Resting-state EEG reveals global network deficiency in dyslexic children

NEUROPSYCHOLOGIA

卷:138

Article

Xue, Huidong^1,2,3  Wang, Zhiguo⁴  Tan, Yufei^5,6  Yang, Hang⁷  Fu, Wanlu^1,2,3  Xue, Licheng^1,2  Zhao, Jing^1,2 

[1] Hangzhou Normal Univ, Inst Psychol Sci, Hangzhou, Peoples R China

[2] Zhejiang Key Lab Res Assessment Cognit Impairment, Hangzhou, Peoples R China

[3] Hangzhou Normal Univ, Ctr Cognit & Brain Disorder, Hangzhou, Peoples R China

[4] SR Res Ltd, Ottawa, ON, Canada

[5] Univ Aix Marseille, Lab Psychol Cognit, Marseille, France

[6] CNRS, Paris, France

[7] Univ Groningen, Fac Sci & Engn, Bernoulli Inst Math Comp Sci & Artificial Intelli, Groningen, Netherlands

关键词: Developmental dyslexia;    Resting-state electroencephalography (EEG);    Functional network connectivity;    Graph theory;    Minimum spanning tree (MST);   

DOI  :  10.1016/j.neuropsychologia.2020.107343

来源: Elsevier

【 摘 要 】

Developmental dyslexia is known to involve dysfunctions in multiple brain regions; however, a clear understanding of the brain networks behind this disorder is still lacking. The present study examined the functional network connectivity in Chinese dyslexic children with resting-state electroencephalography (EEG) recordings. EEG data were recorded from 27 dyslexic children and 40 age-matched controls, and a minimum spanning tree (MST) analysis was performed to examine the network connectivity in the delta, theta, alpha, and beta frequency bands. The results show that, compared to age-matched controls, Chinese dyslexic children had global network deficiencies in the beta band, and the network topology was more path-like. Moderate correlations are observed between MST degree metric and rapid automatized naming and morphological awareness tests. These observations, together with the findings in alphabetic languages, show that brain network deficiency is a common neural underpinning of dyslexia across writing systems.

【 授权许可】

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