EEG based functional brain networks analysis in dyslexic children during arithmetic task

An Overview on Electrophysiological and Neuroimaging Findings in Dyslexia

Objective: Dyslexia is a prevalent neurodevelopmental condition that is characterized by inaccurate and slow word recognition. This article reviews neural correlates of dyslexia from both electrophysiological and neuroimaging studies. Method : In this brief review, we provide electrophysiological and neuroimaging evidence from electroencephalogram (EEG) and magnetic resonance imaging (MRI) studies in dyslexia to understand functional and structural brain changes in this condition. Results: In both electrophysiological and neuroimaging studies, the most frequently reported functional impairments in dyslexia include aberrant activation of the left hemisphere occipito-temporal cortex (OTC), temporo-parietal cortex (TPC), inferior frontal gyrus (IFG), and cerebellar areas. EEG studies have mostly highlighted the important role of lower frequency bands in dyslexia, especially theta waves. Furthermore, neuroimaging studies have suggested that dyslexia is related to functional and structural impairments in the left hemisphere regions associated with reading and language, including reduced grey matter volume in the left TPC, decreased white matter connectivity between reading networks, and hypo-activation of the left OTC and TPC. In addition, neural evidence from pre-reading children and infants at risk for dyslexia show that there are abnormalities in the dyslexic brain before learning to read begins. Conclusion: Advances in comprehending the neural correlates of dyslexia could bring closer translation from basic to clinical neuroscience and effective rehabilitation for individuals who struggle to read. However, neuroscience still has great potential for clinical translation that requires further research.

Extraction of discriminative features from EEG signals of dyslexic children; before and after the treatment

Dyslexia is a neurological disorder manifested as difficulty reading and writing. It can occur despite adequate instruction, intelligence, and intact sensory abilities. Different electroencephalogram (EEG) patterns have been demonstrated between dyslexic and healthy subjects in previous studies. This study focuses on the difference between patients before and after treatment. The main goal is to identify the subset of features that adequately discriminate subjects before and after a specific treatment plan. The treatment consists of Transcranial Direct Current Stimulation (tDCS) and occupational therapy using the BrainWare SAFARI software. The EEG signals of sixteen dyslexic children were recorded during the eyes-closed resting state before and after treatment. The preprocessing step was followed by the extraction of a wide range of features to investigate the differences related to the treatment. An optimal subset of features extracted from recorded EEG signals was determined using Principal Component Analysis (PCA) in conjunction with the Sequential Floating Forward Selection (SFFS) algorithm. The results showed that treatment leads to significant changes in EEG features like spectral and phase-related EEG features, in various regions. It has been demonstrated that the extracted subset of discriminative features can be useful for classification applications in treatment assessment. The most discriminative subset of features could classify the data with an accuracy of 92% with SVM classifier. The above result confirms the efficacy of the treatment plans in improving dyslexic children's cognitive skills.