Influences of neural pathway integrity on children’s response to reading instruction

Abstract

As the education field moves toward using responsiveness to intervention to identify students with disabilities, an important question is the degree to which this classification can be connected to a student's neurobiological characteristics. A few functional neuroimaging studies have reported a relationship between activation and response to instruction; however, whether a similar correlation exists with white matter (WM) is not clear. To investigate this issue, we acquired high angular resolution diffusion images from a group of first grade children who differed in their levels of responsiveness to a year-long reading intervention. Using probabilistic tractography, we calculated the strength of WM connections among nine cortical regions of interest and correlated these estimates with participants’ scores on four standardized reading measures. We found eight significant correlations, four of which were connections between the insular cortex and angular gyrus. In each of the correlations, a relationship with children's response to intervention was evident.

Thalamo-Cortical Connectivity: What Can Diffusion Tractography Tell Us About Reading Difficulties in Children?

“…Given the lack of previous studies in dyslexia examining potential thalamic connectivity differences, our hypotheses were necessarily general; however, given the differences in functional activation in the thalamus between typically developing and dyslexic groups, we expected that we would find differences in thalamo-cortical connectivity between the TD and DYS groups. While specificity of these regions was difficult to pinpoint, in the one previous diffusion tractography-based connectivity study (Davis et al, 2010), we showed differences in thalamo-cortical connectivity between responders and nonresponders to reading intervention. Therefore, we expected thalamo-cortical differences between groups in the standard language-related regions near the perisylvian cortex, such as the occipito-temporal cortex (OTC) and the temporo-parietal cortex (TPC).…”

“…In addition to the voxel-based morphometry analyses that focus on the localized white matter microstructural properties, diffusion tractography was employed to map the white matter fiber pathways which are important for reading, including arcuate fasciculus, corpus callosum, inferior longitudinal fasciculus, and inferior frontal occipital fasciculus (Catani et al, 2005;Odegard et al, 2009;Rauschecker et al, 2009;Saygin et al, 2013;Yeatman et al, 2012) (for a review, see Vandermosten et al, 2012;Wandell, 2011). Brain connectivity between distant regions, such as thalamus, angular gyrus, superior temporal cortex, and insula, has been shown to be related to reading ability in children (Davis et al, 2010). These findings suggest that the characteristics of white matter pathways between distant cortical regions are potentially an important aspect of the neurobiology of dyslexia.…”

Atypical White Matter Connectivity in Dyslexic Readers of a Fairly Transparent Orthography

“…A recent study found increased connectivity between the thalamus and both the lateral prefrontal cortex and the sensorimotor cortex in English-speaking dyslexic children ( Fan et al, 2014 ). Furthermore, Fan et al (2014) observed a negative correlation between thalamo-cortical connectivity and a composite score of visual word identification and word attack measures, while another study found a negative correlation between thalamo-cortical connections and pseudoword reading ( Davis et al, 2010 ). Contrary to the increased anterior thalamo-cortical connectivity, more posterior thalamo-cortical connectivity, i.e., between LGN and V5/MT may be reduced in dyslexia ( Müller-Axt et al, 2017 ).…”

Learning to See Words

“…One application is to use neuroimaging measurements to predict the likelihood of success of specific interventions. For example, EEG potentials (Maurer et al 2009, Molfese 2000) and MR measures (Davis et al 2010; Hoeft et al 2007, 2011) have been used to predict reading outcomes. Such measures can be used to select the best intervention for an individual (Gabrieli 2009).…”