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Jia Wang, Xiaomin Wang, Xuelai Wang, Huiying Zhang, Yong Zhou, Lei Chen, Yutong Li, Lijie Wu (2020). Increased EEG coherence in long‐distance and short‐distance connectivity in children with autism spectrum disorders. Brain and Behavior, 10(10), e01796. Wiley.

Date de publication
19/08/2020
Identifiant
10.1002/brb3.1796
Auteurs
Jia Wang, Xiaomin Wang, Xuelai Wang, Huiying Zhang, Yong Zhou, Lei Chen, Yutong Li, Lijie Wu
Source
Brain and Behavior
Détails
10(10), e01796
Type de référence
article
Éditeur
Wiley
Source de métadonnées
crossref

Résumé

Abstract Introduction Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD. Methods Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long‐distance and short‐distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD. Results Compared with TD group, individuals with ASD showed increased coherence in short‐distance electrode pairs in the right temporal–parietal region (delta, alpha, beta bands), left temporal–parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central–parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long‐distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal–occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity. Discussion Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism.

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