Frontiers in neuroscience · 2026
Atypical development of white matter structural networks in children and adolescents with autism spectrum disorder: a graph theory study.
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Li Min, Kurita Kohei, Yamada Takashi, Wang Yide, Izumoto Maya, Iwatani Yoshiko, Mohri Ikuko, Shou Qiulu, Yamashita Masatoshi, Hamatani Sayo, Matsuzaki Hideo, Okazawa Hidehiko, Yoshida Tokiko, Kitagawa Hitomi, Sasaki Tsuyoshi, Matsumoto Koji, Nagano Tomomi, Isobe Yuko, Kamashita Rio, Sudo Yusuke, Shimizu Eiji, Kawasaki Ryo, Hirano Yoshiyuki, Mizuno Yoshifumi, Kagitani-Shimono Kuriko
Аннотация
BACKGROUND: Atypical brain connectivity is considered a key neurobiological feature underlying the heterogeneous clinical manifestations of autism spectrum disorder (ASD). However, findings on brain networks in ASD are inconsistent, likely owing to the effects of developmental factors. In addition, how large-scale brain networks in ASD differ across developmental stages remains unclear. We aimed to elucidate the atypical developmental patterns of white matter (WM) structural networks in children and adolescents with ASD using a graph-theoretical approach.
METHODS: Diffusion/T1-weighted brain imaging data were acquired from 69 individuals with ASD (age: 6-17 years) and 71 age- and sex-matched typically developing controls. Global and nodal topological properties of WM structural networks were computed, and 28 social-related regions were examined through subnetwork and nodal analyses. Case-control comparisons of global and nodal graph metrics were conducted separately for children and adolescents.
RESULTS: The children with ASD exhibited reduced integration of the whole-brain network, reflected by increased characteristic path length and decreased global efficiency. In contrast, the adolescents with ASD showed enhanced segregation within the social-brain subnetwork, indicated by increased clustering coefficient and local efficiency. Nodal analyses revealed reduced nodal efficiency across several social-related regions (e.g., the left inferior frontal gyrus, insula, amygdala, supramarginal gyrus, bilateral superior temporal poles) in children with ASD.
CONCLUSION: Topological disorganization in the autistic brain network varies across developmental stages, shifting from reduced global integration in childhood to enhanced segregation of social-brain circuits in adolescence. Such atypical WM structural organization may underlie the persistent social cognitive deficits observed in ASD.
METHODS: Diffusion/T1-weighted brain imaging data were acquired from 69 individuals with ASD (age: 6-17 years) and 71 age- and sex-matched typically developing controls. Global and nodal topological properties of WM structural networks were computed, and 28 social-related regions were examined through subnetwork and nodal analyses. Case-control comparisons of global and nodal graph metrics were conducted separately for children and adolescents.
RESULTS: The children with ASD exhibited reduced integration of the whole-brain network, reflected by increased characteristic path length and decreased global efficiency. In contrast, the adolescents with ASD showed enhanced segregation within the social-brain subnetwork, indicated by increased clustering coefficient and local efficiency. Nodal analyses revealed reduced nodal efficiency across several social-related regions (e.g., the left inferior frontal gyrus, insula, amygdala, supramarginal gyrus, bilateral superior temporal poles) in children with ASD.
CONCLUSION: Topological disorganization in the autistic brain network varies across developmental stages, shifting from reduced global integration in childhood to enhanced segregation of social-brain circuits in adolescence. Such atypical WM structural organization may underlie the persistent social cognitive deficits observed in ASD.