonological skills predict later reading performance (e.g., Hulme et al., 2002). Phonology-based training

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 75

tasks used to assess the hypothesis of a general auditory disorder are temporal order and similarity judgment tasks. They involve the serial presentation of two phonological auditory stimuli and participants have to determine respectively which stimulus came first in the pair or whether the two stimuli were the same. Interestingly, deficits on these tasks were reported in SLI children only when the two stimuli were separated by a short time period; i.e., short ISI (e.g., Tallal & Piercy, 1973, 1974). Tallal's team then administered the same tasks to dyslexic children, but using non-verbal sounds such as pure tones. Deficits were reported in these children as compared to age-matched children but for ISIs shorter than 428ms (Tallal, 1980). A strong correlation was further found between dyslexic participants' performance on auditory temporal tasks and their pseudoword reading performance, thus providing first evidence for a link between rapid auditory sequential processing deficits and

Further evidence for a causal link between auditory and reading disorders was provided by Benasich and Tallal (1996), assessing performance of 7.5 month old infants considered "at risk" for a future language disorder on a task where participants had to distinguish various acoustic features presented at a fast rate. The performance of the infants on the task explained a significant part of variance in their later language skills and predicted a language impairment at 3 (Benasich & Tallal, 2002, see also Hood & Colon, 2004). Coupled with neuroimaging data, some training studies of auditory rapid sequential skills supported

While many studies showed auditory rapid sequential processing deficits in dyslexic individuals using either verbal (e.g., De Martino, Espesser, Rey, & Habib, 2001; Heim, Freeman, Eulitz, & Elbert, 2001) or non-verbal (e.g., Laasonen, Service, & Virsu, 2001) stimuli, other results questioned the restriction of the impairment to rapid stimuli sequences. Indeed, some studies failed to reveal a deficit in dyslexic participants on the short ISI conditions only (Bretherton & Holmes, 2003; Chiappe, Stringer, Siegel, & Stanovich, 2002; Ram-Tsur, Faust, & Zivotofsky, 2006). Others found that dyslexic individuals were impaired for long intervals as well, even when using the same tasks as Tallal (Share, Jorm, Maclean, & Matthews, 2002). It follows that auditory rapid sequential deficits may not be a condition sufficient and necessary to observe dyslexia. Nevertheless, available data suggests that such rapid sequential auditory processing plays a role in normal reading (Au & Lovegrove, 2001a,

It has also been suggested that the phoneme processing difficulties of dyslexic participants could well be part of a more general, amodal, rapid sequential processing deficit (the "rate processing deficit" hypothesis) by introducing the hypothesis of a similar impairment in the visual modality. Regarding visual *sequential* processing deficits, studies reported that as compared to controls, dyslexic individuals required longer ISIs in order to be accurate on spatial-temporal order judgment tasks, either with verbal (May, Williams, & Dunlap, 1988) or non-verbal (Hairston, Burdette, Flowers, Wood, & Wallace, 2005; Jaskowski & Russiak, 2008) visual stimuli. In these tasks – similar to those described previously in the auditory modalityparticipants are presented with pairs of visual stimuli appearing sequentially on a screen at

As with in the auditory modality however, findings revealed that visual temporal order judgment impairments of dyslexic participants did not depend upon the ISI duration (Ram-

2001b) and phonological development (Walker, Hall, Klein, & Phillips, 2006).

different locations, and have to decide which of the two stimuli was displayed first.

dyslexia.

such causal link (e.g., Habib et al., 2002).

programs further showed a positive impact on reading acquisition (see Ehri et al., 2001 for a review). Such data strongly suggests that the role that phonological difficulties play in the reading disorder may indeed be critical.

However, studies have questioned the restriction of the difficulties of dyslexic participants to the verbal sphere, assuming that phonological disorders would themselves result from more basic perceptual processing difficulties. Such studies propose that perceptual difficulties might affect the rapid temporal dimension of processing characterizing phonological inputs. Thus, in order to highlight a link between these difficulties and reading problems, a large number of studies have attempted to define the nature of the temporal dimension of the deficits observed in dyslexic participants. In their review of the literature, Farmer and Klein (1995) described studies showing impaired performance in dyslexic participants not only in auditory but also in visual temporal processing. The authors concluded that a temporal amodal processing deficit is associated with developmental dyslexia and that the phonological disorder would result from this temporal processing deficit. Soon after their review, Farmer and Klein were reproached for having poorly defined and circumscribed the temporal deficits found in individuals with developmental dyslexia (Rayner, Pollatsek, & Bilsky, 1995).

Starting from Farmer and Klein (1995) and from the literature published since then, the following section will present three main research axes providing coherent choices of experimental paradigms and specific interpretative frameworks regarding temporal deficits in developmental dyslexia. However, these hypotheses greatly overlap with each other, and are not mutually exclusive.

#### **1.1.1 The rapid temporal -** *sequential* **- processing deficit hypothesis**

Before starting to detail the rapid temporal processing deficit hypothesis, note that here, *temporal* refers to the *sequential* dimension of processing, i.e., the succession of two or more stimuli, which underlies the notion of inter-stimulus interval (ISI). ISI corresponds to the period of time separating two visual or auditory objects presented sequentially. Therefore, the shorter the ISI, the more rapid the stimuli succession speed. It is important to note that this hypothesis also accounts for another type of temporal processing, a *transient* processing (temporal change within one stimuli) which specifically relates to the magnocellular hypothesis of dyslexia (cf 1.1.2). This section more specifically focuses on *sequential* aspects of temporal processing deficits in dyslexic participants since studies testing the rapid temporal processing deficit hypothesis of dyslexia have mainly assessed this specific type (i.e., sequential) of temporal impairments.

In line with the phonological hypothesis which posits that developmental dyslexia stems from a linguistic deficit (Vellutino et al., 2004), Tallal (1980) put forward a more general hypothesis accounting for an auditory processing deficit in dyslexia. Her underlying hypothesis is that the degradation of speech temporal analysis at the phonemic level causes the reading difficulties of dyslexic participants. More specifically, Tallal reasoned that dyslexic participants could not process the fast temporal changes in the speech signal, leading to degraded and noisy representations of linguistic sounds.

The results supporting this hypothesis first came from studies of specific language impairment (SLI) children who exhibit phonological problems, like dyslexic children. The

programs further showed a positive impact on reading acquisition (see Ehri et al., 2001 for a review). Such data strongly suggests that the role that phonological difficulties play in the

However, studies have questioned the restriction of the difficulties of dyslexic participants to the verbal sphere, assuming that phonological disorders would themselves result from more basic perceptual processing difficulties. Such studies propose that perceptual difficulties might affect the rapid temporal dimension of processing characterizing phonological inputs. Thus, in order to highlight a link between these difficulties and reading problems, a large number of studies have attempted to define the nature of the temporal dimension of the deficits observed in dyslexic participants. In their review of the literature, Farmer and Klein (1995) described studies showing impaired performance in dyslexic participants not only in auditory but also in visual temporal processing. The authors concluded that a temporal amodal processing deficit is associated with developmental dyslexia and that the phonological disorder would result from this temporal processing deficit. Soon after their review, Farmer and Klein were reproached for having poorly defined and circumscribed the temporal deficits found in individuals with developmental

Starting from Farmer and Klein (1995) and from the literature published since then, the following section will present three main research axes providing coherent choices of experimental paradigms and specific interpretative frameworks regarding temporal deficits in developmental dyslexia. However, these hypotheses greatly overlap with each other, and

Before starting to detail the rapid temporal processing deficit hypothesis, note that here, *temporal* refers to the *sequential* dimension of processing, i.e., the succession of two or more stimuli, which underlies the notion of inter-stimulus interval (ISI). ISI corresponds to the period of time separating two visual or auditory objects presented sequentially. Therefore, the shorter the ISI, the more rapid the stimuli succession speed. It is important to note that this hypothesis also accounts for another type of temporal processing, a *transient* processing (temporal change within one stimuli) which specifically relates to the magnocellular hypothesis of dyslexia (cf 1.1.2). This section more specifically focuses on *sequential* aspects of temporal processing deficits in dyslexic participants since studies testing the rapid temporal processing deficit hypothesis of dyslexia have mainly assessed this specific type

In line with the phonological hypothesis which posits that developmental dyslexia stems from a linguistic deficit (Vellutino et al., 2004), Tallal (1980) put forward a more general hypothesis accounting for an auditory processing deficit in dyslexia. Her underlying hypothesis is that the degradation of speech temporal analysis at the phonemic level causes the reading difficulties of dyslexic participants. More specifically, Tallal reasoned that dyslexic participants could not process the fast temporal changes in the speech signal,

The results supporting this hypothesis first came from studies of specific language impairment (SLI) children who exhibit phonological problems, like dyslexic children. The

**1.1.1 The rapid temporal -** *sequential* **- processing deficit hypothesis** 

leading to degraded and noisy representations of linguistic sounds.

reading disorder may indeed be critical.

dyslexia (Rayner, Pollatsek, & Bilsky, 1995).

(i.e., sequential) of temporal impairments.

are not mutually exclusive.

tasks used to assess the hypothesis of a general auditory disorder are temporal order and similarity judgment tasks. They involve the serial presentation of two phonological auditory stimuli and participants have to determine respectively which stimulus came first in the pair or whether the two stimuli were the same. Interestingly, deficits on these tasks were reported in SLI children only when the two stimuli were separated by a short time period; i.e., short ISI (e.g., Tallal & Piercy, 1973, 1974). Tallal's team then administered the same tasks to dyslexic children, but using non-verbal sounds such as pure tones. Deficits were reported in these children as compared to age-matched children but for ISIs shorter than 428ms (Tallal, 1980). A strong correlation was further found between dyslexic participants' performance on auditory temporal tasks and their pseudoword reading performance, thus providing first evidence for a link between rapid auditory sequential processing deficits and dyslexia.

Further evidence for a causal link between auditory and reading disorders was provided by Benasich and Tallal (1996), assessing performance of 7.5 month old infants considered "at risk" for a future language disorder on a task where participants had to distinguish various acoustic features presented at a fast rate. The performance of the infants on the task explained a significant part of variance in their later language skills and predicted a language impairment at 3 (Benasich & Tallal, 2002, see also Hood & Colon, 2004). Coupled with neuroimaging data, some training studies of auditory rapid sequential skills supported such causal link (e.g., Habib et al., 2002).

While many studies showed auditory rapid sequential processing deficits in dyslexic individuals using either verbal (e.g., De Martino, Espesser, Rey, & Habib, 2001; Heim, Freeman, Eulitz, & Elbert, 2001) or non-verbal (e.g., Laasonen, Service, & Virsu, 2001) stimuli, other results questioned the restriction of the impairment to rapid stimuli sequences. Indeed, some studies failed to reveal a deficit in dyslexic participants on the short ISI conditions only (Bretherton & Holmes, 2003; Chiappe, Stringer, Siegel, & Stanovich, 2002; Ram-Tsur, Faust, & Zivotofsky, 2006). Others found that dyslexic individuals were impaired for long intervals as well, even when using the same tasks as Tallal (Share, Jorm, Maclean, & Matthews, 2002). It follows that auditory rapid sequential deficits may not be a condition sufficient and necessary to observe dyslexia. Nevertheless, available data suggests that such rapid sequential auditory processing plays a role in normal reading (Au & Lovegrove, 2001a, 2001b) and phonological development (Walker, Hall, Klein, & Phillips, 2006).

It has also been suggested that the phoneme processing difficulties of dyslexic participants could well be part of a more general, amodal, rapid sequential processing deficit (the "rate processing deficit" hypothesis) by introducing the hypothesis of a similar impairment in the visual modality. Regarding visual *sequential* processing deficits, studies reported that as compared to controls, dyslexic individuals required longer ISIs in order to be accurate on spatial-temporal order judgment tasks, either with verbal (May, Williams, & Dunlap, 1988) or non-verbal (Hairston, Burdette, Flowers, Wood, & Wallace, 2005; Jaskowski & Russiak, 2008) visual stimuli. In these tasks – similar to those described previously in the auditory modalityparticipants are presented with pairs of visual stimuli appearing sequentially on a screen at different locations, and have to decide which of the two stimuli was displayed first.

As with in the auditory modality however, findings revealed that visual temporal order judgment impairments of dyslexic participants did not depend upon the ISI duration (Ram-

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 77

2. The observation of these two neural pathways at the surface of the brain, (i.e., in the cerebral cortex, which plays a key role in language) via two routes called the dorsal and

3. The dorsal route starts from the visual primary brain areas (V1) to the visual motion brain areas (MT/V5) to finish on the posterior parietal cortex, that subtends to visual

In the visual modality, the magnocellular hypothesis predicts impaired monitoring of ocular movements, leading to visual confusion, superposition and distortion during reading. In the auditory modality, a similar organization is found with the existence of two cortical routes (Clarke, Bellmann, Meuli, Assal, & Steck, 2000). Moreover, the "magnocellular" auditory neurons have been shown to be specialized in the tracking of amplitude and auditory frequency (pitch) changes within acoustic signals (Trussel, 1999). According to Stein and Talcott (1999), a phonological disorder would result from auditory transient, very fast, temporal processing difficulties. Therefore, both visual and auditory transient processing deficits would together yield a degradation of grapheme-to-phoneme mapping processes

Data on behavioral tasks involving processing changes within stimuli have supported the visual transient processing deficit hypothesis of developmental dyslexia. It was indeed shown that dyslexic participants required more time to perceive the dynamic change within stimuli (McLean et al., 2011). The most commonly used tasks for revealing transient processing differences between dyslexic individuals and controls involve the detection of either a transient change in the identity of the stimulus (e.g., a single visual dot becoming two flashing dots at the same location: Edwards et al., 2004; Van Ingelghem et al., 2001), a transient change in the spatial location of the stimulus (e.g., when a visual object is moved to a different location: Jones, Branigan, & Kelly, 2008) or a transient change in the way a group of stimuli moves (e.g., when the direction of the movement of a group of visual dots changes: Cornelissen, Richardson, Mason, Fowler, & Stein, 1995). Supporting the magnocellular hypothesis deficit, visual transient processing deficits have been linked to sub-lexical reading deficits in participants with dyslexia (e.g., Cestnick & Coltheart, 1999). However, the link between visual transient processing and reading was not always established in skilled readers (e.g., Au & Lovegrove, 2001a). Moreover, strong inconsistencies have still been reported with some studies showing no such visual deficits in dyslexic participants (e.g., Amitay, Ben-Yehudah, Banai, & Ahissar, 2002; Ben-Yehudah,

In the auditory modality, a transient processing deficit has also been reported with experimental paradigms similar to the ones used in the visual modality, such as silent gap detection or segregation tasks (when participants have to detect a silence inserted within an auditory stimulus: Helenius, Salmelin, Service, & Connolly, 1999), the apparent movement task (when auditory tones moves from one hear to the other: Hari & Kiesilä, 1996 but see

1 Note that the magnocellular system preferentially responds to low spatial frequencies and is very sensitive to luminance contrasts. For the purpose of the present chapter, we will specifically focus on the *temporal transient* processing deficits in relation to reading disorders and reading development.

selective attention and ocular movement monitoring (important in reading).

and sub-lexical reading and decoding (Pammer & Vidyasagar, 2005).

temporal processing – *sustained system*1);

ventral routes respectively;

Sackett, Malchi-Ginzberg, & Ahissar, 2001).

fast temporal processing, whereas the parvocellular system is more sensitive to slower

Tsur et al., 2006; Ram-Tsur, Faust, & Zivotofsky, 2008). Some studies even failed to show any disorder of this kind (Laasonen Tomma-Halme, Lahti-Nuuttila, Service, & Virsu., 2000, Lassonen et al., 2001). Supporting the idea of a weak link between visual sequential processing and reading, Hood and Conlon (2004) failed to show that visual temporal order judgment performance of preschoolers predicted their reading skills at Grade 1 (see also Landerl & Willburger, 2010 for similar results in both the visual and the auditory modality). However, Walker et al. (2006) showed that such performance significantly contributed to reading performance and phonological awareness abilities in a large sample of young and older adults with various reading levels.

Despite attempts to highlight an amodal rapid sequential processing deficit, very few studies have actually measured visual and auditory rapid sequential processing in the same dyslexic participants using similar paradigms (e.g., Laasonen et al., 2000, 2001; Reed, 1989). Overall, previous studies question the sequential visual impairment but the nature of the auditory processes that have been captured by the order judgment task (e.g., deciding which of two stimuli displayed sequentially appeared first) and similarity judgment task (e.g., deciding whether two stimuli presented sequentially were the same or not) still needs to be clarified (see Bailey & Snowling, 2002). Lastly, this hypothesis tends to predict a relation between visual rapid sequential processing and lexical reading, i.e., regular word or irregular word reading, but *a priori* no link with phonological processing, which is hard to reconcile with the phonological hypothesis of developmental dyslexia. Pointing out these problems, Stein and Talcott (1999) reminded that the rapid sequential processing deficit hypothesis was first grounded on temporal order and similarity judgments, which, according to them, cannot capture the temporal processing required for phonological representation build-up.

#### **1.1.2 The magnocellular hypothesis: The "Impaired Neuronal Timing" hypothesis (Stein & Talcott, 1999)**

The magnocellular hypothesis of dyslexia (Stein & Walsh, 1997; Stein & Talcott, 1999) supports the idea of visual and auditory perceptual deficits which specifically account for *transient* or *dynamic* aspects of temporal processing (i.e., rapid physical changes in real time within a stimulus). To a lesser extent, it relies to the ability to process distinct stimuli when presented serially, in sequences (see 1.1.1). Stein and Talcott (1999) claimed that sensitivity to transient events could be assessed with simple stimuli triggering the activation of neurons specifically devoted to that type of processing: the magnocellular cells. The authors assume that magnocellular cells which are part of both the visual and the auditory human systems would dysfunction in dyslexic participants (vision: Livingstone, Rosen, Drislane, & Galaburda, 1991; audition: Galaburda, Menard, & Rosen, 1994). In that sense, the magnocellular hypothesis of dyslexia differs from the rapid sequential processing deficit hypothesis because the latter does not specify any cerebral origin to the auditory and visual deficits of individuals with dyslexia.

Originally, the magnocellular hypothesis builds its foundation on the organization of the visual system and leans onto three main ideas:

1. The existence of two independent neural pathways, located deep below the surface of the brain (sub cortical structures), called the magnocellular and parvocellular pathways. Interestingly, the magnocellular system – called also *the transient system* - is tuned in to

Tsur et al., 2006; Ram-Tsur, Faust, & Zivotofsky, 2008). Some studies even failed to show any disorder of this kind (Laasonen Tomma-Halme, Lahti-Nuuttila, Service, & Virsu., 2000, Lassonen et al., 2001). Supporting the idea of a weak link between visual sequential processing and reading, Hood and Conlon (2004) failed to show that visual temporal order judgment performance of preschoolers predicted their reading skills at Grade 1 (see also Landerl & Willburger, 2010 for similar results in both the visual and the auditory modality). However, Walker et al. (2006) showed that such performance significantly contributed to reading performance and phonological awareness abilities in a large sample of young and

Despite attempts to highlight an amodal rapid sequential processing deficit, very few studies have actually measured visual and auditory rapid sequential processing in the same dyslexic participants using similar paradigms (e.g., Laasonen et al., 2000, 2001; Reed, 1989). Overall, previous studies question the sequential visual impairment but the nature of the auditory processes that have been captured by the order judgment task (e.g., deciding which of two stimuli displayed sequentially appeared first) and similarity judgment task (e.g., deciding whether two stimuli presented sequentially were the same or not) still needs to be clarified (see Bailey & Snowling, 2002). Lastly, this hypothesis tends to predict a relation between visual rapid sequential processing and lexical reading, i.e., regular word or irregular word reading, but *a priori* no link with phonological processing, which is hard to reconcile with the phonological hypothesis of developmental dyslexia. Pointing out these problems, Stein and Talcott (1999) reminded that the rapid sequential processing deficit hypothesis was first grounded on temporal order and similarity judgments, which, according to them, cannot

capture the temporal processing required for phonological representation build-up.

**1.1.2 The magnocellular hypothesis: The "Impaired Neuronal Timing" hypothesis** 

The magnocellular hypothesis of dyslexia (Stein & Walsh, 1997; Stein & Talcott, 1999) supports the idea of visual and auditory perceptual deficits which specifically account for *transient* or *dynamic* aspects of temporal processing (i.e., rapid physical changes in real time within a stimulus). To a lesser extent, it relies to the ability to process distinct stimuli when presented serially, in sequences (see 1.1.1). Stein and Talcott (1999) claimed that sensitivity to transient events could be assessed with simple stimuli triggering the activation of neurons specifically devoted to that type of processing: the magnocellular cells. The authors assume that magnocellular cells which are part of both the visual and the auditory human systems would dysfunction in dyslexic participants (vision: Livingstone, Rosen, Drislane, & Galaburda, 1991; audition: Galaburda, Menard, & Rosen, 1994). In that sense, the magnocellular hypothesis of dyslexia differs from the rapid sequential processing deficit hypothesis because the latter does not specify any cerebral origin to the auditory and visual

Originally, the magnocellular hypothesis builds its foundation on the organization of the

1. The existence of two independent neural pathways, located deep below the surface of the brain (sub cortical structures), called the magnocellular and parvocellular pathways. Interestingly, the magnocellular system – called also *the transient system* - is tuned in to

older adults with various reading levels.

**(Stein & Talcott, 1999)** 

deficits of individuals with dyslexia.

visual system and leans onto three main ideas:

fast temporal processing, whereas the parvocellular system is more sensitive to slower temporal processing – *sustained system*1);


In the visual modality, the magnocellular hypothesis predicts impaired monitoring of ocular movements, leading to visual confusion, superposition and distortion during reading. In the auditory modality, a similar organization is found with the existence of two cortical routes (Clarke, Bellmann, Meuli, Assal, & Steck, 2000). Moreover, the "magnocellular" auditory neurons have been shown to be specialized in the tracking of amplitude and auditory frequency (pitch) changes within acoustic signals (Trussel, 1999). According to Stein and Talcott (1999), a phonological disorder would result from auditory transient, very fast, temporal processing difficulties. Therefore, both visual and auditory transient processing deficits would together yield a degradation of grapheme-to-phoneme mapping processes and sub-lexical reading and decoding (Pammer & Vidyasagar, 2005).

Data on behavioral tasks involving processing changes within stimuli have supported the visual transient processing deficit hypothesis of developmental dyslexia. It was indeed shown that dyslexic participants required more time to perceive the dynamic change within stimuli (McLean et al., 2011). The most commonly used tasks for revealing transient processing differences between dyslexic individuals and controls involve the detection of either a transient change in the identity of the stimulus (e.g., a single visual dot becoming two flashing dots at the same location: Edwards et al., 2004; Van Ingelghem et al., 2001), a transient change in the spatial location of the stimulus (e.g., when a visual object is moved to a different location: Jones, Branigan, & Kelly, 2008) or a transient change in the way a group of stimuli moves (e.g., when the direction of the movement of a group of visual dots changes: Cornelissen, Richardson, Mason, Fowler, & Stein, 1995). Supporting the magnocellular hypothesis deficit, visual transient processing deficits have been linked to sub-lexical reading deficits in participants with dyslexia (e.g., Cestnick & Coltheart, 1999). However, the link between visual transient processing and reading was not always established in skilled readers (e.g., Au & Lovegrove, 2001a). Moreover, strong inconsistencies have still been reported with some studies showing no such visual deficits in dyslexic participants (e.g., Amitay, Ben-Yehudah, Banai, & Ahissar, 2002; Ben-Yehudah, Sackett, Malchi-Ginzberg, & Ahissar, 2001).

In the auditory modality, a transient processing deficit has also been reported with experimental paradigms similar to the ones used in the visual modality, such as silent gap detection or segregation tasks (when participants have to detect a silence inserted within an auditory stimulus: Helenius, Salmelin, Service, & Connolly, 1999), the apparent movement task (when auditory tones moves from one hear to the other: Hari & Kiesilä, 1996 but see

<sup>1</sup> Note that the magnocellular system preferentially responds to low spatial frequencies and is very sensitive to luminance contrasts. For the purpose of the present chapter, we will specifically focus on the *temporal transient* processing deficits in relation to reading disorders and reading development.

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 79

of *distinct successive stimuli*, and, on the other hand, to the processing of distinct changes

Therefore, the SAS hypothesis does not make predictions about, for example, auditory frequency or amplitude modulation detection described by the magnocellular deficit hypothesis. Hari & Renvall (2001) propose that SAS is "*the pathophysiological link between the magnocellular deficit and the RSS* [Rapid Stimuli Sequence] *processing in dyslexic subjects*" (p.530). In this framework, a magnocellular dysfunction would not be a factor sufficient and necessary to observe dyslexia (Skoyles & Skottun, 2004) although magnocellar deficits would still potentially be associated with manifestations of reading difficulties. Rather, Hari and Renvall assume that the parietal dysfunction would be responsible for reading

The principles of the SAS hypothesis are the following: when a to-be-processed stimulus is perceived, it falls into a perceptual temporal window whose size depends upon how fast the cognitive system can integrate this stimulus. According to Hari and Renvall (2001), the time of integration would be prolonged in individuals with developmental dyslexia. When several stimuli are sequentially presented, the prolongation of the integration time would create interferences between the stimuli entering the temporal window and induce a prolonged perceptual persistence in dyslexic individuals (e.g., Slaghuis & Ryan, 1999). It is therefore inferred that dyslexic participants would show difficulties in automatically

disengaging the focus of attention from one stimulus to reengage it on the next one.

In order to justify the specific attentional (and not perceptual) origin of the deficit, Hari and Renvall (2001) argue that 1) dyslexic participants do not exhibit any deficit regarding the temporal synchronization between the moment when stimulus is presented and its actual processing by the neuronal system (*phase locking*: Hari, Saaskilahti, Helenius, & Uutela, 1999a; Llinas, 1993; Witton, Richardson, Griffiths, & Rees, 1997) and 2) the SAS hypothesis can account for two attention phenomena known to be linked to reading, namely the attentional dwell time and the symptom of hemineglect. These two phenomena are

i. The attentional dwell time has been reported in all sensory modalities in paradigms where stimuli are rapidly and serially presentated (in vision: Raymond, Shapiro, & Arnell, 1992; in audition: Vachon & Tremblay, 2008). The attentional dwell time is a theoretical concept corresponding to a natural limit in attentional resources reflected by the interference induced when several stimuli fall into the same temporal integration window. Specifically, the attentional dwell time is thought to cause difficulties in processing a target falling into the same temporal integration window as a first previous target to which most attentional resources have been already allocated. This drop in performance for the second target processing would spread from 300ms to 500ms after the presentation of the first target depending on the experimental paradigm and/or the sensory modality. According to Hari and Renvall (2001), this natural limit in temporal attention resources would be stronger in individuals with developmental dyslexia because of their SAS skills. Hence, in dyslexic participants, the combination of SAS skills and attentional dwell time would lead to a prolongation of temporal input chunks falling under the attentional focus. The length of these inputs would increase their complexity, inducing poor encoding of visual or auditory sequential stimuli at

within a *stimulus sequence* (rather than within a single stimulus).

disabilities, via SAS skills.

explained below:

Kronbichler, Hutzler, & Wimmer, 2002), or pitch and amplitude modulation discrimination tasks (when auditory stimuli progressively change in loudness or pitch: Witton, Stein, Stoodley, Rosner, & Talcott, 2002). Phonological skills (Talcott et al., 2000, but see Kidd & Hogben, 2007) and pseudo word reading (Au & Lovegrove, 2001a, 2001b, 2008; Walker et al., 2006; Witton et al., 2002) performance has further been linked to auditory transient (i.e., magnocellular) performance. Some data further suggests a potential causal link between auditory transient processing and phonological skills (Schäffler, Sonntag, Hartnegg, & Fischer, 2004).

However, it still remains that a phonological deficit does not always accompany difficulties in auditory or visual transient processing (Heim et al., 2008; Kronbichler et al., 2002; Ramus et al., 2003; White et al., 2006). The hypothesis of a role of these deficits in the reading disorder has been criticized particularly in the visual modality and such visual deficits have been considered as an epiphenomenon associated with reading difficulties (e.g., Hutzler, Kronbichler, Jacobs, & Wimmer, 2006; Skottun, 2000).

Interestingly, in their original proposal, Stein and Talcott (1999; Stein & Walsh, 1997) suggest that the link between magnocells dysfunction and developmental dyslexia is mediated by poor ocular movement monitoring because of the projection of magnocells to the posterior parietal cortex in charge of such visual-motor control skills. From that perspective, it has been proposed that the reading disorder may rather result from a parietal dysfunction than from the degradation of magnocells *per se* (e.g., Boden & Giaschi, 2007). Along these lines, Buchholz and MacKone (2004) concluded that phonological awareness and visual attention skills – subtended by parietal activation – are related, whereas phonology and magnocellular processing *per se* are not. This new perspective based on attentional processing will result in a new proposal explaining the cause of developmental dyslexia, favoring the role of the parietal cortex in the amodal temporal processing deficits associated with the reading disorder (Hari & Renvall, 2001).

#### **1.1.3 The sluggish attentional shifting hypothesis**

According to Hari and Renvall (2001), the magnocellular dysfunction at the cell level could lead to a variety of symptoms (including the reading disorder) which would depend on what cerebral structure is the most impaired by the magnocellular dysfunction. From that perspective, the type of temporal processing affected would not be specific to magnocell characteristics but would be supported by the cerebral structure the most affected by the magnocell dysfunction. In the sluggish attentional shifting (SAS, hereafter) hypothesis, Hari and Renvall (2001) propose the parietal cortex as the structure responsible for the reading disorder (see Figure 1 for a schematic representation of the links between the magnocellular and the SAS hypotheses in relation to reading disorders).

According to these authors, the parietal dysfunction would affect the automatic processes engaged in attentional shifting over rapid stimulus sequences in all sensory modalities (auditory, visual, and tactile). In that sense, the SAS hypothesis stands at the crossroad between the rapid sequential (perceptual) processing deficit hypothesis (see section 1.1.1) and the magnocellular deficit hypothesis of developmental dyslexia (see 1.1.2). Hari and Renvall (2001) described precisely the temporal dimension their theory accounts for and emphasized that this specific temporal processing relates, on the one hand, to the processing

Kronbichler, Hutzler, & Wimmer, 2002), or pitch and amplitude modulation discrimination tasks (when auditory stimuli progressively change in loudness or pitch: Witton, Stein, Stoodley, Rosner, & Talcott, 2002). Phonological skills (Talcott et al., 2000, but see Kidd & Hogben, 2007) and pseudo word reading (Au & Lovegrove, 2001a, 2001b, 2008; Walker et al., 2006; Witton et al., 2002) performance has further been linked to auditory transient (i.e., magnocellular) performance. Some data further suggests a potential causal link between auditory transient processing and phonological skills (Schäffler, Sonntag, Hartnegg, &

However, it still remains that a phonological deficit does not always accompany difficulties in auditory or visual transient processing (Heim et al., 2008; Kronbichler et al., 2002; Ramus et al., 2003; White et al., 2006). The hypothesis of a role of these deficits in the reading disorder has been criticized particularly in the visual modality and such visual deficits have been considered as an epiphenomenon associated with reading difficulties (e.g., Hutzler,

Interestingly, in their original proposal, Stein and Talcott (1999; Stein & Walsh, 1997) suggest that the link between magnocells dysfunction and developmental dyslexia is mediated by poor ocular movement monitoring because of the projection of magnocells to the posterior parietal cortex in charge of such visual-motor control skills. From that perspective, it has been proposed that the reading disorder may rather result from a parietal dysfunction than from the degradation of magnocells *per se* (e.g., Boden & Giaschi, 2007). Along these lines, Buchholz and MacKone (2004) concluded that phonological awareness and visual attention skills – subtended by parietal activation – are related, whereas phonology and magnocellular processing *per se* are not. This new perspective based on attentional processing will result in a new proposal explaining the cause of developmental dyslexia, favoring the role of the parietal cortex in the amodal temporal processing deficits associated

According to Hari and Renvall (2001), the magnocellular dysfunction at the cell level could lead to a variety of symptoms (including the reading disorder) which would depend on what cerebral structure is the most impaired by the magnocellular dysfunction. From that perspective, the type of temporal processing affected would not be specific to magnocell characteristics but would be supported by the cerebral structure the most affected by the magnocell dysfunction. In the sluggish attentional shifting (SAS, hereafter) hypothesis, Hari and Renvall (2001) propose the parietal cortex as the structure responsible for the reading disorder (see Figure 1 for a schematic representation of the links between the magnocellular

According to these authors, the parietal dysfunction would affect the automatic processes engaged in attentional shifting over rapid stimulus sequences in all sensory modalities (auditory, visual, and tactile). In that sense, the SAS hypothesis stands at the crossroad between the rapid sequential (perceptual) processing deficit hypothesis (see section 1.1.1) and the magnocellular deficit hypothesis of developmental dyslexia (see 1.1.2). Hari and Renvall (2001) described precisely the temporal dimension their theory accounts for and emphasized that this specific temporal processing relates, on the one hand, to the processing

Kronbichler, Jacobs, & Wimmer, 2006; Skottun, 2000).

with the reading disorder (Hari & Renvall, 2001).

**1.1.3 The sluggish attentional shifting hypothesis** 

and the SAS hypotheses in relation to reading disorders).

Fischer, 2004).

of *distinct successive stimuli*, and, on the other hand, to the processing of distinct changes within a *stimulus sequence* (rather than within a single stimulus).

Therefore, the SAS hypothesis does not make predictions about, for example, auditory frequency or amplitude modulation detection described by the magnocellular deficit hypothesis. Hari & Renvall (2001) propose that SAS is "*the pathophysiological link between the magnocellular deficit and the RSS* [Rapid Stimuli Sequence] *processing in dyslexic subjects*" (p.530). In this framework, a magnocellular dysfunction would not be a factor sufficient and necessary to observe dyslexia (Skoyles & Skottun, 2004) although magnocellar deficits would still potentially be associated with manifestations of reading difficulties. Rather, Hari and Renvall assume that the parietal dysfunction would be responsible for reading disabilities, via SAS skills.

The principles of the SAS hypothesis are the following: when a to-be-processed stimulus is perceived, it falls into a perceptual temporal window whose size depends upon how fast the cognitive system can integrate this stimulus. According to Hari and Renvall (2001), the time of integration would be prolonged in individuals with developmental dyslexia. When several stimuli are sequentially presented, the prolongation of the integration time would create interferences between the stimuli entering the temporal window and induce a prolonged perceptual persistence in dyslexic individuals (e.g., Slaghuis & Ryan, 1999). It is therefore inferred that dyslexic participants would show difficulties in automatically disengaging the focus of attention from one stimulus to reengage it on the next one.

In order to justify the specific attentional (and not perceptual) origin of the deficit, Hari and Renvall (2001) argue that 1) dyslexic participants do not exhibit any deficit regarding the temporal synchronization between the moment when stimulus is presented and its actual processing by the neuronal system (*phase locking*: Hari, Saaskilahti, Helenius, & Uutela, 1999a; Llinas, 1993; Witton, Richardson, Griffiths, & Rees, 1997) and 2) the SAS hypothesis can account for two attention phenomena known to be linked to reading, namely the attentional dwell time and the symptom of hemineglect. These two phenomena are explained below:

i. The attentional dwell time has been reported in all sensory modalities in paradigms where stimuli are rapidly and serially presentated (in vision: Raymond, Shapiro, & Arnell, 1992; in audition: Vachon & Tremblay, 2008). The attentional dwell time is a theoretical concept corresponding to a natural limit in attentional resources reflected by the interference induced when several stimuli fall into the same temporal integration window. Specifically, the attentional dwell time is thought to cause difficulties in processing a target falling into the same temporal integration window as a first previous target to which most attentional resources have been already allocated. This drop in performance for the second target processing would spread from 300ms to 500ms after the presentation of the first target depending on the experimental paradigm and/or the sensory modality. According to Hari and Renvall (2001), this natural limit in temporal attention resources would be stronger in individuals with developmental dyslexia because of their SAS skills. Hence, in dyslexic participants, the combination of SAS skills and attentional dwell time would lead to a prolongation of temporal input chunks falling under the attentional focus. The length of these inputs would increase their complexity, inducing poor encoding of visual or auditory sequential stimuli at

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 81

neurophysiologic cause and specific cerebral locus of the reading disorder. In this framework, developmental dyslexia is still viewed as resulting from a phonological disorder, which however would be associated with additional visual attentional deficits

Fig. 1. Schematic syntheses of the causal cascade (plain arrows) suggested by the

**1.2 The visual attention span deficit hypothesis: Developmental dyslexia as a** 

So far we have reviewed hypotheses that have been put forward in order to explain developmental dyslexia as resulting from a phonological disorder. However, it appears that at least some dyslexic cases are clearly not phonological (Friedmann & Naachman-Katz, 2004; Friedmann & Rahamin, 2007; Rouse & Wilshire, 2007; Valdois et al., 2003; Valdois, Lassus-Sangosse, & Lobier, In press), thus questioning the homogeneity of developmental dyslexia. Instead, a growing body of evidence suggests that developmental dyslexia is

The visual attention span (VA Span hereafter) hypothesis put forward by Bosse, Tainturier and Valdois (2007) is complementary to the phonological deficit hypothesis. It posits that another cause of developmental dyslexia stands in a limitation of the visual attention resources that can be allocated simultaneously to letters within words. This would in particular prevent normal encoding of whole word orthographic information. The VA Span therefore taps into parallel, simultaneous, processing, and VA Span resources are expected

magnocellular and the SAS hypotheses. Dotted simple arrows represent causal links and dotted double arrows associative links as suggested in the literature but which have been questioned. Note that the SAS hypothesis explains many symptoms associated with

whose role in reading difficulties still remains unclear.

developmental dyslexia. Adapted from Lallier (2009).

to be limited in at least a subgroup of dyslexic children.

**cognitive multifactorial disorder** 

heterogeneous (e.g., Heim et al., 2008).

higher levels (such as graphemic –letter- or phonemic –language soundsrepresentations).

ii. Furthermore, based on the observation that visual heminiglect patients2 exhibit a prolongation of the attentional dwell time (Husain, Shapiro, Martin, & Kennard, 1997), Hari and Renvall (2001) proposed the left visual minineglect as a marker of developmental dyslexia, but not as a causal factor. From that perspective, this left minineglect would result from a dysfunction, and not a lesion, of the right parietal cortex (Hari, Renvall, & Tanskanen, 2001; Liddle, Jackson, Rorden, & Jackson, 2009). Supporting this idea, dyslexic children have been shown to suffer from left pseudoneglect, i.e. presenting symptoms of left hemineglect patients, in absence of any parietal lesion. The typical behavioural marker for this left pseudoneglect is the absence of the usual overestimation (facilitation for processing) of stimuli presented in the left visual hemifield (Sireteanu, Goertz, Bachert, & Wandert 2005; Sireteanu, Goebel, Goertz, & Wandert, 2006).

Along the same lines, data collected in dyslexic individuals are in accordance with an asymmetric distribution of attention resources between right and left visual hemifields (e.g., Facoetti & Moltoni, 2001; Facoetti Paganoni, Turatto, Marzola, & Mascetti,, 2000; Facoetti & Turatto, 2000). Indeed, Facoetti's team studies show that participants with developmental dyslexia exhibit higher inhibition for the stimuli displayed in the left visual field but a facilitation of processing for those displayed in the right visual field. Moreover, it has been shown that training programs involving specific stimulation of each hemisphere individually (tachitoscopic presentation of words) improved not only the visual-spatial attentional skills of dyslexic readers in the right hemisphere/left hemifield (Facoetti, Lorusso, Paganoni, Umilta, & Mascetti, 2003; Lorusso, Facoetti, Toraldo, & Molteni, 2005) but also their reading performance (Lorusso, Facoetti, & Molteni, 2004; Lorusso et al., 2005). Note that lesions in the posterior parietal cortex can also induce auditory neglect (Marshall, 2001), the SAS hypothesis predicts similar impairment in the auditory modality.

Regarding the link between visual and auditory SAS and reading, Hari and Renvall (2001) assume that a phonological disorder would result from auditory SAS. Indeed SAS is expected to cause longer and more complex phonological input chunks, thus hindering the build-up of stable phonological representations. The link between visual SAS skills and reading is clearly explained (i.e., because the number of letters that participants have to encode during one ocular fixation during reading is increased, interferences and possible confusions in reading are observed) but their responsibility in the phonological disorder is not described. However, one can assume that both visual and auditory SAS would be linked to phonological deficits via their contribution to the acquisition of the grapheme-phoneme correspondences that are indispensable for normal reading acquisition (Pammer & Vidyasagar, 2005; Vidyasagar & Pammer, 2010).

The SAS hypothesis therefore offers an explicative framework for verbal and non-verbal auditory and visual attention sequential deficits. It furthermore specifies the

<sup>2</sup> Hemineglect patients typically suffer from a parietal lesion (interpreted as an attentional deficit at the cognitive level) which causes difficulties in encoding and processing visual object appearing in the hemifield in the opposite side of this parietal brain lesion (e.g., impairment of processing visual object appearing on the right side visual field due to a lesion in the parietal lobe of the left part of the brain).

ii. Furthermore, based on the observation that visual heminiglect patients2 exhibit a prolongation of the attentional dwell time (Husain, Shapiro, Martin, & Kennard, 1997), Hari and Renvall (2001) proposed the left visual minineglect as a marker of developmental dyslexia, but not as a causal factor. From that perspective, this left minineglect would result from a dysfunction, and not a lesion, of the right parietal cortex (Hari, Renvall, & Tanskanen, 2001; Liddle, Jackson, Rorden, & Jackson, 2009). Supporting this idea, dyslexic children have been shown to suffer from left pseudoneglect, i.e. presenting symptoms of left hemineglect patients, in absence of any parietal lesion. The typical behavioural marker for this left pseudoneglect is the absence of the usual overestimation (facilitation for processing) of stimuli presented in the left visual hemifield (Sireteanu, Goertz, Bachert, & Wandert 2005; Sireteanu, Goebel,

representations).

Goertz, & Wandert, 2006).

impairment in the auditory modality.

Vidyasagar, 2005; Vidyasagar & Pammer, 2010).

higher levels (such as graphemic –letter- or phonemic –language sounds-

Along the same lines, data collected in dyslexic individuals are in accordance with an asymmetric distribution of attention resources between right and left visual hemifields (e.g., Facoetti & Moltoni, 2001; Facoetti Paganoni, Turatto, Marzola, & Mascetti,, 2000; Facoetti & Turatto, 2000). Indeed, Facoetti's team studies show that participants with developmental dyslexia exhibit higher inhibition for the stimuli displayed in the left visual field but a facilitation of processing for those displayed in the right visual field. Moreover, it has been shown that training programs involving specific stimulation of each hemisphere individually (tachitoscopic presentation of words) improved not only the visual-spatial attentional skills of dyslexic readers in the right hemisphere/left hemifield (Facoetti, Lorusso, Paganoni, Umilta, & Mascetti, 2003; Lorusso, Facoetti, Toraldo, & Molteni, 2005) but also their reading performance (Lorusso, Facoetti, & Molteni, 2004; Lorusso et al., 2005). Note that lesions in the posterior parietal cortex can also induce auditory neglect (Marshall, 2001), the SAS hypothesis predicts similar

Regarding the link between visual and auditory SAS and reading, Hari and Renvall (2001) assume that a phonological disorder would result from auditory SAS. Indeed SAS is expected to cause longer and more complex phonological input chunks, thus hindering the build-up of stable phonological representations. The link between visual SAS skills and reading is clearly explained (i.e., because the number of letters that participants have to encode during one ocular fixation during reading is increased, interferences and possible confusions in reading are observed) but their responsibility in the phonological disorder is not described. However, one can assume that both visual and auditory SAS would be linked to phonological deficits via their contribution to the acquisition of the grapheme-phoneme correspondences that are indispensable for normal reading acquisition (Pammer &

The SAS hypothesis therefore offers an explicative framework for verbal and non-verbal auditory and visual attention sequential deficits. It furthermore specifies the

2 Hemineglect patients typically suffer from a parietal lesion (interpreted as an attentional deficit at the cognitive level) which causes difficulties in encoding and processing visual object appearing in the hemifield in the opposite side of this parietal brain lesion (e.g., impairment of processing visual object appearing on the right side visual field due to a lesion in the parietal lobe of the left part of the brain).

neurophysiologic cause and specific cerebral locus of the reading disorder. In this framework, developmental dyslexia is still viewed as resulting from a phonological disorder, which however would be associated with additional visual attentional deficits whose role in reading difficulties still remains unclear.

Fig. 1. Schematic syntheses of the causal cascade (plain arrows) suggested by the magnocellular and the SAS hypotheses. Dotted simple arrows represent causal links and dotted double arrows associative links as suggested in the literature but which have been questioned. Note that the SAS hypothesis explains many symptoms associated with developmental dyslexia. Adapted from Lallier (2009).

#### **1.2 The visual attention span deficit hypothesis: Developmental dyslexia as a cognitive multifactorial disorder**

So far we have reviewed hypotheses that have been put forward in order to explain developmental dyslexia as resulting from a phonological disorder. However, it appears that at least some dyslexic cases are clearly not phonological (Friedmann & Naachman-Katz, 2004; Friedmann & Rahamin, 2007; Rouse & Wilshire, 2007; Valdois et al., 2003; Valdois, Lassus-Sangosse, & Lobier, In press), thus questioning the homogeneity of developmental dyslexia. Instead, a growing body of evidence suggests that developmental dyslexia is heterogeneous (e.g., Heim et al., 2008).

The visual attention span (VA Span hereafter) hypothesis put forward by Bosse, Tainturier and Valdois (2007) is complementary to the phonological deficit hypothesis. It posits that another cause of developmental dyslexia stands in a limitation of the visual attention resources that can be allocated simultaneously to letters within words. This would in particular prevent normal encoding of whole word orthographic information. The VA Span therefore taps into parallel, simultaneous, processing, and VA Span resources are expected to be limited in at least a subgroup of dyslexic children.

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 83

Fig. 2. Schematic illustration of the whole and partial report tasks. The whole report task requires naming as many of the 5 consonants as possible without order constraint (a.). The

The link between VA Span skills and reading has been observed in a group study conducted in two populations of dyslexic children (68 French speaking dyslexic children and 29 English dyslexic children) whose performance was compared to age-matched children (Bosse et al., 2007). All children were given a screening battery comprising reading tasks, phonological awareness tasks and the whole and partial report tasks. Results showed that a large part of dyslexic children exhibited either a specific and selective phonological deficit or a specific and selective VA Span deficit. On the other hand, a smaller group of children exhibited a double deficit (i.e., on phoneme awareness *and* visual letter report tasks). Moreover, the results of the study in French speaking children revealed that both phonological and VA Span skills independently explained a significant part of variance in reading performance. The study in the English speaking children confirmed that VA Span skills contribute to reading abilities even when non verbal IQ, verbal fluency skills, vocabulary and the performance on a single letter identification task are controlled for. Bosse et al. (2007)'s findings therefore suggest that at least two independent cognitive disorders underlying developmental dyslexia can be observed. Their conclusion is furthermore supported by a case study in two French dyslexic teenagers showing that a reading disorder of the same severity could either be accompanied by a phonological disorder (rhyme judgment, sound categorization, phoneme and syllable omission, phoneme segmentation, acronyms) associated with a phonological dyslexic profile (impaired decoding skills illustrated by poor pseudoword reading and spelling skills) in the absence of any VA Span deficit on the two report tasks, *or* by a VA Span disorder associated with a surface dyslexia profile (poor lexical reading procedure illustrated by poor word reading

partial report task requires a single cued letter to be named (b.).

and spelling) with no additional phonological disorder (Valdois et al., 2003).

The role of VA Span skills in normal reading development was investigated in a crosssectional study conducted on large samples of typically developing children from 1st to 5th grade (Bosse & Valdois, 2009). Results showed that VA Span abilities contributed to reading performance from the early stages of literacy instruction even after controlling for variations

The VA Span is a notion theoretically motivated by the Multi-Trace Memory model of reading (Ans, Carbonnel, & Valdois, 1998; hereafter MTM model). The MTM model was the first reading model to implement a visual attention component, called the visual attentional window (which is the counterpart of the VA Span in human participants). The VA window is a critical component of the reading system as it delineates the amount of orthographic information which is under the focus of attention at each step of the reading process. The MTM model postulates that reading relies on two global (parallel) and analytic (serial) procedures that differ regarding the visual attention window size, and therefore, regarding VA Span skills and the quantity of visual attention devoted to processing. In global mode, the window opens over the whole letter string whereas in analytic mode, it narrows down to focus attention on each orthographic sub-unit of the input word in turn. Although these two procedures are *a priori* not devoted to reading specific item types, most familiar items (in particular previously learned words) are processed in global mode whereas non-familiar items (most pseudowords) are processed in analytic mode. The visual attentional window therefore corresponds to the set of visual elements over which the visual attentional focus falls.

Following this theoretical framework, it was reasoned that a VA Span reduction (i.e., a reduction of the number of visual letters that can be processed simultaneously) should prevent normal encoding of the orthographic sequence of most words (Bosse et al., 2007). According to this idea, a reduced VA Span would be particularly detrimental when reading irregular words that cannot be accurately decoded serially.

The VA Span is typically measured using whole and partial letter report tasks which require naming all of the letters of a five-consonant string or a single post-cued letter within the string (see Fig 2). In partial as in global report, participants have to process all five consonants since the position of the letter to be reported is randomly chosen and the cue in partial report only occurs at the offset of the consonant string. Moreover, sequences are displayed for a time period short enough to avoid useful ocular saccades (<200ms), so that participants have to engage enough visual attention resources to process all five elements simultaneously (Lobier, Przybylski, & Valdois, Submitted; Peyrin, Lallier, & Valdois, 2008; Peyrin, Démonet, N´Guyen-Morel, Le Bas, & Valdois, 2011). Only consonants are used as stimuli to compose unpronounceable illegal letter strings. In random consonant strings, identification of one consonant within the string does not help identifying the other consonants, so that the number of reported letters provides a good account of the number of distinct elements that can be processed simultaneously. To avoid any potential top-down influence of orthographic knowledge on performance, the consonant strings we use do not include any multi-letter grapheme or frequent bigram (as CH or FL in French). Moreover, sequences do not correspond to the skeleton of any word (e.g., C M P T R for computer), since we know that such consonant strings activate the corresponding word orthographic information in long term memory. In the whole report task, the five elements need to be verbally reported without order constraint whereas in the partial report task the cued letter alone has to be reported. Accordingly, responses as "RHSDM", "SDHRM" or "DSRMH" are all considered as accurate (quoted 5/5) for the "RHSDM" input in global report, since all five consonants have been accurately identified in all three cases. A deficit on such tasks is reflected by a poor accuracy report score, interpreted as a reduction of the VA Span.

The VA Span is a notion theoretically motivated by the Multi-Trace Memory model of reading (Ans, Carbonnel, & Valdois, 1998; hereafter MTM model). The MTM model was the first reading model to implement a visual attention component, called the visual attentional window (which is the counterpart of the VA Span in human participants). The VA window is a critical component of the reading system as it delineates the amount of orthographic information which is under the focus of attention at each step of the reading process. The MTM model postulates that reading relies on two global (parallel) and analytic (serial) procedures that differ regarding the visual attention window size, and therefore, regarding VA Span skills and the quantity of visual attention devoted to processing. In global mode, the window opens over the whole letter string whereas in analytic mode, it narrows down to focus attention on each orthographic sub-unit of the input word in turn. Although these two procedures are *a priori* not devoted to reading specific item types, most familiar items (in particular previously learned words) are processed in global mode whereas non-familiar items (most pseudowords) are processed in analytic mode. The visual attentional window therefore corresponds to the set of visual elements over which

Following this theoretical framework, it was reasoned that a VA Span reduction (i.e., a reduction of the number of visual letters that can be processed simultaneously) should prevent normal encoding of the orthographic sequence of most words (Bosse et al., 2007). According to this idea, a reduced VA Span would be particularly detrimental when reading

The VA Span is typically measured using whole and partial letter report tasks which require naming all of the letters of a five-consonant string or a single post-cued letter within the string (see Fig 2). In partial as in global report, participants have to process all five consonants since the position of the letter to be reported is randomly chosen and the cue in partial report only occurs at the offset of the consonant string. Moreover, sequences are displayed for a time period short enough to avoid useful ocular saccades (<200ms), so that participants have to engage enough visual attention resources to process all five elements simultaneously (Lobier, Przybylski, & Valdois, Submitted; Peyrin, Lallier, & Valdois, 2008; Peyrin, Démonet, N´Guyen-Morel, Le Bas, & Valdois, 2011). Only consonants are used as stimuli to compose unpronounceable illegal letter strings. In random consonant strings, identification of one consonant within the string does not help identifying the other consonants, so that the number of reported letters provides a good account of the number of distinct elements that can be processed simultaneously. To avoid any potential top-down influence of orthographic knowledge on performance, the consonant strings we use do not include any multi-letter grapheme or frequent bigram (as CH or FL in French). Moreover, sequences do not correspond to the skeleton of any word (e.g., C M P T R for computer), since we know that such consonant strings activate the corresponding word orthographic information in long term memory. In the whole report task, the five elements need to be verbally reported without order constraint whereas in the partial report task the cued letter alone has to be reported. Accordingly, responses as "RHSDM", "SDHRM" or "DSRMH" are all considered as accurate (quoted 5/5) for the "RHSDM" input in global report, since all five consonants have been accurately identified in all three cases. A deficit on such tasks is

reflected by a poor accuracy report score, interpreted as a reduction of the VA Span.

the visual attentional focus falls.

irregular words that cannot be accurately decoded serially.

Fig. 2. Schematic illustration of the whole and partial report tasks. The whole report task requires naming as many of the 5 consonants as possible without order constraint (a.). The partial report task requires a single cued letter to be named (b.).

The link between VA Span skills and reading has been observed in a group study conducted in two populations of dyslexic children (68 French speaking dyslexic children and 29 English dyslexic children) whose performance was compared to age-matched children (Bosse et al., 2007). All children were given a screening battery comprising reading tasks, phonological awareness tasks and the whole and partial report tasks. Results showed that a large part of dyslexic children exhibited either a specific and selective phonological deficit or a specific and selective VA Span deficit. On the other hand, a smaller group of children exhibited a double deficit (i.e., on phoneme awareness *and* visual letter report tasks). Moreover, the results of the study in French speaking children revealed that both phonological and VA Span skills independently explained a significant part of variance in reading performance. The study in the English speaking children confirmed that VA Span skills contribute to reading abilities even when non verbal IQ, verbal fluency skills, vocabulary and the performance on a single letter identification task are controlled for. Bosse et al. (2007)'s findings therefore suggest that at least two independent cognitive disorders underlying developmental dyslexia can be observed. Their conclusion is furthermore supported by a case study in two French dyslexic teenagers showing that a reading disorder of the same severity could either be accompanied by a phonological disorder (rhyme judgment, sound categorization, phoneme and syllable omission, phoneme segmentation, acronyms) associated with a phonological dyslexic profile (impaired decoding skills illustrated by poor pseudoword reading and spelling skills) in the absence of any VA Span deficit on the two report tasks, *or* by a VA Span disorder associated with a surface dyslexia profile (poor lexical reading procedure illustrated by poor word reading and spelling) with no additional phonological disorder (Valdois et al., 2003).

The role of VA Span skills in normal reading development was investigated in a crosssectional study conducted on large samples of typically developing children from 1st to 5th grade (Bosse & Valdois, 2009). Results showed that VA Span abilities contributed to reading performance from the early stages of literacy instruction even after controlling for variations

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 85

impaired in tasks involving visual-to-phonological code mapping. Dyslexic and control children were asked to perform a 5-elements report task using letters, digits and color patches as stimuli. All three conditions required verbally reporting as many letter, digit or color names as possible at the offset of the multi-element string. Accordingly a visual-tophonological code mapping disorder was expected to impact all three conditions. Against this expectation however, dyslexic participants were found to exhibit poor performance in letter and digit string report tasks but no disorder in the color string report task. This result

Moreover, Valdois et al. (In press) reported a second experiment in which dyslexic children were administered two versions of the whole letter report task. Both conditions required the oral report of all five letter-names at the end of processing but the whole report task was either performed alone or together with a concurrent phonological articulation task (i.e., of counting aloud). The concurrent articulation task taxed phonological processing and verbal short-term memory and as such prevented online verbal encoding of letter names during visual processing. Dyslexic children exhibited a similar VA Span deficit in the two conditions, suggesting that performance was not modulated by on line verbal encoding. This last result suggests that difficulties of dyslexic participants on the whole report task do

Moreover, Lobier, Lassus-Sangosse, Zoubrinetzki, and Valdois (In press) administered a categorization task which required parallel processing of multi-elements within strings to a group of dyslexic children selected for their poor performance in visual letter report tasks. The categorization task involved the processing of verbal (digits and letters) *or* non-verbal (Japanese Hiragana characters, pseudo letters, and unknown geometrical shapes) characters. The study aimed to assess whether this group of dyslexic children exhibited similar difficulties in the processing of alphanumeric and non-alphanumeric character strings. The dyslexic participants with a VA Span deficit were found to be impaired on the visual categorization task regardless of whether the stimuli to be processed were verbal or nonverbal. They were thus impaired in a non-verbal task using non-verbal stimuli as they were found impaired in the letter report task. Taken together, these results provide strong evidence against a phonological account of poor letter string processing and VA Span skills

The currently available neurobiological data collected during parallel multi-element processing are well in line with the VA Span interpretation. Data from adult skilled readers showed that the letter report task elicited increased activation of the superior parietal lobules bilaterally and that activation of these regions was reduced in the dyslexic participants (Peyrin, et al., 2008). In another study carried out on dyslexic and non-dyslexic children, participants were administered a categorization task comprising two isolated and flanked conditions (inspired from Pernet, Valdois, Celsis, & Démonet, 2006) under fMRI (Peyrin et al., 2011). In both conditions, two stimuli – either two letters or two geometrical shapes or one of each – were simultaneously displayed, one stimulus was centrally presented on the fixation point, the other one was randomly presented in the right or left visual field. In the flanked condition, the peripheral stimulus was flanked with two "X"s whereas it was presented alone in the isolated condition. Participants had to decide whether the two stimuli belonged to the same category or not. Results replicated previous findings in showing that VA Span impaired dyslexic children were characterized by reduced

goes against the visual-to-phonological code mapping disorder hypothesis.

not result from a verbal encoding deficit.

in developmental dyslexia.

in phonological performance. Indeed, the unique contribution of VA Span to reading performance was observed from the first year of literacy instruction at a time phoneme awareness skills played an important (but independent) role in reading acquisition. Furthermore, VA Span performance contributed preferentially to irregular word reading (i.e., word-specific orthographic knowledge) as compared to pseudoword reading.

Moreover regarding spelling abilities, the findings of Valdois and Bosse (Submitted) in 1st, 3rd and 5th graders strengthen the role of VA Span skills in orthographic knowledge acquisition. These authors show that VA Span skills and phonological skills independently contribute to the acquisition of orthographic knowledge. Moreover, VA Span contribution to word spelling accuracy remains even after accounting for the children's recoding skills. This suggests a role of VA Span in the acquisition of word specific orthographic knowledge. VA Span contribution to word spelling is more stable than phoneme awareness contribution over grades, suggesting a long-term influence of the VA Span on the acquisition of orthographic knowledge. In sum, a large body of data from dyslexic and typically developing children supports a role of the VA Span in reading and spelling. The overall data points to the involvement of VA Span in the acquisition of orthographic knowledge and suggests this visual attention mechanism may act as a self-teaching device process.

The VA Span hypothesis postulates that the component preventing dyslexic individuals from performing accurately a multi-element array of stimuli does not relate to any type of verbal or phonological disorder but rather, to visual attention (Bosse et al., 2007; Peyrin et al., 2011). It has however been argued that poor performance in letter report tasks might be due to verbal deficits in encoding and reporting letters, and as such reflected a visual-tophonology code mapping disorder (Ziegler, Pech-Georgel, Dufau, & Grainger, 2010) rather than a visual attention resource limitation. Ziegler et al. (2010)'s account is based on data from a forced choice detection task in which children were shown briefly presented strings of letters, digits or symbols. At the offset of the multi-character string, participants had to choose which one of two characters previously occurred in a cued position within the string. Results showed that dyslexic children performed poorly when asked to process letter or digit strings but at the level of control children when processing symbol strings. The authors reasoned that a VA Span disorder would have predicted a deficit whenever multi-element parallel processing is required independently of the nature (alphanumeric or not) of the stimuli. Against this expectation, their data showed that the disorder was restricted to alphanumeric material. They thus concluded that their findings did not support the VA Span deficit hypothesis but rather suggested a visual-to-phonological code mapping disorder.

It is however noteworthy that the letter/digit *versus* symbol character not only differ in their phonological characteristics (pronounceable *versus* non pronounceable characters) but also in the visual ones (familiar *versus* unfamiliar visual shapes), so that differences in processing might follow from one or the other dimension.

Against the phonological account, data shows that:


With respect to the first point and against the visual-to-phonological code mapping disorder interpretation, Valdois et al. (In press) showed that dyslexic children are not systematically

in phonological performance. Indeed, the unique contribution of VA Span to reading performance was observed from the first year of literacy instruction at a time phoneme awareness skills played an important (but independent) role in reading acquisition. Furthermore, VA Span performance contributed preferentially to irregular word reading

Moreover regarding spelling abilities, the findings of Valdois and Bosse (Submitted) in 1st, 3rd and 5th graders strengthen the role of VA Span skills in orthographic knowledge acquisition. These authors show that VA Span skills and phonological skills independently contribute to the acquisition of orthographic knowledge. Moreover, VA Span contribution to word spelling accuracy remains even after accounting for the children's recoding skills. This suggests a role of VA Span in the acquisition of word specific orthographic knowledge. VA Span contribution to word spelling is more stable than phoneme awareness contribution over grades, suggesting a long-term influence of the VA Span on the acquisition of orthographic knowledge. In sum, a large body of data from dyslexic and typically developing children supports a role of the VA Span in reading and spelling. The overall data points to the involvement of VA Span in the acquisition of orthographic knowledge and suggests this visual attention mechanism may act as a self-teaching device process.

The VA Span hypothesis postulates that the component preventing dyslexic individuals from performing accurately a multi-element array of stimuli does not relate to any type of verbal or phonological disorder but rather, to visual attention (Bosse et al., 2007; Peyrin et al., 2011). It has however been argued that poor performance in letter report tasks might be due to verbal deficits in encoding and reporting letters, and as such reflected a visual-tophonology code mapping disorder (Ziegler, Pech-Georgel, Dufau, & Grainger, 2010) rather than a visual attention resource limitation. Ziegler et al. (2010)'s account is based on data from a forced choice detection task in which children were shown briefly presented strings of letters, digits or symbols. At the offset of the multi-character string, participants had to choose which one of two characters previously occurred in a cued position within the string. Results showed that dyslexic children performed poorly when asked to process letter or digit strings but at the level of control children when processing symbol strings. The authors reasoned that a VA Span disorder would have predicted a deficit whenever multi-element parallel processing is required independently of the nature (alphanumeric or not) of the stimuli. Against this expectation, their data showed that the disorder was restricted to alphanumeric material. They thus concluded that their findings did not support the VA Span deficit hypothesis but rather suggested a visual-to-phonological code mapping disorder.

It is however noteworthy that the letter/digit *versus* symbol character not only differ in their phonological characteristics (pronounceable *versus* non pronounceable characters) but also in the visual ones (familiar *versus* unfamiliar visual shapes), so that differences in processing


With respect to the first point and against the visual-to-phonological code mapping disorder interpretation, Valdois et al. (In press) showed that dyslexic children are not systematically


might follow from one or the other dimension.

set;

Against the phonological account, data shows that:

(i.e., word-specific orthographic knowledge) as compared to pseudoword reading.

impaired in tasks involving visual-to-phonological code mapping. Dyslexic and control children were asked to perform a 5-elements report task using letters, digits and color patches as stimuli. All three conditions required verbally reporting as many letter, digit or color names as possible at the offset of the multi-element string. Accordingly a visual-tophonological code mapping disorder was expected to impact all three conditions. Against this expectation however, dyslexic participants were found to exhibit poor performance in letter and digit string report tasks but no disorder in the color string report task. This result goes against the visual-to-phonological code mapping disorder hypothesis.

Moreover, Valdois et al. (In press) reported a second experiment in which dyslexic children were administered two versions of the whole letter report task. Both conditions required the oral report of all five letter-names at the end of processing but the whole report task was either performed alone or together with a concurrent phonological articulation task (i.e., of counting aloud). The concurrent articulation task taxed phonological processing and verbal short-term memory and as such prevented online verbal encoding of letter names during visual processing. Dyslexic children exhibited a similar VA Span deficit in the two conditions, suggesting that performance was not modulated by on line verbal encoding. This last result suggests that difficulties of dyslexic participants on the whole report task do not result from a verbal encoding deficit.

Moreover, Lobier, Lassus-Sangosse, Zoubrinetzki, and Valdois (In press) administered a categorization task which required parallel processing of multi-elements within strings to a group of dyslexic children selected for their poor performance in visual letter report tasks. The categorization task involved the processing of verbal (digits and letters) *or* non-verbal (Japanese Hiragana characters, pseudo letters, and unknown geometrical shapes) characters. The study aimed to assess whether this group of dyslexic children exhibited similar difficulties in the processing of alphanumeric and non-alphanumeric character strings. The dyslexic participants with a VA Span deficit were found to be impaired on the visual categorization task regardless of whether the stimuli to be processed were verbal or nonverbal. They were thus impaired in a non-verbal task using non-verbal stimuli as they were found impaired in the letter report task. Taken together, these results provide strong evidence against a phonological account of poor letter string processing and VA Span skills in developmental dyslexia.

The currently available neurobiological data collected during parallel multi-element processing are well in line with the VA Span interpretation. Data from adult skilled readers showed that the letter report task elicited increased activation of the superior parietal lobules bilaterally and that activation of these regions was reduced in the dyslexic participants (Peyrin, et al., 2008). In another study carried out on dyslexic and non-dyslexic children, participants were administered a categorization task comprising two isolated and flanked conditions (inspired from Pernet, Valdois, Celsis, & Démonet, 2006) under fMRI (Peyrin et al., 2011). In both conditions, two stimuli – either two letters or two geometrical shapes or one of each – were simultaneously displayed, one stimulus was centrally presented on the fixation point, the other one was randomly presented in the right or left visual field. In the flanked condition, the peripheral stimulus was flanked with two "X"s whereas it was presented alone in the isolated condition. Participants had to decide whether the two stimuli belonged to the same category or not. Results replicated previous findings in showing that VA Span impaired dyslexic children were characterized by reduced

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 87

Interestingly, the SAS and VA Span hypotheses both predict visual attention problems in developmental dyslexia, but while the VA Span hypothesis assigns to the visual attention disorder a causal role in developmental dyslexia, the SAS hypothesis rather predicts an association between reading and sequential visual attention skills than a causal relationship, unlike what is posited in the auditory modality. Furthermore, the SAS hypothesis predicts sequential attention deficits in both the auditory and visual modalities whereas the VA Span hypothesis *a priori* predicts that the simultaneous attention deficit in dyslexic individuals is

The figure below provides a schematic representation of the different predictions of the SAS and VA Span hypotheses regarding visual and auditory processing deficits in

Fig. 3. Schematic representation of the VA Span and SAS hypotheses. The two hypotheses postulate that a parietal dysfunction yields the reading disorder through distinct cognitive impairments (VA Span and phonological disorders respectively). Thick arrows illustrate the causal cascade of impairments leading to developmental dyslexia for each of the two hypotheses. Dotted arrows indicate causal links (simple arrows) or associative links (double

In the following section, we will present arguments in favor of a dissociation between the two hypotheses and between the expected attention impairments. The data that will be

restricted to the visual modality only (see Fig 3).

arrows) with no or weak support in the literature.

presented will address two main questions:

developmental dyslexia.

activations within the superior parietal lobules bilaterally (Peyrin et al., 2011). Thus, multielement parallel processing relies on brain regions that are well known for their involvement in visual attention. More recently, Lobier et al. (Submitted) investigated whether these parietal regions were sensitive to the alphanumeric or non-alphanumeric nature of the stimuli. They administered a non-verbal categorization task under fMRI using either letters or digits as targets, or pseudo-letters, shapes and hiragana characters. They found that the superior parietal lobules were involved in the processing of both alphanumeric and non-alphanumeric character strings and that activity in these regions was reduced in dyslexic individuals regardless of character type (i.e., strings composed of alphanumeric or non alphanumeric elements).

The overall results of the series of studies of Valdois'team thus support the existence in a subset of dyslexic individuals of a parallel multi-element processing disorder, i.e. a VA Span disorder, that relates to a superior parietal lobules dysfunction and dissociates from phonological problems.

#### **2. SAS** *versus* **VA Span hypotheses: Sequential** *versus* **simultaneous processing deficits in dyslexia**

We previously presented a set of hypotheses that sought to explain the cognitive origin of developmental dyslexia. The first part was devoted to the description of the phonological hypothesis which postulates that reading difficulties result from a specific impairment affecting the processing of phonological stimuli, then resulting in difficulties in mapping graphemes to phonemes during reading. Among the hypotheses presented, the SAS hypothesis postulates a deficit at the attentional level which would then lead to developmental reading disorders.

In the second part, we presented a multifactorial view of the cause of developmental dyslexia: the VA Span hypothesis. This hypothesis assumes that atypical reading development can either stem from a phonological deficit, or a visual attention deficit affecting the simultaneous processing of multiple visual stimuli. In preventing simultaneous processing of letters within the word string, the VA Span disorder is expected to prevent normal encoding of whole word forms, thus leading poor word-specific orthographic knowledge acquisition.

It is noteworthy that the type of attention processes described in the SAS and the VA Span hypotheses corresponds to what could be named "perceptual" or "automatic" attention. Such attention processes are thought to facilitate the processing of stimuli falling under the focus of attention during the first 200-250 msec after engagement of the attentional focus.

Looking at the SAS and VA Span hypotheses more carefully, we can observe that they offer complementary accounts for developmental dyslexia. While they both assume that a parietal dysfunction is the cerebral origin of the reading disorder, the two hypotheses differ in the sense that the parietal impairments described would lead to distinct, independent, cognitive deficits: a phonological deficit for the SAS hypothesis, and a visual attention deficit for the VA Span hypothesis. Moreover, it is assumed that the mechanisms underlying phonological and VA Span processing would *a priori* engage distinct dimensions of processing: one sequential, and the other simultaneous.

activations within the superior parietal lobules bilaterally (Peyrin et al., 2011). Thus, multielement parallel processing relies on brain regions that are well known for their involvement in visual attention. More recently, Lobier et al. (Submitted) investigated whether these parietal regions were sensitive to the alphanumeric or non-alphanumeric nature of the stimuli. They administered a non-verbal categorization task under fMRI using either letters or digits as targets, or pseudo-letters, shapes and hiragana characters. They found that the superior parietal lobules were involved in the processing of both alphanumeric and non-alphanumeric character strings and that activity in these regions was reduced in dyslexic individuals regardless of character type (i.e., strings composed of

The overall results of the series of studies of Valdois'team thus support the existence in a subset of dyslexic individuals of a parallel multi-element processing disorder, i.e. a VA Span disorder, that relates to a superior parietal lobules dysfunction and dissociates from

We previously presented a set of hypotheses that sought to explain the cognitive origin of developmental dyslexia. The first part was devoted to the description of the phonological hypothesis which postulates that reading difficulties result from a specific impairment affecting the processing of phonological stimuli, then resulting in difficulties in mapping graphemes to phonemes during reading. Among the hypotheses presented, the SAS hypothesis postulates a deficit at the attentional level which would then lead to

In the second part, we presented a multifactorial view of the cause of developmental dyslexia: the VA Span hypothesis. This hypothesis assumes that atypical reading development can either stem from a phonological deficit, or a visual attention deficit affecting the simultaneous processing of multiple visual stimuli. In preventing simultaneous processing of letters within the word string, the VA Span disorder is expected to prevent normal encoding of whole word forms, thus leading poor word-specific orthographic

It is noteworthy that the type of attention processes described in the SAS and the VA Span hypotheses corresponds to what could be named "perceptual" or "automatic" attention. Such attention processes are thought to facilitate the processing of stimuli falling under the focus of attention during the first 200-250 msec after engagement of the attentional focus.

Looking at the SAS and VA Span hypotheses more carefully, we can observe that they offer complementary accounts for developmental dyslexia. While they both assume that a parietal dysfunction is the cerebral origin of the reading disorder, the two hypotheses differ in the sense that the parietal impairments described would lead to distinct, independent, cognitive deficits: a phonological deficit for the SAS hypothesis, and a visual attention deficit for the VA Span hypothesis. Moreover, it is assumed that the mechanisms underlying phonological and VA Span processing would *a priori* engage distinct dimensions of processing: one

**2. SAS** *versus* **VA Span hypotheses: Sequential** *versus* **simultaneous** 

alphanumeric or non alphanumeric elements).

phonological problems.

**processing deficits in dyslexia** 

developmental reading disorders.

sequential, and the other simultaneous.

knowledge acquisition.

Interestingly, the SAS and VA Span hypotheses both predict visual attention problems in developmental dyslexia, but while the VA Span hypothesis assigns to the visual attention disorder a causal role in developmental dyslexia, the SAS hypothesis rather predicts an association between reading and sequential visual attention skills than a causal relationship, unlike what is posited in the auditory modality. Furthermore, the SAS hypothesis predicts sequential attention deficits in both the auditory and visual modalities whereas the VA Span hypothesis *a priori* predicts that the simultaneous attention deficit in dyslexic individuals is restricted to the visual modality only (see Fig 3).

The figure below provides a schematic representation of the different predictions of the SAS and VA Span hypotheses regarding visual and auditory processing deficits in developmental dyslexia.

Fig. 3. Schematic representation of the VA Span and SAS hypotheses. The two hypotheses postulate that a parietal dysfunction yields the reading disorder through distinct cognitive impairments (VA Span and phonological disorders respectively). Thick arrows illustrate the causal cascade of impairments leading to developmental dyslexia for each of the two hypotheses. Dotted arrows indicate causal links (simple arrows) or associative links (double arrows) with no or weak support in the literature.

In the following section, we will present arguments in favor of a dissociation between the two hypotheses and between the expected attention impairments. The data that will be presented will address two main questions:

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 89

sequences of multiple (i.e., more than two) stimuli as used in paradigms of stream segregation (Helenius et al., 1999) or attentional blink (Hari et al., 1999). These paradigms seem more appropriate to capture the nature of the auditory and visual processes engaged for the encoding of speech streams or orthographic sequences (these paradigms will be

Therefore, we propose that an assessment of SAS amodal deficit in dyslexic participants should be conducted 1) with tasks requiring the processing of long stimulus sequences (see Meyler & Breznitz, 2005, for a similar proposal) and 2) in groups of participants with

The role of amodal simultaneous processing in reading development has barely been studied. We are aware of only one study which tried to capture amodal simultaneous processing deficit in dyslexia. Geiger et al. (2008) administered to a group of dyslexic children two similar tasks, one in the visual modality, the other one in the auditory modality. In the visual modality, participants were asked to recognize letter stimuli presented in the center of a screen and ignore the letter stimuli in the periphery. In the auditory modality, they had to recognize auditory lexical stimuli presented via speakers located in front of participants (i.e., centrally) with or without the presence of auditory simultaneous peripheral lexical stimuli. Dyslexic children were found to exhibit difficulties in recognizing the central stimuli presented with external noise in both the auditory and the visual modalities. The authors concluded to a "wider perceptual mode" in the dyslexic children, which in turn may hinder their ability to focus on relevant stimuli and inhibit irrelevant information. Unfortunately, this study did not specify whether the assessed dyslexic children exhibited a phonological deficit, making impossible to determine whether such simultaneous processing deficits were found regardless of phonological deficits, as the

**2.2 Assessing visual and auditory sequential and simultaneous deficits in relation to** 

In the following section, we will present evidence that sequential and simultaneous disorders in developmental dyslexia can be found in the same dyslexic participants in both

1. sequential and simultaneous automatic attention processes rely on different

2. these mechanisms relate to potentially independent literacy-related cognitive abilities, i.e., phonological (sequential) or VA Span (simultaneous), leading to different dyslexia

We first need to emphasize the fact that when investigating auditory and visual non-verbal attention or perception abilities, the underlying cognitive deficits of the dyslexic group should be precisely defined. This is critical in order to investigate the extent to which deficits in non-verbal abilities are linked and result to specific cognitive dyslexic symptoms (i.e., phonological or VA Span disorders). Disregarding this first step may lead to highly

**phonological and VA Span disorders in developmental dyslexia** 

the visual and the auditory modalities. Moreover, we will argue that:

developmental dyslexia diagnosed with a phonological deficit.

described later in this chapter).

**2.1.2 Simultaneous processing deficits** 

VA Span hypothesis would predict.

mechanisms;

subtypes.


Based on experimental evidence, we will argue that sequential and simultaneous attention deficits may play independent roles in the reading disorder, in hindering the development of independent cognitive components which are both required for normal reading acquisition.

#### **2.1 Amodal sequential and simultaneous processing deficits**

#### **2.1.1 Sequential processing deficits**

Few studies straightforwardly addressed the question of amodal *attentional* processing deficits in dyslexia, since research interests have largely focused on the amodal *perceptual* deficit hypothesis. Disorders extending over several modalities, as expected by the SAS hypothesis, have then been reported (Meyler & Breznitz, 2005). However, a fair amount of data failed to highlight amodal rapid sequential processing disorders in dyslexic individuals, either because of the absence of deficit in the visual modality (e.g., Eddins & Green, 1995; Laasonen et al., 2001; Reed, 1989; Welch, DuttonHurt, & Warren, 1986) or because of the absence of deficits in both modalities (e.g., Bretherton & Holmes, 2003; Laasonen et al., 2000).

Such inconclusive results in the visual modality (as opposed to the auditory modality) could reflect the absence of causal role of visual sequential deficits in developmental dyslexia (see Skottun, 2000). They could also follow from the heterogeneity of the dyslexic population and lack of characterization of the cognitive deficits underlying the reading disorder of dyslexic participants at the individual level. Indeed, knowing that all cases of developmental dyslexia *are not* associated with phonological disorders (Bosse et al., 2007), performance may have been influenced by the heterogeneity of the phonological disorders in the dyslexic sample. In line with this hypothesis, Meyler and Breznitz (2005) who reported a phonological deficit in their dyslexic group did find an amodal sequential deficit in their dyslexic participants.

Differences in the choice of experimental paradigms could also have led to inconsistent results in the observation of amodal sequential deficits in dyslexia. In the original proposal of Tallal (1980), rapid temporal deficits were assessed with order or similarity judgment tasks composed of two stimuli only. Interestingly, the SAS hypothesis predicts deficits on sequences of multiple (i.e., more than two) stimuli as used in paradigms of stream segregation (Helenius et al., 1999) or attentional blink (Hari et al., 1999). These paradigms seem more appropriate to capture the nature of the auditory and visual processes engaged for the encoding of speech streams or orthographic sequences (these paradigms will be described later in this chapter).

Therefore, we propose that an assessment of SAS amodal deficit in dyslexic participants should be conducted 1) with tasks requiring the processing of long stimulus sequences (see Meyler & Breznitz, 2005, for a similar proposal) and 2) in groups of participants with developmental dyslexia diagnosed with a phonological deficit.

#### **2.1.2 Simultaneous processing deficits**

88 Dyslexia – A Comprehensive and International Approach

1. The question of amodality will be first addressed. Indeed, Hari and Renvall (2001) in their initial proposal argued for an amodal SAS in developmental dyslexia. They however reported studies that assessed SAS in either the visual or the auditory modality, but never explored the two modalities in the same dyslexic participants, therefore questioning the amodality of the sequential deficits. We will examine to what extent sequential and simultaneous attention deficits quantified on similar paradigms in both the auditory and the visual modalities can be observed in the same dyslexic

2. The second question that we will address is to what extent sequential and simultaneous deficits relate respectively to the phonological and VA Span disorder in developmental dyslexia. In particular, the link between SAS and phonological disorders was never directly assessed in the previously mentioned studies, thus questioning the validity of

Based on experimental evidence, we will argue that sequential and simultaneous attention deficits may play independent roles in the reading disorder, in hindering the development of independent cognitive components which are both required for normal reading

Few studies straightforwardly addressed the question of amodal *attentional* processing deficits in dyslexia, since research interests have largely focused on the amodal *perceptual* deficit hypothesis. Disorders extending over several modalities, as expected by the SAS hypothesis, have then been reported (Meyler & Breznitz, 2005). However, a fair amount of data failed to highlight amodal rapid sequential processing disorders in dyslexic individuals, either because of the absence of deficit in the visual modality (e.g., Eddins & Green, 1995; Laasonen et al., 2001; Reed, 1989; Welch, DuttonHurt, & Warren, 1986) or because of the absence of deficits in both modalities (e.g., Bretherton & Holmes, 2003;

Such inconclusive results in the visual modality (as opposed to the auditory modality) could reflect the absence of causal role of visual sequential deficits in developmental dyslexia (see Skottun, 2000). They could also follow from the heterogeneity of the dyslexic population and lack of characterization of the cognitive deficits underlying the reading disorder of dyslexic participants at the individual level. Indeed, knowing that all cases of developmental dyslexia *are not* associated with phonological disorders (Bosse et al., 2007), performance may have been influenced by the heterogeneity of the phonological disorders in the dyslexic sample. In line with this hypothesis, Meyler and Breznitz (2005) who reported a phonological deficit in their dyslexic group did find an amodal sequential deficit

Differences in the choice of experimental paradigms could also have led to inconsistent results in the observation of amodal sequential deficits in dyslexia. In the original proposal of Tallal (1980), rapid temporal deficits were assessed with order or similarity judgment tasks composed of two stimuli only. Interestingly, the SAS hypothesis predicts deficits on

the causal link between SAS skills and phonological deficits in dyslexia.

**2.1 Amodal sequential and simultaneous processing deficits** 

**2.1.1 Sequential processing deficits** 

participants.

acquisition.

Laasonen et al., 2000).

in their dyslexic participants.

The role of amodal simultaneous processing in reading development has barely been studied. We are aware of only one study which tried to capture amodal simultaneous processing deficit in dyslexia. Geiger et al. (2008) administered to a group of dyslexic children two similar tasks, one in the visual modality, the other one in the auditory modality. In the visual modality, participants were asked to recognize letter stimuli presented in the center of a screen and ignore the letter stimuli in the periphery. In the auditory modality, they had to recognize auditory lexical stimuli presented via speakers located in front of participants (i.e., centrally) with or without the presence of auditory simultaneous peripheral lexical stimuli. Dyslexic children were found to exhibit difficulties in recognizing the central stimuli presented with external noise in both the auditory and the visual modalities. The authors concluded to a "wider perceptual mode" in the dyslexic children, which in turn may hinder their ability to focus on relevant stimuli and inhibit irrelevant information. Unfortunately, this study did not specify whether the assessed dyslexic children exhibited a phonological deficit, making impossible to determine whether such simultaneous processing deficits were found regardless of phonological deficits, as the VA Span hypothesis would predict.

#### **2.2 Assessing visual and auditory sequential and simultaneous deficits in relation to phonological and VA Span disorders in developmental dyslexia**

In the following section, we will present evidence that sequential and simultaneous disorders in developmental dyslexia can be found in the same dyslexic participants in both the visual and the auditory modalities. Moreover, we will argue that:


We first need to emphasize the fact that when investigating auditory and visual non-verbal attention or perception abilities, the underlying cognitive deficits of the dyslexic group should be precisely defined. This is critical in order to investigate the extent to which deficits in non-verbal abilities are linked and result to specific cognitive dyslexic symptoms (i.e., phonological or VA Span disorders). Disregarding this first step may lead to highly

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 91

Charbonneau, and Jolicoeur (2006) measured the phenomenon according to four parameters defining a curve fitting function (see Fig 4.b.): the duration parameter corresponds to the duration of the attentional blink, the amplitude parameter corresponds to the difference between the best and the worst performance and indicates the severity of the attentional blink, the minimum parameter corresponds to the worst performance, and lag-1 sparing parameter corresponds to the speed at which T1 processing starts to have a negative impact on T2 processing. The SAS hypothesis predicts a longer attentional blink duration in

Fig. 4. Representation of the typical pattern of performance obtained in attentional blink (a). When compared to the single task condition (black squares), performance on the dual task condition (white dots) drops for the first four positions of T2 after T1. The four attentional

Several studies have shown that dyslexic individuals exhibit a prolonged visual attentional blink (lasting in average 600-800 ms) as compared to normal readers (e.g., Hari, Valta, and Uutela, 1999b; Visser, Boden, & Giaschi, 2004; Facoetti, Ruffino, Peru, Paganoni, & Chelazzi, 2008). This finding suggests that T1 captures visual attention resources for longer time in dyslexic participants than in control participants. However, research conducted on the attentional blink in impaired readers has given rise to discrepant results and has been

Overall, previous studies conducted in dyslexic participants suffer from a lack of homogeneity regarding either the characterization of the cognitive deficit underlying dyslexia (i.e., phonological or VA Span disorder), or methodological aspects. Furthermore, although the attentional blink had been highlighted in the auditory modality (e.g., Vachon & Tremblay, 2008), no study had examined whether dyslexic participants presented an

In a first study (Lallier, Donnadieu, Berger, & Valdois, 2010a), we assessed the amodality assumption of the SAS hypothesis by administering two similar attentional blink tasks in the visual and the auditory modalities to a French dyslexic adult participant, LL, and a group of skilled reader adults. The neuropsychological assessment of LL revealed that this patient suffered from a phonological dyslexia as characterised by slowed pseudoword reading rate

blink parameters adapted from Cousineau et al. (2006) are presented in (b).

subject to criticisms (Badcock, Hogben, & Fletcher, 2008).

atypical attentional blink in this modality as in vision.

dyslexic participants with phonological disorders.

heterogeneous performance in the dyslexic group, hence inconsistent observations between studies.

So far, most of the studies aiming to assess sequential deficits in individuals with developmental dyslexia implicitly assumed that the dyslexic participants exhibited a phonological deficit. Furthermore, other studies which explicitly reported a phonological processing deficit based their diagnosis upon pseudoword reading difficulties (i.e., decoding or sub-lexical reading difficulties), but pseudoword reading does not only require phonological abilities but also engages visual attention (Bosse et al., 2007; Bosse & Valdois, 2009; Facoetti et al., 2006; Facoetti et al., 2010; Vidyasagar & Pammer, 2010).

A number of case studies have now been reported (Dubois et al., 2010; Peyrin, Lallier, Baciu, Démonet, Le Bas, & Valdois, In press; Valdois et al., 2003; Valdois et al., In press) showing that dyslexic individuals (adults or children) with a single VA Span deficit may suffer from poor pseudoword reading abilities (reading accuracy and/or reading speed) *in spite of* any difficulties in "pure auditory" phonological processing skills.

From these considerations, it appears critical to systematically base the diagnosis of phonological disorders in dyslexic patients on measures of auditory phonological processing rather than on decoding skills. This precaution alone can ensure avoiding the impact of visual attention on performance, which would no longer reflect the "phonological disorder" primarily targeted.

We therefore will present data from a series of studies suggesting that sequential attention skills preferentially relate to phonological (and not decoding) skills rather than VA Span skills. We chose two experimental paradigms - the attentional blink and the stream segregation paradigms - that we thought had a great sensitivity to capture the rapid sequential processing abilities required for reading acquisition development (presentation of multiple stimuli in rapid sequences). These two tasks are supposed to allow the evaluation of temporal automatic attention deployment via attentional shifting, i.e., the successive engagement and disengagement of the attentional focus over a sequence of multiple stimuli.

#### **2.2.1 Amodal sequential processing assessment: The attentional blink**

Hari and Renvall (2001) predict that a prolongation of the attentional dwell time (see section 1.1.3 for a definition) in all sensory modalities would result in developmental dyslexia. The attentional dwell time has been highlighted in rapid serial presentation paradigms (10 items/sec) requiring the identification and/or detection of two targets (T1 and T2) embedded in a series of distracters. When the two targets are present in the sequence, performance on T1 is high whereas performance on T2 is lower. This drop of T2 performance (also called the attentional blink) is all the more interesting that it varies according to its temporal position as regards the presentation of T1 (Raymond et al., 1992).

In attentional blink tasks, two conditions are generally used: a dual task condition (see white dots in Fig 4.a.) where participants have to identify T1 and detect the presence or absence of T2, and a single task condition (see black squares in Fig 4.a.) which serves as a baseline, and where T1 is absent and only T2 has to be detected. Results on this task show an attentional blink, which is typically observed during a temporal window of about 300-500 ms after T1 presentation. In order to characterize the attentional blink more accurately, Cousineau,

heterogeneous performance in the dyslexic group, hence inconsistent observations between

So far, most of the studies aiming to assess sequential deficits in individuals with developmental dyslexia implicitly assumed that the dyslexic participants exhibited a phonological deficit. Furthermore, other studies which explicitly reported a phonological processing deficit based their diagnosis upon pseudoword reading difficulties (i.e., decoding or sub-lexical reading difficulties), but pseudoword reading does not only require phonological abilities but also engages visual attention (Bosse et al., 2007; Bosse & Valdois,

A number of case studies have now been reported (Dubois et al., 2010; Peyrin, Lallier, Baciu, Démonet, Le Bas, & Valdois, In press; Valdois et al., 2003; Valdois et al., In press) showing that dyslexic individuals (adults or children) with a single VA Span deficit may suffer from poor pseudoword reading abilities (reading accuracy and/or reading speed) *in spite of* any

From these considerations, it appears critical to systematically base the diagnosis of phonological disorders in dyslexic patients on measures of auditory phonological processing rather than on decoding skills. This precaution alone can ensure avoiding the impact of visual attention on performance, which would no longer reflect the "phonological

We therefore will present data from a series of studies suggesting that sequential attention skills preferentially relate to phonological (and not decoding) skills rather than VA Span skills. We chose two experimental paradigms - the attentional blink and the stream segregation paradigms - that we thought had a great sensitivity to capture the rapid sequential processing abilities required for reading acquisition development (presentation of multiple stimuli in rapid sequences). These two tasks are supposed to allow the evaluation of temporal automatic attention deployment via attentional shifting, i.e., the successive engagement and disengagement of the attentional focus over a sequence of multiple stimuli.

Hari and Renvall (2001) predict that a prolongation of the attentional dwell time (see section 1.1.3 for a definition) in all sensory modalities would result in developmental dyslexia. The attentional dwell time has been highlighted in rapid serial presentation paradigms (10 items/sec) requiring the identification and/or detection of two targets (T1 and T2) embedded in a series of distracters. When the two targets are present in the sequence, performance on T1 is high whereas performance on T2 is lower. This drop of T2 performance (also called the attentional blink) is all the more interesting that it varies according to its temporal position as regards the presentation of T1 (Raymond et al., 1992). In attentional blink tasks, two conditions are generally used: a dual task condition (see white dots in Fig 4.a.) where participants have to identify T1 and detect the presence or absence of T2, and a single task condition (see black squares in Fig 4.a.) which serves as a baseline, and where T1 is absent and only T2 has to be detected. Results on this task show an attentional blink, which is typically observed during a temporal window of about 300-500 ms after T1 presentation. In order to characterize the attentional blink more accurately, Cousineau,

2009; Facoetti et al., 2006; Facoetti et al., 2010; Vidyasagar & Pammer, 2010).

**2.2.1 Amodal sequential processing assessment: The attentional blink** 

difficulties in "pure auditory" phonological processing skills.

disorder" primarily targeted.

studies.

Charbonneau, and Jolicoeur (2006) measured the phenomenon according to four parameters defining a curve fitting function (see Fig 4.b.): the duration parameter corresponds to the duration of the attentional blink, the amplitude parameter corresponds to the difference between the best and the worst performance and indicates the severity of the attentional blink, the minimum parameter corresponds to the worst performance, and lag-1 sparing parameter corresponds to the speed at which T1 processing starts to have a negative impact on T2 processing. The SAS hypothesis predicts a longer attentional blink duration in dyslexic participants with phonological disorders.

Fig. 4. Representation of the typical pattern of performance obtained in attentional blink (a). When compared to the single task condition (black squares), performance on the dual task condition (white dots) drops for the first four positions of T2 after T1. The four attentional blink parameters adapted from Cousineau et al. (2006) are presented in (b).

Several studies have shown that dyslexic individuals exhibit a prolonged visual attentional blink (lasting in average 600-800 ms) as compared to normal readers (e.g., Hari, Valta, and Uutela, 1999b; Visser, Boden, & Giaschi, 2004; Facoetti, Ruffino, Peru, Paganoni, & Chelazzi, 2008). This finding suggests that T1 captures visual attention resources for longer time in dyslexic participants than in control participants. However, research conducted on the attentional blink in impaired readers has given rise to discrepant results and has been subject to criticisms (Badcock, Hogben, & Fletcher, 2008).

Overall, previous studies conducted in dyslexic participants suffer from a lack of homogeneity regarding either the characterization of the cognitive deficit underlying dyslexia (i.e., phonological or VA Span disorder), or methodological aspects. Furthermore, although the attentional blink had been highlighted in the auditory modality (e.g., Vachon & Tremblay, 2008), no study had examined whether dyslexic participants presented an atypical attentional blink in this modality as in vision.

In a first study (Lallier, Donnadieu, Berger, & Valdois, 2010a), we assessed the amodality assumption of the SAS hypothesis by administering two similar attentional blink tasks in the visual and the auditory modalities to a French dyslexic adult participant, LL, and a group of skilled reader adults. The neuropsychological assessment of LL revealed that this patient suffered from a phonological dyslexia as characterised by slowed pseudoword reading rate

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 93

In a second study (Lallier, Donnadieu, & Valdois, 2010b), we used the curve fitting method of Cousineau et al. (2006) to quantify and better define the visual attentional blink deficit of dyslexic children. We further explored whether any parameter specifically related to their phonological disorder (Lallier et al., 2010b). Fourteen dyslexic children and 14 age-matched control children took part in the experiment. The dyslexic group was impaired in phonological short-term memory and showed marginally poor phoneme deletion skills but performed as well as the controls on the partial or whole report task, thus suggesting preserved VA Span skills (Lallier, 2009). All children were given the same visual attentional blink task as in Lallier et al (2010a). A group effect was revealed on the attentional blink minimum parameters, reflecting a lower minimum for the dyslexic group than the control group, but no difference regarding duration of the attentional blink. Correlation analyses on the whole sample revealed that the attentional blink minimum and amplitude parameters significantly correlated, and

that attentional blink amplitude was significantly related to phonemic deletion skills.

**2.2.2 Amodal sequential processing assessment: Stream segregation** 

parameters (Cousineau et al., 2006).

Noorden, 1975).

perceived.

patterns can occur (see Fig 6):

From these findings and previous other results, it seems that deficits in several attentional blink features (see Fig 4) could occur in the same dyslexic participants. Indeed, both atypical attentional blink "duration *and* minimum" (Facoetti et al., 2008; Hari et al., 1999) and "duration *and* amplitude" (Lallier et al., 2010a) have been reported in the same participants. Such result is *a priori* not surprising given the correlation reported between all three

To sum up, our two studies assessing sequential attention processing with attentional blink tasks in dyslexic participants showed that a visual sequential attention deficit can be found in the absence of any visual simultaneous attention disorder. Moreover, both auditory and visual SAS skills were preferentially associated with phonological deficits in developmental dyslexia.

In another series of studies we will present in this section, we used the experimental paradigm used for the assessment of stream segregation. Interestingly, stream segregation can be observed in the two modalities. In the auditory modality (Bey & McAdams, 2003), stream segregation occurs when sequences of auditory stimuli alternate in pitch/auditory frequency (e.g. high and low pitch tones). In the visual modality (Bregman & Achim, 1973), segregation occurs when sequences of visual stimuli alternate in spatial locations (e.g. visual dots appearing above and below fixation). The resulting percept depends on both temporal and auditory frequency/visual distance intervals between two successive stimuli (Van

For adequate auditory frequency/visual distance intervals, two perceptual temporal

i. When time interval is long enough, a unique auditory stream alternating high and low pitch tones (or a unique visual object composed of two dots bouncing up and down) is

ii. For short enough intervals, the participants perceive two different auditory streams, one high- and the other low-pitched (or two visual dots flickering in parallel).

Focusing on the temporal aspects of the phenomenon, auditory stream segregation has been assessed in dyslexia, showing that dyslexic individuals required longer ISIs to perceive the

and poor pseudoword spelling. LL further had poor pseudoword repetition and poor phoneme awareness skills, thus reflecting an underlying phonological disorder. On the contrary, LL showed normal simultaneous processing of letter strings on the whole and partial report tasks, thus suggesting preserved VA Span abilities.

The visual attentional blink task consisted in the rapid serial presentation of black digits. T1 was the only red digit in the stream and it was either 1 or 5. T2 was the digit 0 and was black like the distracters. The auditory attention blink task consisted in the rapid serial auditory presentation of sounds. Pure tones were used as distracters and a higher-pitched tone of 4000 Hz was used as T1 target. This tone was either a complex tone (sounding like a locust cry) or pure tone (sounding like a bird cry), giving rise to two distinct perceptions. T2 was a pure tone of 600 Hz belonging to the distracters' frequency range but it was delivered at a higher amplitude level (i.e., it was louder). In the dual task condition, participants were instructed to attend to and name T1 (1 or 5 digits; pure or complex tones) while judging whether T2 occurred or not (number 0; louder sound). For both the single and dual task conditions, we took into account eight T1-T2 lags in the analyses, i.e., from lag 1 (no intervening items, ISI = 60 ms) to lag 8 (ISI = 760 ms). For each of the visual and the auditory tasks, participants were instructed to name T1 and/or report aloud whether T2 was present or not, after each sequence was seen or heard.

Fig. 5. Visual (a.) and auditory (b.) attentional blinks in the control group (plain lines) and in LL (dotted lines) for the single task condition (black dots) and for the dual task condition (white dots). From Lallier et al., 2010a.

When LL's performance was compared to performance of skilled readers, it revealed atypical visual attentional blink duration and atypical auditory attentional blink amplitude (see Fig 5). Both atypical attentional blinks were interpreted as reflecting prolonged attentional dwell time, thus demonstrating amodal SAS skills in LL. Interestingly, this amodal disorder was reported in a dyslexic participant with a phonological disorder, in accordance with the SAS hypothesis. Moreover, the auditory and visual attentional blink deficits were found independently of any VA Span disorder, suggesting that sequential and simultaneous attention processing could dissociate and might independently contribute to developmental dyslexia.

and poor pseudoword spelling. LL further had poor pseudoword repetition and poor phoneme awareness skills, thus reflecting an underlying phonological disorder. On the contrary, LL showed normal simultaneous processing of letter strings on the whole and

The visual attentional blink task consisted in the rapid serial presentation of black digits. T1 was the only red digit in the stream and it was either 1 or 5. T2 was the digit 0 and was black like the distracters. The auditory attention blink task consisted in the rapid serial auditory presentation of sounds. Pure tones were used as distracters and a higher-pitched tone of 4000 Hz was used as T1 target. This tone was either a complex tone (sounding like a locust cry) or pure tone (sounding like a bird cry), giving rise to two distinct perceptions. T2 was a pure tone of 600 Hz belonging to the distracters' frequency range but it was delivered at a higher amplitude level (i.e., it was louder). In the dual task condition, participants were instructed to attend to and name T1 (1 or 5 digits; pure or complex tones) while judging whether T2 occurred or not (number 0; louder sound). For both the single and dual task conditions, we took into account eight T1-T2 lags in the analyses, i.e., from lag 1 (no intervening items, ISI = 60 ms) to lag 8 (ISI = 760 ms). For each of the visual and the auditory tasks, participants were instructed to name T1 and/or report aloud whether T2 was present

Fig. 5. Visual (a.) and auditory (b.) attentional blinks in the control group (plain lines) and in LL (dotted lines) for the single task condition (black dots) and for the dual task condition

When LL's performance was compared to performance of skilled readers, it revealed atypical visual attentional blink duration and atypical auditory attentional blink amplitude (see Fig 5). Both atypical attentional blinks were interpreted as reflecting prolonged attentional dwell time, thus demonstrating amodal SAS skills in LL. Interestingly, this amodal disorder was reported in a dyslexic participant with a phonological disorder, in accordance with the SAS hypothesis. Moreover, the auditory and visual attentional blink deficits were found independently of any VA Span disorder, suggesting that sequential and simultaneous attention processing could dissociate and might independently contribute to

partial report tasks, thus suggesting preserved VA Span abilities.

or not, after each sequence was seen or heard.

(white dots). From Lallier et al., 2010a.

developmental dyslexia.

In a second study (Lallier, Donnadieu, & Valdois, 2010b), we used the curve fitting method of Cousineau et al. (2006) to quantify and better define the visual attentional blink deficit of dyslexic children. We further explored whether any parameter specifically related to their phonological disorder (Lallier et al., 2010b). Fourteen dyslexic children and 14 age-matched control children took part in the experiment. The dyslexic group was impaired in phonological short-term memory and showed marginally poor phoneme deletion skills but performed as well as the controls on the partial or whole report task, thus suggesting preserved VA Span skills (Lallier, 2009). All children were given the same visual attentional blink task as in Lallier et al (2010a). A group effect was revealed on the attentional blink minimum parameters, reflecting a lower minimum for the dyslexic group than the control group, but no difference regarding duration of the attentional blink. Correlation analyses on the whole sample revealed that the attentional blink minimum and amplitude parameters significantly correlated, and that attentional blink amplitude was significantly related to phonemic deletion skills.

From these findings and previous other results, it seems that deficits in several attentional blink features (see Fig 4) could occur in the same dyslexic participants. Indeed, both atypical attentional blink "duration *and* minimum" (Facoetti et al., 2008; Hari et al., 1999) and "duration *and* amplitude" (Lallier et al., 2010a) have been reported in the same participants. Such result is *a priori* not surprising given the correlation reported between all three parameters (Cousineau et al., 2006).

To sum up, our two studies assessing sequential attention processing with attentional blink tasks in dyslexic participants showed that a visual sequential attention deficit can be found in the absence of any visual simultaneous attention disorder. Moreover, both auditory and visual SAS skills were preferentially associated with phonological deficits in developmental dyslexia.

#### **2.2.2 Amodal sequential processing assessment: Stream segregation**

In another series of studies we will present in this section, we used the experimental paradigm used for the assessment of stream segregation. Interestingly, stream segregation can be observed in the two modalities. In the auditory modality (Bey & McAdams, 2003), stream segregation occurs when sequences of auditory stimuli alternate in pitch/auditory frequency (e.g. high and low pitch tones). In the visual modality (Bregman & Achim, 1973), segregation occurs when sequences of visual stimuli alternate in spatial locations (e.g. visual dots appearing above and below fixation). The resulting percept depends on both temporal and auditory frequency/visual distance intervals between two successive stimuli (Van Noorden, 1975).

For adequate auditory frequency/visual distance intervals, two perceptual temporal patterns can occur (see Fig 6):


Focusing on the temporal aspects of the phenomenon, auditory stream segregation has been assessed in dyslexia, showing that dyslexic individuals required longer ISIs to perceive the

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 95

results suggest a strong link between reading skills and auditory stream segregation thresholds and consequently, between reading skills and auditory automatic attention shifting, which was also supported by correlation analyses. In the visual modality no

Fig. 7. Mean auditory and visual stream segregation thresholds (average ISI on the last 10 trials) together with standard error bars in children (a.; dyslexic readers, black dots; poor readers, white squares; good readers, white dots) and adults (b.; dyslexic readers, black

The second experiment (see Fig 7.b) was carried out with 10 skilled readers and 10 dyslexic young adults. As a whole, the dyslexic group showed difficulties in performing a spoonerism task, reflecting poor phonological awareness skills. Furthermore, the group presented a VA Span disorder as compared to controls, illustrated by difficulties on both the whole and the partial report tasks (Lallier, 2009). Results on the two stream segregation tasks showed that dyslexic adults obtained auditory and visual higher stream segregation thresholds as compared to the control group: this means that they needed more time than the control individuals between successive stimuli, i.e., longer ISIs, in order to perceive them as single entities. The results on both the visual and the auditory task thus reflected amodal SAS skills in the dyslexic group. In addition, significant relationships were found in the whole group of participants (dyslexic and control individuals) between SAS, poor reading and poor phonological skills, even after controlling for non-verbal IQ and chronological age. No such relation was found between VA Span skills and visual or auditory stream

Overall, the results of the two experiments of Lallier et al. (2009) with children and adults support the view that auditory SAS impacts on phonological abilities, and plays a role in developmental dyslexia. In addition, the comparison between children and adult results

dots; skilled readers, white dots). Adapted from Lallier et al. 2009.

segregation thresholds (Lallier, 2009).

difference was reported between any of the groups (see Fig 7.a., bottom graph).

one unique auditory stream (i.e., the alternation of two distinct sounds) as compared to skilled readers. Hari and Renvall (2001) interpreted this result as evidence for auditory SAS skills in individuals with developmental dyslexia.

In the following series of experiments, we used the paradigms of Helenius et al. (1999) in the auditory modality, and designed a similar paradigm to assess stream segregation skills in the visual modality. For both tasks, we measured stream segregation thresholds according to an adaptive procedure that allows varying the ISI between the successive stimuli in the sequences according to the answer/perception of participants ("one stream", cf Fig 6.a., or "two streams", cf Fig 6.b.).

Fig. 6. Schematic representation of the stream segregation procedure. The dotted arrows symbolise the one stream (a., longer ISIs) or two streams (b., shorter ISIs) conditions. From Lallier et al. 2010c.

Stream segregation thresholds correspond to the ISI for which participants cannot straightforwardly decide if they perceive one stream or two streams of stimuli, corresponding to a response "at chance".

We interpreted stream segregation thresholds as an estimation of the fastest speed at which attention could engage and disengage automatically from one stimulus to another in order to perceive them as independent entities.

The first study (Lallier et al., 2009) combined two experiments: one with children, one with adults. In the first experiment, we tested 36 children on both the visual and the auditory stream segregation tasks. Twelve children were diagnosed as dyslexic and, as a group, showed a phonological impairment (phoneme deletion and phonological short term memory) together with a mild VA Span disorder illustrated by a deficit on the whole report task but not on the partial report task (Lallier, 2009). The other participants were either skilled readers (12 children) or poor readers (12 children). The three groups of children were matched for chronological age but significantly differed between each other on their reading skills.

Results on the segregation tasks showed that dyslexic children exhibited higher auditory thresholds than the two other groups of non dyslexic readers, suggesting SAS skills in the dyslexic group as compared to the non dyslexic groups (see Fig 7.a., top graph). Furthermore, poor readers exhibited a higher auditory threshold than skilled readers. Such

one unique auditory stream (i.e., the alternation of two distinct sounds) as compared to skilled readers. Hari and Renvall (2001) interpreted this result as evidence for auditory SAS

In the following series of experiments, we used the paradigms of Helenius et al. (1999) in the auditory modality, and designed a similar paradigm to assess stream segregation skills in the visual modality. For both tasks, we measured stream segregation thresholds according to an adaptive procedure that allows varying the ISI between the successive stimuli in the sequences according to the answer/perception of participants ("one stream", cf Fig 6.a., or

Fig. 6. Schematic representation of the stream segregation procedure. The dotted arrows symbolise the one stream (a., longer ISIs) or two streams (b., shorter ISIs) conditions. From

Stream segregation thresholds correspond to the ISI for which participants cannot straightforwardly decide if they perceive one stream or two streams of stimuli,

We interpreted stream segregation thresholds as an estimation of the fastest speed at which attention could engage and disengage automatically from one stimulus to another in order

The first study (Lallier et al., 2009) combined two experiments: one with children, one with adults. In the first experiment, we tested 36 children on both the visual and the auditory stream segregation tasks. Twelve children were diagnosed as dyslexic and, as a group, showed a phonological impairment (phoneme deletion and phonological short term memory) together with a mild VA Span disorder illustrated by a deficit on the whole report task but not on the partial report task (Lallier, 2009). The other participants were either skilled readers (12 children) or poor readers (12 children). The three groups of children were matched for chronological age but significantly differed between each other on their reading

Results on the segregation tasks showed that dyslexic children exhibited higher auditory thresholds than the two other groups of non dyslexic readers, suggesting SAS skills in the dyslexic group as compared to the non dyslexic groups (see Fig 7.a., top graph). Furthermore, poor readers exhibited a higher auditory threshold than skilled readers. Such

skills in individuals with developmental dyslexia.

"two streams", cf Fig 6.b.).

Lallier et al. 2010c.

skills.

corresponding to a response "at chance".

to perceive them as independent entities.

results suggest a strong link between reading skills and auditory stream segregation thresholds and consequently, between reading skills and auditory automatic attention shifting, which was also supported by correlation analyses. In the visual modality no difference was reported between any of the groups (see Fig 7.a., bottom graph).

Fig. 7. Mean auditory and visual stream segregation thresholds (average ISI on the last 10 trials) together with standard error bars in children (a.; dyslexic readers, black dots; poor readers, white squares; good readers, white dots) and adults (b.; dyslexic readers, black dots; skilled readers, white dots). Adapted from Lallier et al. 2009.

The second experiment (see Fig 7.b) was carried out with 10 skilled readers and 10 dyslexic young adults. As a whole, the dyslexic group showed difficulties in performing a spoonerism task, reflecting poor phonological awareness skills. Furthermore, the group presented a VA Span disorder as compared to controls, illustrated by difficulties on both the whole and the partial report tasks (Lallier, 2009). Results on the two stream segregation tasks showed that dyslexic adults obtained auditory and visual higher stream segregation thresholds as compared to the control group: this means that they needed more time than the control individuals between successive stimuli, i.e., longer ISIs, in order to perceive them as single entities. The results on both the visual and the auditory task thus reflected amodal SAS skills in the dyslexic group. In addition, significant relationships were found in the whole group of participants (dyslexic and control individuals) between SAS, poor reading and poor phonological skills, even after controlling for non-verbal IQ and chronological age. No such relation was found between VA Span skills and visual or auditory stream segregation thresholds (Lallier, 2009).

Overall, the results of the two experiments of Lallier et al. (2009) with children and adults support the view that auditory SAS impacts on phonological abilities, and plays a role in developmental dyslexia. In addition, the comparison between children and adult results

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 97

stream segregation tasks. These three groups included (i) a group of nine skilled reader adults, (ii) a group of nine dyslexic adults each of whom exhibited a phonological deficit at the individual level (i.e., impaired on three phonological measures out of five, among phonological working memory, phonological fluency, phonemic deletion, and spoonerism time and accuracy), and (iii) nine dyslexic adults without any phonological deficit. Regarding visual attention performance, the two dyslexic groups showed a significant VA Span deficit on the whole report task as compared to the controls. On the partial report task, the three groups of participants showed similar scores (Lallier et al., In progress b). Importantly, the three groups were matched for non-verbal IQ and chronological age, and the two dyslexic groups were matched for general reading and spelling abilities. Therefore, we were in presence of a relatively pure phonological dyslexic group, and a nonphonological dyslexic group with a VA Span disorder. In line with the hypothesis of a dissociation between phonological *versus* VA Span disorder and sequential *versus* simultaneous attention deficits in developmental dyslexia, only the dyslexic group with a phonological disorder exhibited higher auditory and marginally higher visual stream

segregation thresholds as compared to the control group (see Fig 8).

Fig. 8. Visual (a.) and auditory (b.) stream segregation thresholds together with standard error bars in the dyslexic group with a phonological disorder (black dots), the dyslexic group without phonological disorder (grey dots) and the control group (white dots).

Importantly, auditory thresholds significantly differed between the two dyslexic groups. Looking at individual performance, 78% of participants with a phonological disorder (*versus* 11% without) were impaired on the auditory stream segregation task and 33% (*versus* 11%) on the visual task. These results strongly support the hypothesis of a link between auditory (and visual, but to a lesser extent) sequential deficits, impaired phonology, and reading disorders, but do not suggest any link between VA Span disorder and auditory or visual

In order to obtain a complete picture of the contribution of sequential and simultaneous skills to reading difficulties in the dyslexic population regarding auditory processing, we designed a task that we considered to be a reasonable auditory counterpart of the visual whole report task (Lallier, Donnadieu, & Valdois, Under Review a). That way, we aimed to

Adapted from Lallier et al., Under Review b, and Lallier et al., In progress b.

**2.2.3 Amodal simultaneous processing assessment: Dichotic listening** 

SAS in developmental dyslexia.

suggests that a visual sequential disorder in dyslexia might emerge at a later developmental stage, when the visual system normally becomes more expert at rapid temporal processing.

In the second study (Lallier et al., 2010c), we quantified both auditory and visual stream segregation thresholds in 13 dyslexic young adults with a phonological awareness deficit as a group (poor performance on phonemic deletion and spoonerisms) and 13 control participants, matched for cognitive abilities. Consistent with Lallier et al. (2009), we found higher auditory and visual stream segregation thresholds in the dyslexic group as compared to the controls, thus evidence for amodal SAS skills. We then used electrophysiological measures allowing us to capture the electric activity produced naturally by the brain, to determine to what extent brain responses of these dyslexic participants would reflect their atypical perception of visual and auditory stimulus sequences. For the electrophysiological experiment, the auditory and visual sequences administered to the participants varied according to different tempos that were carefully chosen based on preliminarily obtained thresholds. Participants were presented with blocks of 4 min-long sequences of either the same auditory or the same visual stimuli as those used in the stream segregation tasks, whilst their brain responses were recorded by electroencephalography (i.e., EEG). They were asked to press a button as soon as they perceived a change in the speed of stimulus alternation, and were not told or asked anything about the perception of unique or distinct streams. Electrophysiological brain responses were recorded during the task, and interpreted as an index of stimulus sequence perception. Results showed that dyslexic participants presented atypical auditory and visual brain responses to tempos variations within stimulus sequences as compared to controls.

Overall, these results strongly support the hypothesis that SAS in dyslexic participants might be responsible for their atypical perception of rapid sequential stimulus sequences in both the auditory and the visual modalities. In the auditory modality, the atypical brain response elicited by rapid stimulus sequences is likely to index the atypical perception of auditory speech streams in dyslexic participants with a phonological disorder. In the visual modality, such abnormal rapid stimulus sequences perception could well relate to difficulties encountered by dyslexic participants in rapidly shifting their attention along the orthographic sequences composing texts (Hari & Renvall, 2001). The direct links between stream segregation tasks and speech and orthographic strings processing still need to be investigated. Furthermore, our results bring new evidence supporting the link between amodal SAS and the phonological impairment in developmental dyslexia.

In our previous studies evaluating attentional blink or stream segregation performance in dyslexic individuals, links between sequential attention deficits and the phonological and VA Span disorders were studied by means of correlation analyses carried out on the whole sample of participants (i.e., including both dyslexic and skilled readers), a choice that may raise some methodological concerns. Furthermore, phonological and VA Span disorders were always defined regarding the whole group of dyslexic participants (except for Lallier et al., 2010a).

The next study conducted in adults (Lallier, Thierry, & Tainturier, Under Review b; Lallier, Thierry, Valdois & Tainturier, In progress b) was conducted in order to ascertain the relationships between amodal SAS skills and both phonological and VA Span disorders in a more stringent way. We examined performance of three groups of participants on the

suggests that a visual sequential disorder in dyslexia might emerge at a later developmental stage, when the visual system normally becomes more expert at rapid temporal processing. In the second study (Lallier et al., 2010c), we quantified both auditory and visual stream segregation thresholds in 13 dyslexic young adults with a phonological awareness deficit as a group (poor performance on phonemic deletion and spoonerisms) and 13 control participants, matched for cognitive abilities. Consistent with Lallier et al. (2009), we found higher auditory and visual stream segregation thresholds in the dyslexic group as compared to the controls, thus evidence for amodal SAS skills. We then used electrophysiological measures allowing us to capture the electric activity produced naturally by the brain, to determine to what extent brain responses of these dyslexic participants would reflect their atypical perception of visual and auditory stimulus sequences. For the electrophysiological experiment, the auditory and visual sequences administered to the participants varied according to different tempos that were carefully chosen based on preliminarily obtained thresholds. Participants were presented with blocks of 4 min-long sequences of either the same auditory or the same visual stimuli as those used in the stream segregation tasks, whilst their brain responses were recorded by electroencephalography (i.e., EEG). They were asked to press a button as soon as they perceived a change in the speed of stimulus alternation, and were not told or asked anything about the perception of unique or distinct streams. Electrophysiological brain responses were recorded during the task, and interpreted as an index of stimulus sequence perception. Results showed that dyslexic participants presented atypical auditory and visual brain responses to tempos variations

Overall, these results strongly support the hypothesis that SAS in dyslexic participants might be responsible for their atypical perception of rapid sequential stimulus sequences in both the auditory and the visual modalities. In the auditory modality, the atypical brain response elicited by rapid stimulus sequences is likely to index the atypical perception of auditory speech streams in dyslexic participants with a phonological disorder. In the visual modality, such abnormal rapid stimulus sequences perception could well relate to difficulties encountered by dyslexic participants in rapidly shifting their attention along the orthographic sequences composing texts (Hari & Renvall, 2001). The direct links between stream segregation tasks and speech and orthographic strings processing still need to be investigated. Furthermore, our results bring new evidence supporting the link between

In our previous studies evaluating attentional blink or stream segregation performance in dyslexic individuals, links between sequential attention deficits and the phonological and VA Span disorders were studied by means of correlation analyses carried out on the whole sample of participants (i.e., including both dyslexic and skilled readers), a choice that may raise some methodological concerns. Furthermore, phonological and VA Span disorders were always defined regarding the whole group of dyslexic participants (except for Lallier

The next study conducted in adults (Lallier, Thierry, & Tainturier, Under Review b; Lallier, Thierry, Valdois & Tainturier, In progress b) was conducted in order to ascertain the relationships between amodal SAS skills and both phonological and VA Span disorders in a more stringent way. We examined performance of three groups of participants on the

amodal SAS and the phonological impairment in developmental dyslexia.

within stimulus sequences as compared to controls.

et al., 2010a).

stream segregation tasks. These three groups included (i) a group of nine skilled reader adults, (ii) a group of nine dyslexic adults each of whom exhibited a phonological deficit at the individual level (i.e., impaired on three phonological measures out of five, among phonological working memory, phonological fluency, phonemic deletion, and spoonerism time and accuracy), and (iii) nine dyslexic adults without any phonological deficit. Regarding visual attention performance, the two dyslexic groups showed a significant VA Span deficit on the whole report task as compared to the controls. On the partial report task, the three groups of participants showed similar scores (Lallier et al., In progress b). Importantly, the three groups were matched for non-verbal IQ and chronological age, and the two dyslexic groups were matched for general reading and spelling abilities. Therefore, we were in presence of a relatively pure phonological dyslexic group, and a nonphonological dyslexic group with a VA Span disorder. In line with the hypothesis of a dissociation between phonological *versus* VA Span disorder and sequential *versus* simultaneous attention deficits in developmental dyslexia, only the dyslexic group with a phonological disorder exhibited higher auditory and marginally higher visual stream segregation thresholds as compared to the control group (see Fig 8).

Fig. 8. Visual (a.) and auditory (b.) stream segregation thresholds together with standard error bars in the dyslexic group with a phonological disorder (black dots), the dyslexic group without phonological disorder (grey dots) and the control group (white dots). Adapted from Lallier et al., Under Review b, and Lallier et al., In progress b.

Importantly, auditory thresholds significantly differed between the two dyslexic groups. Looking at individual performance, 78% of participants with a phonological disorder (*versus* 11% without) were impaired on the auditory stream segregation task and 33% (*versus* 11%) on the visual task. These results strongly support the hypothesis of a link between auditory (and visual, but to a lesser extent) sequential deficits, impaired phonology, and reading disorders, but do not suggest any link between VA Span disorder and auditory or visual SAS in developmental dyslexia.

#### **2.2.3 Amodal simultaneous processing assessment: Dichotic listening**

In order to obtain a complete picture of the contribution of sequential and simultaneous skills to reading difficulties in the dyslexic population regarding auditory processing, we designed a task that we considered to be a reasonable auditory counterpart of the visual whole report task (Lallier, Donnadieu, & Valdois, Under Review a). That way, we aimed to

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 99

Span skills correlated positively with dichotic listening scores while phonological skills did not correlate with either dichotic or VA Span measures. All the dyslexic children with a dichotic listening deficit showed a VA Span disorder, but the VA Span disorder was not systematically associated with poor dichotic listening. A high proportion of dyslexic children exhibited a phonological short-term memory or a phonemic awareness deficit whether or not they had difficulties on the dichotic listening task. Our findings suggest that processing simultaneous auditory stimuli in developmental dyslexia may be impaired regardless of any phonological deficit and be linked to similar difficulties in the visual

This chapter aimed to clarify the nature of the temporal dimension of processing (sequential or simultaneous) relevant for the study of visual and auditory deficits (verbal or non-verbal) in developmental dyslexia. First, our review of the available data suggests that processes tapping into automatic attention mechanisms may be likely to highlight critical links between auditory and visual deficits and reading disorders. Second, our series of experiments provides new evidence for a potential dissociation between sequential and simultaneous processing deficits in developmental dyslexia and their respective links to distinct cognitive dyslexic profiles (VA Span and phonological disorders): when auditory automatic attentional shifting speed seems to clearly contribute to phonological processing (phonological awareness and phonological short-term memory in particular), the link between similar visual measures and reading is weaker, as previously suggested in the literature (e.g., Skottun, 2000). Our data further suggests that visual simultaneous disorders could extend over the auditory modality in participants with dyslexia regardless of their

**3.1 The role of sequential** *versus* **simultaneous amodal attention processing in** 

When looking at what reading is, it seems obvious that both the auditory and visual perceptual-attentional systems have an important role to play. In their theoretical account integrating auditory and visual networks together with their role in developmental dyslexia, Pammer and Vidyasagar (2005) suggest that automatic spatial attentional orientation and focalization are the amodal mechanisms playing a fundamental role in reading acquisition. In the visual modality, such mechanisms would be in charge of screening and encoding at a pre-orthographic level the visual letter strings, such as coding letter positions within the string (e.g., Pammer, Lavis, Hansen, & Cornelissen, 2004), in order to facilitate grapheme-tophoneme conversion rules acquisition. In the auditory modality, similar attentional mechanisms would be required to encode speech units to form adequate phonological

In the present chapter, we proposed that auditory and visual mechanisms engaged in reading acquisition require both sequential and simultaneous processes to encode phonological and orthographic inputs. The first one, a sequential attention mechanism, would lead the attentional focus to rapidly and automatically engage and disengage over speech streams and orthographic sequences, whilst being guided by salient and relevant cues (syllabic stress, Goswami, 2011; or visual syllable, Ans et al., 1998). The second one

modality.

**3. Conclusion** 

phonological skills.

representations (Hari & Renvall, 2001).

**reading** 

assess the amodality of simultaneous attention in dyslexic children. We chose a dichotic listening paradigm (Cherry, 1953) which has broadly been used to assess simultaneous auditory attention (e.g., Asbjörnsen & Hugdahl, 1995). In dichotic tasks, different auditory sources of information are simultaneously displayed in the two ears. As opposed to the *focal*  attention condition where participants have to report the stimuli presented in one ear only, the *non focal* attention reflect the performance of participants when they have to report the stimuli presented in the two ears. The latter condition makes the participants allocate their attention resources in parallel to the two ears and indexes some attention resources limitation. We measured the report scores of participants in the latter condition in order to quantify their simultaneous auditory attention abilities.

Fig. 9. Illustration of the dichotic listening task we used to assess simultaneous attention resources. From Lallier et al., Under Review a.

The dichotic sequences were composed of three syllables sequentially presented in the right ear and of three different syllables sequentially presented in the left ear (see Fig 9). More importantly, the two series of syllables were carefully synchronized so that participants had to process pairs of syllables simultaneously presented in the two ears. They were instructed to listen carefully to the syllables presented in their right ear and in their left ear and to report as many syllables as possible from both sides.

Because auditory syllables were used as stimuli, relations between dichotic performance and phonological processes were likely to be shown. We therefore assessed VA Span abilities, phoneme awareness skills and phonological short-term memory in dyslexic children together with their dichotic listening performance. We reasoned that if phonological and VA Span skills play different roles in reading acquisition and are respectively associated with sequential and simultaneous processes (Lallier et al., 2010a), performance on a task requiring a high degree of simultaneous resource allocation should fail to, or only weakly, relate to phonological skills, even when participants are presented with phonological stimuli. However, if poor dichotic listening performance is mainly driven by simultaneous processing difficulties and if the simultaneous processing disorder is amodal, then dyslexic children with a VA Span disorder should perform poorly on the dichotic listening task *whether or not* they exhibit associated phonological deficits. On the other hand, if dichotic listening poor performance is determined by difficulties in phonological/sequential processing abilities, then individuals with phonological deficits should perform poorly on the dichotic listening task regardless of their VA Span skills.

We assessed the dichotic listening performance of 17 dyslexic children and 17 skilled readers. Results showed that the dyslexic group exhibited difficulties in reporting the simultaneous syllables as compared to the controls. Moreover, in the dyslexic group, VA Span skills correlated positively with dichotic listening scores while phonological skills did not correlate with either dichotic or VA Span measures. All the dyslexic children with a dichotic listening deficit showed a VA Span disorder, but the VA Span disorder was not systematically associated with poor dichotic listening. A high proportion of dyslexic children exhibited a phonological short-term memory or a phonemic awareness deficit whether or not they had difficulties on the dichotic listening task. Our findings suggest that processing simultaneous auditory stimuli in developmental dyslexia may be impaired regardless of any phonological deficit and be linked to similar difficulties in the visual modality.

#### **3. Conclusion**

98 Dyslexia – A Comprehensive and International Approach

assess the amodality of simultaneous attention in dyslexic children. We chose a dichotic listening paradigm (Cherry, 1953) which has broadly been used to assess simultaneous auditory attention (e.g., Asbjörnsen & Hugdahl, 1995). In dichotic tasks, different auditory sources of information are simultaneously displayed in the two ears. As opposed to the *focal*  attention condition where participants have to report the stimuli presented in one ear only, the *non focal* attention reflect the performance of participants when they have to report the stimuli presented in the two ears. The latter condition makes the participants allocate their attention resources in parallel to the two ears and indexes some attention resources limitation. We measured the report scores of participants in the latter condition in order to

Fig. 9. Illustration of the dichotic listening task we used to assess simultaneous attention

The dichotic sequences were composed of three syllables sequentially presented in the right ear and of three different syllables sequentially presented in the left ear (see Fig 9). More importantly, the two series of syllables were carefully synchronized so that participants had to process pairs of syllables simultaneously presented in the two ears. They were instructed to listen carefully to the syllables presented in their right ear and in their left ear and to

Because auditory syllables were used as stimuli, relations between dichotic performance and phonological processes were likely to be shown. We therefore assessed VA Span abilities, phoneme awareness skills and phonological short-term memory in dyslexic children together with their dichotic listening performance. We reasoned that if phonological and VA Span skills play different roles in reading acquisition and are respectively associated with sequential and simultaneous processes (Lallier et al., 2010a), performance on a task requiring a high degree of simultaneous resource allocation should fail to, or only weakly, relate to phonological skills, even when participants are presented with phonological stimuli. However, if poor dichotic listening performance is mainly driven by simultaneous processing difficulties and if the simultaneous processing disorder is amodal, then dyslexic children with a VA Span disorder should perform poorly on the dichotic listening task *whether or not* they exhibit associated phonological deficits. On the other hand, if dichotic listening poor performance is determined by difficulties in phonological/sequential processing abilities, then individuals with phonological deficits should perform poorly on

We assessed the dichotic listening performance of 17 dyslexic children and 17 skilled readers. Results showed that the dyslexic group exhibited difficulties in reporting the simultaneous syllables as compared to the controls. Moreover, in the dyslexic group, VA

quantify their simultaneous auditory attention abilities.

resources. From Lallier et al., Under Review a.

report as many syllables as possible from both sides.

the dichotic listening task regardless of their VA Span skills.

This chapter aimed to clarify the nature of the temporal dimension of processing (sequential or simultaneous) relevant for the study of visual and auditory deficits (verbal or non-verbal) in developmental dyslexia. First, our review of the available data suggests that processes tapping into automatic attention mechanisms may be likely to highlight critical links between auditory and visual deficits and reading disorders. Second, our series of experiments provides new evidence for a potential dissociation between sequential and simultaneous processing deficits in developmental dyslexia and their respective links to distinct cognitive dyslexic profiles (VA Span and phonological disorders): when auditory automatic attentional shifting speed seems to clearly contribute to phonological processing (phonological awareness and phonological short-term memory in particular), the link between similar visual measures and reading is weaker, as previously suggested in the literature (e.g., Skottun, 2000). Our data further suggests that visual simultaneous disorders could extend over the auditory modality in participants with dyslexia regardless of their phonological skills.

#### **3.1 The role of sequential** *versus* **simultaneous amodal attention processing in reading**

When looking at what reading is, it seems obvious that both the auditory and visual perceptual-attentional systems have an important role to play. In their theoretical account integrating auditory and visual networks together with their role in developmental dyslexia, Pammer and Vidyasagar (2005) suggest that automatic spatial attentional orientation and focalization are the amodal mechanisms playing a fundamental role in reading acquisition. In the visual modality, such mechanisms would be in charge of screening and encoding at a pre-orthographic level the visual letter strings, such as coding letter positions within the string (e.g., Pammer, Lavis, Hansen, & Cornelissen, 2004), in order to facilitate grapheme-tophoneme conversion rules acquisition. In the auditory modality, similar attentional mechanisms would be required to encode speech units to form adequate phonological representations (Hari & Renvall, 2001).

In the present chapter, we proposed that auditory and visual mechanisms engaged in reading acquisition require both sequential and simultaneous processes to encode phonological and orthographic inputs. The first one, a sequential attention mechanism, would lead the attentional focus to rapidly and automatically engage and disengage over speech streams and orthographic sequences, whilst being guided by salient and relevant cues (syllabic stress, Goswami, 2011; or visual syllable, Ans et al., 1998). The second one

Sequential *Versus* Simultaneous Processing Deficits in Developmental Dyslexia 101

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would be a simultaneous attention mechanism: because in real life situations the attended auditory and visual inputs very rarely correspond to one single small unit (such as a letter isolated on a blank page or a single phoneme presented in a quiet environment), simultaneous processing resources are required in order to integrate (VA Span hypothesis) or inhibit (noise exclusion deficit hypothesis, Sperling, Manis, & Seidenberg, 2005) all pieces of information presented at the same time (e.g., multi-letter strings or multi-speaker environments). Future studies will seek to determine to what extent these two mechanisms in charge of processing multiple inputs presented simultaneously (i.e., integrating *versus* filtering/inhibiting) contribute to literacy acquisition, and possibly independently of each other.

#### **3.2 The hypothesis of different independent time scales auditory and visual processing and reading development?**

Poeppel (2003) suggested that two types of time scales for auditory processing are relevant and important for language acquisition: one would be handled by a very high oscillatory auditory system, whereas the other would be linked to a low oscillatory auditory system. Interestingly, the latter could possibly relate to sequential processing, whereas the former could be more tightly related to the "simultaneous" dimension of processing which would in this case correspond to a sequential processing at very high rate. Future studies will aim to clarify whether these two time scales of processing could extend over the visual domain, and to what extent they would impact on reading acquisition. Moreover, it will be necessary to examine whether these two time scales of processing have different and possibly independent roles in literacy acquisition, and lead to different subtypes of developmental dyslexia.

#### **4. Acknowledgment**

The research presented in this chapter was funded by grants from the French "Ministère de l'Enseignement Supérieur et de la Recherche", the Fyssen foundation (postdoctoral fellowship) and the European commission (Marie Curie fellowship, FP7, people, BIRD project) attributed to M. Lallier. We thank all the dyslexic children and adults who took part in our studies and to Dr Catherine Billard, Andrea Reynolds, Polly Barr and Céline Prévost for their help in recruiting and testing the participants. We are very grateful to Dr Marie-Josèphe Tainturier, Prof Guillaume Thierry and Dr Sophie Donnadieu for their valuable help in this research.

#### **5. References**


would be a simultaneous attention mechanism: because in real life situations the attended auditory and visual inputs very rarely correspond to one single small unit (such as a letter isolated on a blank page or a single phoneme presented in a quiet environment), simultaneous processing resources are required in order to integrate (VA Span hypothesis) or inhibit (noise exclusion deficit hypothesis, Sperling, Manis, & Seidenberg, 2005) all pieces of information presented at the same time (e.g., multi-letter strings or multi-speaker environments). Future studies will seek to determine to what extent these two mechanisms in charge of processing multiple inputs presented simultaneously (i.e., integrating *versus* filtering/inhibiting) contribute to literacy acquisition, and possibly independently of each

**3.2 The hypothesis of different independent time scales auditory and visual** 

Poeppel (2003) suggested that two types of time scales for auditory processing are relevant and important for language acquisition: one would be handled by a very high oscillatory auditory system, whereas the other would be linked to a low oscillatory auditory system. Interestingly, the latter could possibly relate to sequential processing, whereas the former could be more tightly related to the "simultaneous" dimension of processing which would in this case correspond to a sequential processing at very high rate. Future studies will aim to clarify whether these two time scales of processing could extend over the visual domain, and to what extent they would impact on reading acquisition. Moreover, it will be necessary to examine whether these two time scales of processing have different and possibly independent roles in literacy acquisition, and lead to different subtypes of developmental

The research presented in this chapter was funded by grants from the French "Ministère de l'Enseignement Supérieur et de la Recherche", the Fyssen foundation (postdoctoral fellowship) and the European commission (Marie Curie fellowship, FP7, people, BIRD project) attributed to M. Lallier. We thank all the dyslexic children and adults who took part in our studies and to Dr Catherine Billard, Andrea Reynolds, Polly Barr and Céline Prévost for their help in recruiting and testing the participants. We are very grateful to Dr Marie-Josèphe Tainturier, Prof Guillaume Thierry and Dr Sophie Donnadieu for their valuable

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**7** 

*UK* 

Diane Montgomery

**The Contribution of Handwriting and Spelling** 

*Middlesex University, London and Learning Difficulties Research Project, Essex,* 

This research details results of casework, interviews, observations and case history analysis of over 1000 dyslexics and those in schools who have not been referred. Their skills have

Subjects referred to English Dyslexia Centres tend to be those with the most severe problems. Normal provision has failed with them. Remedial help within class and as an additional support has also failed. In the English system the diagnosis of need for referral for specialist tuition thus comes late, often at the transfer age of 10/11 years when the pupil is about to leave primary and enter secondary school. The delay in diagnosis is due to the Statementing system needed to gain additional resources, the specialist tuition, and lack of

In the UK up to the age of 7 or 8 years additional support within school is given. If it has not worked then a formal diagnosis is sought and expertise from a specialist tutor is applied for.

 Diagnosis of dyslexia does not need to be delayed for several years until the child is a three time failure but can take place in the Reception class by the class teacher with a

 Many of the so-called 'remedial' programmes are not effective but the few that are effective need to be implemented as soon as possible to obtain the best results. The focus on reading throughout dyslexia research and teaching practice is possibly a

Dyslexia may not be 'cured' but can be overcome by the right sort of tuition in primary

Experimental research requires that the researcher comes to cases with a hypothesis about the condition that is then tested and accepted or rejected. The hypothesis is based upon detailed research of the relevant literature but this can mean that it is defined by that

 Dyslexia is not a disorder but caused by a deficit that results in an educational delay. If dyslexia is remediated there can be associated improved behavioural outcomes.

**2. What casework shows that experiments may not** 

been compared with similar numbers of control subjects.

agreed diagnostic indicators in the early years.

What this chapter will seek to show is that:

small amount of training.

mistake.

school.

**1. Introduction** 

**Remediation to Overcoming Dyslexia** 

dyslexia: Evidence from two case studies. *Reading and Writing: An interdisciplinary Journal,* Vol.16, pp. 541-572, ISSN 0922-4777.

