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Functional network abnormalities consistent with behavioral profile in Autism Spectrum Disorder.

René Besseling1, Rolf Lamerichs2, Britt Michels3

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This study used the iCAPs model to analyze brain activity in autism spectrum disorder (ASD). Findings reveal distinct functional connectivity abnormalities in ASD, particularly in emotional and visual processing networks.

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Area of Science:

  • Neuroimaging
  • Neuroscience
  • Biomarkers

Background:

  • Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with varied symptom severity.
  • Resting-state functional magnetic resonance imaging (fMRI) is crucial for understanding brain function in ASD.
  • Identifying reliable biomarkers is essential for diagnosing and managing ASD.

Purpose of the Study:

  • To employ the innovation-driven co-activation patterns (iCAPs) model to identify functional imaging biomarkers for ASD.
  • To investigate functional brain abnormalities in ASD using resting-state fMRI data.
  • To correlate network dynamics with behavioral domains in individuals with ASD.

Main Methods:

  • Utilized resting-state fMRI data from 125 individuals with ASD and 243 healthy controls from the ABIDE repository.
  • Applied the iCAPs model to analyze spatio-temporal patterns and derive network time series.
  • Calculated the temporal standard deviation of iCAPs to quantify network dynamics and compared between groups.

Main Results:

  • Identified significant abnormalities in functional networks involving subcortical, limbic, and default mode network regions in individuals with ASD.
  • Observed abnormalities in emotional and visual behavioral subdomains, with greater severity in autism compared to Asperger's syndrome.
  • Detected a trend towards impaired social cognition networks in the ASD group.

Conclusions:

  • The iCAPs model successfully identified functional neuroimaging biomarkers for ASD.
  • Functional connectivity alterations in ASD align with observed behavioral impairments, particularly in emotional and visual processing.
  • These findings contribute to a deeper understanding of the neural underpinnings of ASD.