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Updated: Sep 13, 2025
EEG Mu Rhythm in Typical and Atypical Development
Published on: April 9, 2014
Baseline-dependent network reactivity to visual input in children with autism spectrum disorder: a
Tetsu Hirosawa1,2, Daiki Soma1, Masuhiko Sano1
1Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.
Background/Aims:
Neuroimaging studies suggest altered functional brain organization in children with autism spectrum disorder (ASD), particularly in response to visual stimulation. However, how transitions between different visual states modulate brain network in ASD remains unclear. This study aimed to investigate how transitioning from minimal visual input (fixation in a dark room, DR) to a silent video (eyes open, EO) alters functional brain networks in children with ASD compared with their typically developing (TD) peers.
Methods:
We analyzed magnetoencephalography (MEG) data from children with ASD (n=23) and TD children (n=31), aged 3-10 years. MEG signals were mapped to 68 cortical regions using the Desikan-Killiany atlas, and functional connectivity was assessed using the phase lag index across five frequency bands (delta, theta, alpha, beta, and gamma). Graph theoretical analyses quantified the clustering coefficient (C), characteristic path length (L), and small-worldness (SW) to evaluate network organization.
Results:
Both groups exhibited increased alpha-band clustering coefficients under EO. Notably, baseline (DR) graph metrics predicted EO-induced changes, with higher initial values associated with smaller subsequent increases. Diagnosis-by-condition interactions emerged in the delta and beta bands: children with ASD exhibited more pronounced increases in SW from DR to EO, whereas TD peers showed more modest or opposite shifts. Within the ASD group, larger beta-band SW increases correlated with greater autistic trait severity (Social Responsiveness Scale), whereas in TD children, delta-band increases associated with milder autistic-like traits.
Conclusion:
These findings reveal age- and diagnosis-specific differences in how visual stimulation reshapes functional brain network organization. They also highlight the potential of network metrics as biomarkers for ASD, though validation in larger, more diverse cohorts is needed to establish clinical relevance.
