Neuroanatomy of dyslexia: An allometric approach.

Despite evidence for a difference in total brain volume between dyslexic and good readers, no previous neuroimaging study examined differences in allometric scaling (i.e. differences in the relationship between regional and total brain volumes) between dyslexic and good readers. The present study aims to fill this gap by testing differences in allometric scaling and regional brain volume differences in dyslexic and good readers. Object-based morphometry analysis was used to determine grey and white matter volumes of the four lobes, the cerebellum and limbic structures in 130 dyslexic and 106 good readers aged 8-14 years. Data were collected across three countries (France, Poland and Germany). Three methodological approaches were used as follows: principal component analysis (PCA), linear regression and multiple-group confirmatory factor analysis (MGCFA). Difference in total brain volume between good and dyslexic readers was Cohen's d = 0.39. We found no difference in allometric scaling, nor in regional brain volume between dyslexic and good readers. Results of our three methodological approaches (PCA, linear regression and MGCFA) were consistent. This study provides evidence for total brain volume differences between dyslexic and control children, but no evidence for differences in the volumes of the four lobes, the cerebellum or limbic structures, once allometry is taken into account. It also finds no evidence for a difference in allometric relationships between the groups. We highlight the methodological interest of the MGCFA approach to investigate such research issues.

Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in isolation, disregarding potential interactions between regions and measures. Here, for the first time a multivariate classification approach was used to investigate grey matter disruptions in children with dyslexia in a large (N = 236) multisite sample. A variety of cortical morphological features, including volumetric (volume, thickness and area) and geometric (folding index and mean curvature) measures were taken into account and generalizability of classification was assessed with both 10-fold and leave-one-out cross validation (LOOCV) techniques. Classification into control vs. dyslexic subjects achieved above chance accuracy (AUC = 0.66 and ACC = 0.65 in the case of 10-fold CV, and AUC = 0.65 and ACC = 0.64 using LOOCV) after principled feature selection. Features that discriminated between dyslexic and control children were exclusively situated in the left hemisphere including superior and middle temporal gyri, subparietal sulcus and prefrontal areas. They were related to geometric properties of the cortex, with generally higher mean curvature and a greater folding index characterizing the dyslexic group. Our results support the hypothesis that an atypical curvature pattern with extra folds in left hemispheric perisylvian regions characterizes dyslexia. Hum Brain Mapp 38:900-908, 2017. © 2016 Wiley Periodicals, Inc.

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

The neural basis of specific reading disability (SRD) remains only partly understood. A dozen studies have used voxel-based morphometry (VBM) to investigate gray matter volume (GMV) differences between SRD and control children, however, recent meta-analyses suggest that few regions are consistent across studies. We used data collected across three countries (France, Poland, and Germany) with the aim of both increasing sample size (236 SRD and controls) to obtain a clearer picture of group differences, and of further assessing the consistency of the findings across languages. VBM analysis reveals a significant group difference in a single cluster in the left thalamus. Furthermore, we observe correlations between reading accuracy and GMV in the left supramarginal gyrus and in the left cerebellum, in controls only. Most strikingly, we fail to replicate all the group differences in GMV reported in previous studies, despite the superior statistical power. The main limitation of this study is the heterogeneity of the sample drawn from different countries (i.e., speaking languages with varying orthographic transparencies) and selected based on different assessment batteries. Nevertheless, analyses within each country support the conclusions of the cross-linguistic analysis. Explanations for the discrepancy between the present and previous studies may include: (1) the limited suitability of VBM to reveal the subtle brain disruptions underlying SRD; (2) insufficient correction for multiple statistical tests and flexibility in data analysis, and (3) publication bias in favor of positive results. Thus the study echoes widespread concerns about the risk of false-positive results inherent to small-scale VBM studies.

Shared vs. specific brain activation changes in dyslexia after training of phonology, attention, or reading.

Whereas the neurobiological basis of developmental dyslexia has received substantial attention, only little is known about the processes in the brain during remediation. This holds in particular in light of recent findings on cognitive subtypes of dyslexia which suggest interactions between individual profiles, training methods, and also the task in the scanner. Therefore, we trained three groups of German dyslexic primary school children in the domains of phonology, attention, or visual word recognition. We compared neurofunctional changes after 4 weeks of training in these groups to those in untrained normal readers in a reading task and in a task of visual attention. The overall reading improvement in the dyslexic children was comparable over groups. It was accompanied by substantial increase of the activation level in the visual word form area (VWFA) during a reading task inside the scanner. Moreover, there were activation increases that were unique for each training group in the reading task. In contrast, when children performed the visual attention task, shared training effects were found in the left inferior frontal sulcus and gyrus, which varied in amplitude between the groups. Overall, the data reveal that different remediation programmes matched to individual profiles of dyslexia may improve reading ability and commonly affect the VWFA in dyslexia as a shared part of otherwise distinct networks.

Devil in the details? Developmental dyslexia and visual long-term memory for details.

Cognitive theories on causes of developmental dyslexia can be divided into language-specific and general accounts. While the former assume that words are special in that associated processing problems are rooted in language-related cognition (e.g., phonology) deficits, the latter propose that dyslexia is rather rooted in a general impairment of cognitive (e.g., visual and/or auditory) processing streams. In the present study, we examined to what extent dyslexia (typically characterized by poor orthographic representations) may be associated with a general deficit in visual long-term memory (LTM) for details. We compared object- and detail-related visual LTM performance (and phonological skills) between dyslexic primary school children and IQ-, age-, and gender-matched controls. The results revealed that while the overall amount of LTM errors was comparable between groups, dyslexic children exhibited a greater portion of detail-related errors. The results suggest that not only phonological, but also general visual resolution deficits in LTM may play an important role in developmental dyslexia.

Distinct neural signatures of cognitive subtypes of dyslexia: effects of lexicality during phonological processing.

The present study investigates the neurobiological basis of two subtypes of dyslexia with either a double deficit (concerning phonological awareness and rapid naming) or a single rapid naming deficit. We compared such groups of German dyslexic primary school children to each other and with good reading children in a phoneme deletion task performed during fMRI scanning. Children heard German words or pseudowords and repeated the remainder of the stimulus while deleting the initial phoneme (e.g. tear - _ear). In four conditions, the input stimulus (word or pseudoword) could either become another word or pseudoword as output. The word-word condition stuck out against all other conditions involving pseudowords: Dyslexics with a double deficit showed a strong response in left areas 44 and 45 in Boca's region, whereas dyslexics with rapid naming difficulties revealed a contralateral effect in right areas 44 and 45. These findings, which were obtained without presenting written or pictorial stimuli, reveal that a double deficit in dyslexia is not the sum of single deficits, but rather involves the interaction of lexical and phonological processing, making strong demands on the left inferior frontal cortex. In general, the results stress the importance of considering subtypes of dyslexia differentially in order to obtain better insights in the neurocognitive mechanisms of impaired and successful reading.

Identifying brain systems for gaze orienting during reading: fMRI investigation of the Landolt paradigm.

The Landolt reading paradigm was created in order to dissociate effects of eye movements and attention from lexical, syntactic, and sub-lexical processing. While previous eye-tracking and behavioral findings support the usefulness of the paradigm, it remains to be shown that the paradigm actually relies on the brain networks for occulomotor control and attention, but not on systems for lexical/syntactic/orthographic processing. Here, 20 healthy volunteers underwent fMRI scanning while reading sentences (with syntax) or unconnected lists of written stimuli (no syntax) consisting of words (with semantics) or pseudowords (no semantics). In an additional "Landolt reading" condition, all letters were replaced by closed circles, which should be scanned for targets (Landolt's rings) in a reading-like fashion from left to right. A conjunction analysis of all five conditions revealed the visual scanning network which involved bilateral visual cortex, premotor cortex, and superior parietal cortex, but which did not include regions for semantics, syntax, or orthography. Contrasting the Landolt reading condition with all other regions revealed additional involvement of the right superior parietal cortex (areas 7A/7P/7PC) and postcentral gyrus (area 2) involved in deliberate gaze shifting. These neuroimaging findings demonstrate for the first time that the linguistic and orthographic brain network can be dissociated from a pure gaze-orienting network with the Landolt paradigm. Consequently, the Landolt paradigm may provide novel insights into the contributions of linguistic and non-linguistic factors on reading failure e.g., in developmental dyslexia.

Distinct neural signatures of cognitive subtypes of dyslexia with and without phonological deficits.

Developmental dyslexia can be distinguished as different cognitive subtypes with and without phonological deficits. However, despite some general agreement on the neurobiological basis of dyslexia, the neurofunctional mechanisms underlying these cognitive subtypes remain to be identified. The present BOLD fMRI study thus aimed at investigating by which distinct and/or shared neural activation patterns dyslexia subtypes are characterized. German dyslexic fourth graders with and without deficits in phonological awareness and age-matched normal readers performed a phonological decision task: does the auditory word contain the phoneme/a/? Both dyslexic subtypes showed increased activation in the right cerebellum (Lobule IV) compared to controls. Subtype-specific increased activation was systematically found for the phonological dyslexics as compared to those without this deficit and controls in the left inferior frontal gyrus (area 44: phonological segmentation), the left SMA (area 6), the left precentral gyrus (area 6) and the right insula. Non-phonological dyslexics revealed subtype-specific increased activation in the left supramarginal gyrus (area PFcm; phonological storage) and angular gyrus (area PGp). The study thus provides the first direct evidence for the neurobiological grounding of dyslexia subtypes. Moreover, the data contribute to a better understanding of the frequently encountered heterogeneous neuroimaging results in the field of dyslexia.