Resting-state EEG reveals global network deficiency in dyslexic children. (17th February 2020) - Xue, Huidong; Wang, Zhiguo; Tan, Yufei; Yang, Hang; Fu, Wanlu; Xue, Licheng; Zhao, Jing
Abstract: 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. Highlights: MST network analysis was performed on resting-state EEG data from dyslexic children. Dyslexic children show network deficiency in theta and beta bands. The network topology in dyslexic children is more path-like. MST degree moderately correlates with morphological awareness and rapid naming.