Cognitive subtypes of dyslexia are characterized by distinct patterns of grey matter volume

Abstract

The variety of different causal theories together with inconsistencies about the anatomical brain markers emphasize the heterogeneity of developmental dyslexia. Attempts were made to test on a behavioral level the existence of subtypes of dyslexia showing distinguishable cognitive deficits. Importantly, no research was directly devoted to the investigation of structural brain correlates of these subtypes. Here, for the first time, we applied voxel-based morphometry (VBM) to study grey matter volume (GMV) differences in a relatively large sample (n = 46) of dyslexic children split into three subtypes based on the cognitive deficits: phonological, rapid naming, magnocellular/dorsal, and auditory attention shifting. VBM revealed GMV clusters specific for each studied group including areas of left inferior frontal gyrus, cerebellum, right putamen, and bilateral parietal cortex. In addition, using discriminant analysis on these clusters 79 % of cross-validated cases were correctly re-classified into four groups (controls vs. three subtypes). Current results indicate that dyslexia may result from distinct cognitive impairments characterized by distinguishable anatomical markers.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-013-0595-6) contains supplementary material, which is available to authorized users.

Lessons to be learned: how a comprehensive neurobiological framework of atypical reading development can inform educational practice

“…Neuroimaging studies are beginning to inform several of the most contentious questions historically faced by the field: for instance, the field has debated whether a multi-deficit view of dyslexia should be accepted. Several studies so far have demonstrated that literacy skills such as PA and RAN are associated with distinct neuroanatomical regions [177–179] and that children with different profiles of deficit on these skills have unique patterns of activation during a reading-related task [180]. This supports the multi-deficit approach to dyslexia by suggesting that distinct brain mechanisms are associated with the various dyslexia profiles.…”

Impairments of multisensory integration and cross-sensory learning as pathways to dyslexia

“…More specifically, we find that children with pure dyslexia are severely impaired in their ability to benefit from multisensory cues on a multisensory speech-in-noise word identification task (see Foxe et al, 2013 for a full description of the paradigm), whereas children with co-morbid ADHD are not. What is more, studies using functional and anatomical MRI suggest that the affected neural regions differ between individuals with dyslexia subgrouped as a function of their profile of cognitive deficits (Jednorog, Gawron, Marchewka, Heim, & Grabowska, 2013; van Ermingen-Marbach, Grande, Pape-Neumann, Sass, & Heim, 2013). Thus it is clear that is necessary to thoroughly characterize dyslexia participants and consider the relationship between specific co-morbidities/cognitive deficits (e.g., poor working memory) and the underlying neurobiological pathway.…”

How reliable are gray matter disruptions in specific reading disability across multiple countries and languages? insights from a large‐scale voxel‐based morphometry study

“…Subsequently, Ashburner and Friston [] introduced voxel‐based morphometry (VBM) allowing the objective automatic analysis of structural T1‐weighted (T1w) MR scans. So far a number of VBM studies of gray matter volume (GMV) in SRD were published [Black et al, ; Brambati et al, ; Brown et al, ; Eckert et al, ; Evans et al, ; Hoeft et al, ; Jednoróg et al, ; Krafnick et al ; Kronbichler et al, ; Liu et al, 2013 ; Menghini et al, ; Pernet et al, , b; Raschle et al, ; Silani et al, ; Siok et al, ; Steinbrink et al, ; Vinckenbosch et al, ]. One review of the group differences (increased and decreased GMV) observed across some of these studies, gives an impression of a widely distributed set of bilateral regions differing between individuals with SRD and controls [Richardson and Price ].…”