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

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

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,

A "disconnection syndrome" in which functional connectivity of the relevant cortical networks in the left hemisphere is disrupted has been proposed as a potential basis for reading difficulties [82]. Diffusion Tensor Imaging (DTI), a technology similar to fMRI, allows probing the distance and direction of water molecule movement in the brain, producing form and orientation information about the underly-

Fractional anisotropy (FA) is a related technology that is used to index structural information regarding a brain area. It measures the anisotropy of the diffusion of water molecules [86] and is sensitive to axonal density, size, myelination, and the coherence of organization of fibers within a voxel, thus providing an index of the structural integrity of white matter. FA is measured from 0 (isotropic diffusion) to 1 (anisotropic diffusion) [83]. Beaulieu et al. propose that FA may be reduced in

that dyslexics may not use the network in the same way as controls [81].

ing white matter structures [83]. White matter exhibits anisotropic water movement, with water molecules showing various degrees of diffusion in each direction. In typical DTI studies, diffusion images from at least six directions are analyzed using an ellipsoid tensor model—a symmetrical 3 3 matrix. Parallel and perpendicular diffusivities are then calculated and used to estimate properties of underlying tissues [84]. DTI has demonstrated a correlation between the microstructural integrity of the left temporo-parietal white matter and reading ability in dyslexic and control adults [85]. It seems that this technology could be instrumental in measuring not only the degree of connectedness between crucial brain features, but also in determining the amount of pressure needed by these systems to change

9. Evidence from diffusion tensor imaging

functioning.

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letter patterns, and unique words.

Neurodevelopment and Neurodevelopmental Disorder

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 featuremyelination, 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 reading model.

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

where significant differences in FA existed between dyslexic and typical readers, and research that used VBA to locate cortical coordinates where FA significantly correlated with reading ability or performance on a reading-based task. Their results were extraordinary. The analysis of 47 foci from 5 experiments (99 subjects), where FA was significantly greater in typical compared to dyslexic readers, and the analysis of 17 foci from 2 experiments (52 subjects), where FA was significantly greater in dyslexic compared to typical readers, yielded no significant clusters when using FDR correction of 0.05. Further, the analysis of 42 foci from 9 experiments (500 subjects), where reading ability was significantly positively correlated with FA, and the analysis of 2 foci from 2 experiments (40 subjects), where reading ability was significantly negatively correlated with FA, also yielded no significant clusters when using FDR correction of 0.05. Studies of children and adults were analyzed separately. No significant clusters were produced when typical readers had significantly higher FA than dyslexic readers or when dyslexic readers had significantly greater FA than typical readers, regardless of age [90]. The fact that these results showed no systematic differences in fractional anisotropy between dyslexic and typical readers, or as a function of reading ability, after correcting for multiple comparisons, underscores the ambiguity inherent in brain research in spite of, or perhaps because of, cutting edge technologies. Hoppenbrouwers, Vandermosten, and Boets noted that despite appearing consistent, each one of the studies they included in their meta-analysis produced coordinates at different locations within the temporo-parietal region and corpus callosum [91]. In fact many studies have also reported differences and correlations in a range of other regions distributed widely throughout the cortex [59, 92]. Turkeltaub et al. pointed out that the software commonly used for these kinds of analysis, GingerALE 2.0.4, has since been updated too correct initial errors which made ALE analysis to lenient, therefore inadequately controlling for spurious findings [93].

consistent orthographies, has been found to play a role in reading accuracy in more regular orthographies as readers become more experienced, but this seems to rely on specific language features that promote decoding based on lexical aspects of known, related words. So in languages where these language-specific patterns are prevalent, most dyslexics achieve high levels of reading accuracy but remain deficit

Research into the visual processing of struggling readers has focused mainly on the functions of the occipito-temporal reading circuit. Dysfunction in a variety of visuo-attentional skills such as visual search, visual recognition, and visual information processing has been documented in several languages, with both transparent and opaque orthographies. Interesting work in languages that use diacritical vowel markings which are absent after instruction emphasizes the theory that when grapheme-phoneme processing skills are weak, students are unable to develop strong connections in the orthographic lexicon to support further autonomous word recognition. In this case, the results also highlight the importance of visual accuracy and memory for the missing vowel markings. Generally, however, functional imaging studies reveal reduced reading related activation in a left ventral occipitotemporal brain area, often associated as an interface between visual orthographic codes and phonology and meaning. There is some assurance of parity for even complex visual languages like Urdu that RAN continues to be a reliable predictor of reading accuracy. Regardless, the question of effective interventions remains

American researchers have addressed the problems inherent in dyslexia through new conceptualizations of fluency and definitions that acknowledge the crucial role played by the automatization of underlying subskills at the letter, letterpattern, and word levels. They challenged the validity of the commonly held discrepancy definition of dyslexia which mandates that a student with reading difficulties can be labeled "dyslexic" only if they have an average or higher IQ. Research showed that there were no reliable differences in the brain functioning of poor readers with high IQs and poor readers with low IQs. The effects of instructional intervention have also been explored in studies with American students. Most of this research focuses on explicit instruction in the alphabetic principle and phonological processing. These efforts generally resulted in increases in the activation of left posterior superior temporal gyrus (STG), although processing speed remained unaffected. However, a novel study using visual hemisphere-specific stimulation has shown some advancement in the speed of processing of dyslexic readers. Matching struggling readers to either a left or right hemisphere intervention program by specific oral reading behaviors appears to be helpful in applying an effective remediation program. The differences in the composition of the intervention programs (the left hemisphere lessons are all phonologically decodable words and the right hemisphere lessons are all phonologically decodable non-words) apparently interact with the weak brain processing systems efficiently. The forced pressure of faster and faster recall appears to strengthen the pathways resulting in automatized recall. Brain activations of subjects who achieved levels of automatic processing (recall within 100–250 ms) revealed expected changes: pre-intervention, there was a great deal of diffuse activation in the frontal areas and in the right hemisphere, and post-intervention activation was much more focused bilaterally around the STG and postcentral gyrus with very little activation in the VWFA. Further these documented processing changes were discovered to directly support increases in reading speed in those students reaching automatic levels of visual processing. So, visual hemisphere-specific stimulation has emerged as an intervention tool that influences access to the VWFA in American dyslexic

in reading speed.

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

largely unanswered.

readers.

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