Frontiers in Psychiatry (Aug 2022)

Alterations in brain networks in children with sub-threshold autism spectrum disorder: A magnetoencephalography study

  • Yuka Shiota,
  • Yuka Shiota,
  • Yuka Shiota,
  • Daiki Soma,
  • Tetsu Hirosawa,
  • Tetsu Hirosawa,
  • Yuko Yoshimura,
  • Yuko Yoshimura,
  • Yuko Yoshimura,
  • Sanae Tanaka,
  • Sanae Tanaka,
  • Chiaki Hasegawa,
  • Chiaki Hasegawa,
  • Chiaki Hasegawa,
  • Ken Yaoi,
  • Ken Yaoi,
  • Sumie Iwasaki,
  • Sumie Iwasaki,
  • Masafumi Kameya,
  • Shigeru Yokoyama,
  • Shigeru Yokoyama,
  • Mitsuru Kikuchi,
  • Mitsuru Kikuchi,
  • Mitsuru Kikuchi

DOI
https://doi.org/10.3389/fpsyt.2022.959763
Journal volume & issue
Vol. 13

Abstract

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Individuals with sub-threshold autism spectrum disorder (ASD) are those who have social communication difficulties but do not meet the full ASD diagnostic criteria. ASD is associated with an atypical brain network; however, no studies have focused on sub-threshold ASD. Here, we used the graph approach to investigate alterations in the brain networks of children with sub-threshold ASD, independent of a clinical diagnosis. Graph theory is an effective approach for characterizing the properties of complex networks on a large scale. Forty-six children with ASD and 31 typically developing children were divided into three groups (i.e., ASD-Unlikely, ASD-Possible, and ASD-Probable groups) according to their Social Responsiveness Scale scores. We quantified magnetoencephalographic signals using a graph-theoretic index, the phase lag index, for every frequency band. Resultantly, the ASD-Probable group had significantly lower small-worldness (SW) in the delta, theta, and beta bands than the ASD-Unlikely group. Notably, the ASD-Possible group exhibited significantly higher SW than the ASD-Probable group and significantly lower SW than the ASD-Unlikely group in the delta band only. To our knowledge, this was the first report of the atypical brain network associated with sub-threshold ASD. Our findings indicate that magnetoencephalographic signals using graph theory may be useful in detecting sub-threshold ASD.

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