Abstract
Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60–89 months old) and for 25 typically developing (TD) control children (10 girls, 60–91 months old) in a resting state while gazing at a fixation cross. After signal sources were localized onto the Desikan–Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. Children with ASD were found to have significantly lower small-worldness in the beta band (p = 0.007) than TD children had. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores (p = 0.047). Significant relations were also inferred for the Social Awareness (p = 0.008) and Social Cognition (p = 0.015) sub-scales. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD.
Highlights
Daiki Soma 1, Tetsu Hirosawa 1,2*, Chiaki Hasegawa 2, Kyung-min An 2, Masafumi Kameya 1, Shoryoku Hino 3, Yuko Yoshimura 2,4, Sou Nobukawa 5, Sumie Iwasaki 2, Sanae Tanaka 2, Ken Yaoi 2, Masuhiko Sano 1, Yuka Shiota 2, Nobushige Naito 1 and Mitsuru Kikuchi 1,2
Within the framework of those limitations, a consensus seems to hold that brain networks of adults with autism spectrum disorder (ASD) constructed based on resting-state MEG/EEG derived functional connectivity show lower CC and higher Characteristic path length (cPL) than those of healthy controls
If a significant group effect was found in any graph metric, we investigated the relation between autism symptom severity and the graph metric
Summary
Of the entire brain network as single numerical values. It is noteworthy that graph metrics differ from traditional measures of connectivity (e.g., means of connectivity) in two meaningful ways. They reported higher CC and lower cPL in the theta band for adolescents (12–15 years old) with ASD compared to healthy controls It remains unclear whether the properties of resting state MEG/EEG-derived functional brain networks are different in adolescents with ASD from those in adults or children with ASD, in that lower CC and lower SW in childhood ASD reported by Han et al might arise as an effect of medication. Within the framework of those limitations, a consensus seems to hold that brain networks of adults with ASD constructed based on resting-state MEG/EEG derived functional connectivity show lower CC and higher cPL than those of healthy controls. They recruited young adults with and without ASD and investigated the functional networks generated from restingstate MEG recordings Based on their findings, they reported significantly lower CC and higher cPL (in the broadband signal) in the ASD group than in healthy controls. All the reports described above indicate lower CC in ASD patients than in healthy control
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