Dataset Information

Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

ABSTRACT: Developmental dyslexia has been hypothesized to result from multiple causes and exhibit multiple manifestations, implying a distributed multidimensional effect on human brain. The disruption of specific white-matter (WM) tracts/regions has been observed in dyslexic children. However, it remains unknown if developmental dyslexia affects the human brain WM in a multidimensional manner. Being a natural tool for evaluating this hypothesis, the multivariate machine learning approach was applied in this study to compare 28 school-aged dyslexic children with 33 age-matched controls. Structural magnetic resonance imaging (MRI) and diffusion tensor imaging were acquired to extract five multitype WM features at a regional level: white matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) classifier achieved an accuracy of 83.61% using these MRI features to distinguish dyslexic children from controls. Notably, the most discriminative features that contributed to the classification were primarily associated with WM regions within the putative reading network/system (e.g., the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, thalamocortical projections, and corpus callosum), the limbic system (e.g., the cingulum and fornix), and the motor system (e.g., the cerebellar peduncle, corona radiata, and corticospinal tract). These results were well replicated using a logistic regression classifier. These findings provided direct evidence supporting a multidimensional effect of developmental dyslexia on WM connectivity of human brain, and highlighted the involvement of WM tracts/regions beyond the well-recognized reading system in dyslexia. Finally, the discriminating results demonstrated a potential of WM neuroimaging features as imaging markers for identifying dyslexic individuals.

SUBMITTER: Cui Z

PROVIDER: S-EPMC6867308 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

Cui Zaixu Z Xia Zhichao Z Su Mengmeng M Shu Hua H Gong Gaolang G

Human brain mapping 20160120 4

Developmental dyslexia has been hypothesized to result from multiple causes and exhibit multiple manifestations, implying a distributed multidimensional effect on human brain. The disruption of specific white-matter (WM) tracts/regions has been observed in dyslexic children. However, it remains unknown if developmental dyslexia affects the human brain WM in a multidimensional manner. Being a natural tool for evaluating this hypothesis, the multivariate machine learning approach was applied in th ...[more]

PMID: 26787263

Similar Datasets

Project description:The DCDC2 gene is involved in neuronal migration. Heterotopias have been found within the white matter of DCDC2-knockdown rats. A deletion in DCDC2/intron 2 (DCDC2d), which encompasses a regulatory region named 'regulatory element associated with dyslexia 1' (READ1), increases the risk for dyslexia. We hypothesized that DCDC2d can be associated to alterations of the white matter structure in general and in dyslexic brains.Based on a full-factorial analysis of covariance (ANCOVA) model, we investigated voxel-based diffusion tensor imaging (VB-DTI) data of four groups of subjects: dyslexia with/without DCDC2d, and normal readers with/without DCDC2d. We also tested DCDC2d effects upon correlation patterns between fractional anisotropy (FA) and reading scores.We found that FA was reduced in the left arcuate fasciculus and splenium of the corpus callosum in subjects with versus without DCDC2d, irrespective of dyslexia. Subjects with dyslexia and DCDC2d showed reduced FA, mainly in the left hemisphere and in the corpus callosum; their counterpart without DCDC2d showed similar FA alterations. Noteworthy, a conjunction analysis in impaired readers revealed common regions with lower FA mainly in the left hemisphere. When we compared subjects with dyslexia with versus without DCDC2d, we found lower FA in the inferior longitudinal fasciculus and genu of the corpus callosum, bilaterally. Normal readers with versus without DCDC2d had FA increases and decreases in both the right and left hemisphere.The major contribution of our study was to provide evidence relating genes, brain and behaviour. Overall, our findings support the hypothesis that DCDC2d is associated with altered FA. In normal readers, DCDC2-related anatomical patterns may mark some developmental cognitive vulnerability to learning disabilities. In subjects with dyslexia, DCDC2d accounted for both common - mainly located in the left hemisphere - and unique - a more severe and extended pattern - alterations of white matter fibre tracts.

Project description:Background: In attempts to understand the migraine patients' overall brain functional architecture, blood oxygenation level-dependent (BOLD) signals in the white matter (WM) and gray matter (GM) were considered in the current study. Migraine, a severe and multiphasic brain condition, is characterized by recurrent attacks of headaches. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both WM and GM. It is feasible to explore the functional interactions between WM tracts and GM regions in migraine. Methods: Forty-eight migraineurs without aura (MWoA) and 48 healthy controls underwent resting-state functional magnetic resonance imaging. Pearson's correlations between the mean time courses of 48 white matter (WM) bundles and 82 gray matter (GM) regions were computed for each subject. Two-sample t-tests were performed on the Pearson's correlation coefficients (CC) to compare the differences between the MWoA and healthy controls in the GM-averaged CC of each bundle and the WM-averaged CC of each GM region. Results: The MWoAs exhibited an overall decreased average temporal CC between BOLD signals in 82 GM regions and 48 WM bundles compared with healthy controls, while little was increased. In particular, WM bundles such as left anterior corona radiata, left external capsule and bilateral superior longitudinal fasciculus had significantly decreased mean CCs with GM in MWoA. On the other hand, 16 GM regions had significantly decreased mean CCs with WM in MWoA, including some areas that are parts of the somatosensory regions, auditory cortex, temporal areas, frontal areas, cingulate cortex, and parietal cortex. Conclusion: Decreased functional connections between WM bundles and GM regions might contribute to disrupted functional connectivity between the parts of the pain processing pathway in MWoAs, which indicated that functional and connectivity abnormalities in cortical regions may not be limited to GM regions but are instead associated with functional abnormalities in WM tracts.

Dataset Information

Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

Publications

Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets