8. Case studies OF VHSS intervention

Subject 1, coded MC, was one of the students who reached very fast processing speeds during the intervention using the left hemisphere program. The

The Neurobiological Development of Reading Fluency DOI: http://dx.doi.org/10.5772/intechopen.82806

pre-intervention scan showed mostly diffuse activation in the right hemisphere occipital-parietal areas. Based on all phonetic reading errors in the pre-intervention fluency measure, this student was labeled a "P-type" and assigned the LH intervention program. MC was a very willing subject and engaged with the program easily. After progressing through the LH program (34 lessons) nearly six times during the 1440 minutes of training, the fastest processing was 80 ms with 100% accuracy. This student also achieved fluent processing rather quickly on the thirteenth day of treatment. MC gained 26 wpm on the final fluency measure. Analyzing this subject's scanner data, there was an almost perfect performance when processing the letter matches: 98% accuracy during Scan 1 and 89% accuracy during Scan 2. MC's analysis of phonemic elements improved from Scan 1–2. During Scan 1, 54% of the word pairs were correctly identified and 70% were right in Scan 2. Overall this subject demonstrated a 5% improvement in fast decoding skills. The post-intervention scan shows much more focused activation bilaterally in the temporal regions around the superior temporal gyrus and postcentral gyrus, and there is very little activation in the VWFA in the LH occipital lobe [78].

Subject 2, coded PE, was one of the students who achieved processing speeds that approached fluency using the left hemisphere program. The pre-intervention scan showed a lot of bilateral frontal activation and more RH activation than LH activation in the occipital areas. Five out of six reading errors were phonics-based, so this student was labeled "P-type" and assigned the LH program. PE completed the LH program six times during 1440 minutes of treatment, but there were only 24 lessons included because some of the orthographic patterns were not taught at this reading level. This student was one of the younger participants in the study and only reached levels of fluent processing for words, not for phrases. PE's fastest processing score was 125 ms with 83% accuracy and during post-intervention fluency measures, reading speed was increased by 11 wpm. Analyzing the scanner data, there is evidence of significant learning, perhaps due to the young age and the nature of reading instruction in the lower grades. PE showed a lot of confusion when analyzing the letter strings: only 49% were judged correctly in Scan 1 and 57% in Scan 2. Growth in decoding skills is evident in the correct identification of the word pairs: 45% during Scan 1 and 62% during Scan 2. Overall, this subject demonstrated a 13% improvement in fast visual processing. The post-intervention scan indicates an increase in left hemisphere activation around the inferior frontal gyrus and VWFA [78].

So if the focus is on automatic word retrieval, the Visual Word Form Area, has to be a region of exceptional interest. There remains much to understand regarding the activation of the Visual Word Form Area in the left fusiform gyrus and its relationship to the development of fluent reading. According to Cohen et al., a standard model of word reading proposes that visual information is initially processed by occipito-temporal areas contra-lateral to the stimulated hemi-field. Then it is transferred to the visual word form system (VWFA), a left temporal region devoted to the processing of letter strings. Using fMRI, they identified a highly significant activation in the left fusiform gyrus (Talairach coordinates: x = 42, y = 57, z = 6) that was strictly unilateral and remarkably stable across subjects [80]. Since their research also included comparisons of activation from the right and left visual hemi-fields, they concluded that the VWFA lies at the convergence of retinotopically organized visual pathways and contain visual neurons with receptive fields in both hemi-fields. They hypothesize that the VWFA may be homologous to inferotemporal areas in the monkey where cells with wide receptive fields, selectivity to high-level visual features, and size and position invariance have been found. If this is the case, it is possible that the human VWFA holds a distributed

processing (<100 ms) in either the left- or right visual hemi-field, also increased

There is considerable evidence that different students responded to the intervention differently. Those students who only displayed phonics-based errors in reading connected text and worked for the entire intervention time in the LH Program seemed to make the most substantial increases in both processing and reading speed. Only one student who demonstrated meaning-based errors and used the RH Program exclusively showed faster processing during intervention. The students who displayed both types of errors and split their time between programs made the least amount of progress; two reached fluency in the LH Program, but not in the RH Program. It is suggested that continued work with the intervention program could achieve the desired level of automaticity and that strengthening processing in the right hemisphere is inherently more difficult than strengthening

Intervention Group (N = 9) Delayed Intervention Group (N = 6)

Net gain Pre-intervention

11.9 wpm 24–128 wpm

reading fluency range (average)

(77 wpm)

Post-intervention reading fluency range (average)

> 50–120 wpm (85 wpm)

Net gain

7.3

Wolf cautions that another source of reading disability could be an impediment in the circuit connections among the brain structures, stressing the importance of understanding the connectivity among the various regions instrumental to reading performance. She proposed at least three forms of disconnections which are consistently studied: between the frontal and posterior language regions based on underactivity in the connecting insula; and between the occipital-temporal region or the left angular gyrus region; and frontal areas in the left hemisphere. She suggests that children with dyslexia use an altogether different reading circuitry. Instead of a progressive disentanglement of the right hemisphere's larger visual recognition system in reading words and an increasing engagement of left hemisphere's frontal, temporal, and occipital-temporal regions, they used more frontal regions, showed less activity in the left-hemisphere angular gyrus, and created potentially compensatory "auxillary" right-hemisphere regions which performed functions usually handled by more efficient left-hemisphere areas [14]. The fMRI results from this study underscore Wolf's proposal. It may be that much of the diffuse frontal acti-

vation that was observed in many pre-intervention scans and some postintervention scans of nonfluent subjects is evidence of these compensatory "auxillary" strategies. It may be that in older readers who have over time consolidated less efficient pathways for reading, more exposure is required for specific hemispheric stimulation (intervention) to supplant frontal and right hemisphere

speeds during the intervention using the left hemisphere program. The

Subject 1, coded MC, was one of the students who reached very fast processing

functions with effective left hemisphere processing.

8. Case studies OF VHSS intervention

104

their reading rate by an average of 20 wpm [78]. See Table 4.

Post-intervention reading fluency range (average)

Neurodevelopment and Neurodevelopmental Disorder

51–131 wpm (90 wpm)

the left hemisphere [78].

Pre-intervention reading fluency range (average)

Summary of behavioral results.

40–115 wpm (78 wpm)

Table 4.

representation of the visual shapes of letters such that specific alphabetic strings are distinguished and is thought to supply instantaneous recognition of learned letters, letter patterns, and unique words.

poor readers due to a number of possible differences in the microstructural properties of white matter. These possible differences include reduced myelination, reduced axonal packing density, decreased axonal diameter, or reduced coherence of the orientation of axons within the region, all of which might impact the efficiency of communication (bandwidth) among cortical areas [87]. Further, their findings suggest that there are regional brain structural correlations over a wide range of reading ability even within a so-called normal population. Keller and Just examined the diffusivity in directions that are perpendicular to the principal axis of diffusion in anisotropic regions of white matter (radial diffusivity) or parallel to it (axial diffusivity). They suggest that the pattern of diffusivity effects signifies that the difference in FA between poor and good readers before remediation is due to initially higher radial diffusivity in the poor readers. Further indicating that the change in FA results from an alteration in some microstructural feature-

The Neurobiological Development of Reading Fluency DOI: http://dx.doi.org/10.5772/intechopen.82806

myelination, packing density, or axon diameter- that affects radial diffusivity. By default, myelination is deemed the plausible mechanism of the microstructural change [88]. It is possible that extended, pressured practice affects the myelinated cortical thickness in key regions of the neuroanatomical correlates of the dual route

In a meta-analysis focusing on the foci of brain activity in a set of studies, Richlan, Kronbichler, and Wimmer used Activation Likelihood Estimation (ALE) to analyze for agreement by modeling each reported focus as the center of a Gaussian probability distribution. These distributions are then joined to create a whole-brain statistical map that estimates the likelihood of activation for each voxel. The data from 17 studies (12 fMRI and 5 PET) with a total number of 595 participants (294 dyslexics and 301 controls) were included. This approach resulted in three ALE maps: one, presenting brain regions with under-activation in dyslexic readers, another, presenting regions with over-activation and, finally, a subtraction map which allows a formal assessment of differences between the two maps. The results extracted 128 foci of reliable group differences (69 for dyslexic under-activation and 59 for dyslexic over-activation), and localized 80 input foci in the left hemisphere and only 48 in the right hemisphere. They found that 58% of the left and 48% of the right hemisphere foci were under-activation foci. The majority of activation abnormalities identified by separate maps were still present in the conservative thresholded difference map: under-activation in a large cluster in the left hemisphere reaching from dorsal inferior parietal to ventral occipito-temporal regions and to the middle temporal and the inferior frontal under-activation, with over-activation in left hemisphere anterior insula, primary motor cortex, lingual gyrus, caudate nuclei, thalamus and right hemisphere medial frontal cortex. These

results provide support for a dysfunction of the VWFA engaged in visualorthographic word recognition and a dysfunction of the left fusiform region affecting the build-up or the use of an orthographic word lexicon in recognition. Further, over-activation of the left lingual gyrus may reflect prolonged visual processing when dyslexic readers are confronted with a reading task [89].

Voxel Based Analysis (VBA) uses brain images normalized to a standard brain atlas and smoothed, before computing and comparing DTI properties for each individual voxel. This approach greatly reduces the typical biases of ROI analyses, though since it is typically less theoretically driven more drastic corrections for multiple comparisons are often required [90]. Moreau, Stonyer, McKay, and Waldie observed that many DTI studies have investigated significant differences in FA between dyslexic and typical readers, as well as identifying regions where FA values significantly correlate with performance on reading tasks, with problems in replication and little convergence of data. Using a very stringent process of examination, they identified research that used VBA to identify cortical coordinates

reading model.

107

Van der Mark et al. researched areas of the fusiform gyrus for activations related to visual processing. Initially, they found a posterior–anterior measure of change to print specificity with higher anterior response to letter strings but higher posterior response to false-fonts. Additionally, there was a constant sensitivity to orthographic familiarity demonstrated by higher response for unfamiliar than familiar word-forms. These variations along the VWF-System could only be detected in controls. They used functional connectivity MRI (fcMRI) to correlate signal changes in a seed region with signal changes in other parts of the brain and reveal functional interactions between brain areas. Five non-overlapping seed regions of interest (ROIs; spheres with a 6 mm radius) centered on the VWFA of the fusiform gyrus and covering neighboring areas along a posterior–anterior axis in the left hemisphere were defined, with ROI3 being the VWFA itself. Results showed that functional connectivity in children with dyslexia was significantly reduced only between the VWFA proper (ROI3) and classical left hemispheric language related regions, including the inferior parietal lobule and the inferior frontal gyrus. Significantly greater connectivity for the dyslexia than the control group was observed between ROI3 and the left middle temporal and middle occipital gyrus, and between ROI4 and the left superior temporal gyrus and the left insula. The strength of the functional connections between VWFA (ROI3) and the left middle temporal gyrus and between ROI4 and the left superior temporal gyrus did not correlate significantly with the behavioral measures in either the control group or the children with dyslexia. Correlating these increases in connectivity does not reflect better performance, but instead compensation efforts. They conclude, as did Wolf, that dyslexics may not use the network in the same way as controls [81].
