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Aberrant dynamic minimal spanning tree parameters within default mode network in patients with autism spectrum
Huibin Jia1,2, Xiangci Wu1,2, Zhiyu Wu3
1Institute of Psychology and Behavior, Henan University, Kaifeng, China.
Frontiers in Psychiatry
|October 3, 2022
Summary
Autism spectrum disorder (ASD) is linked to altered brain connectivity within the default mode network (DMN). Reduced information exchange and increased volatility in the DMN correlate with ASD symptom severity.
Area of Science:
- Neuroscience
- Developmental Neuroscience
- Computational Neuroscience
Background:
- Altered functional connectivity (FC) and temporal dynamics in cortical networks, particularly the default mode network (DMN), are implicated in Autism Spectrum Disorder (ASD).
- Understanding these alterations may offer insights into the neurobiological underpinnings of ASD.
Purpose of the Study:
- To investigate alterations in the topographical organization and temporal dynamics of the DMN in individuals with ASD.
- To examine the relationship between these DMN alterations and autistic symptom severity.
Main Methods:
- Utilized resting-state functional magnetic resonance imaging (fMRI) data from the Autism Brain Imaging Data Exchange (ABIDE) project.
- Applied the minimal spanning tree (MST) technique to construct time-varying complex networks of the DMN.
- Analyzed temporal mean and variance of MST parameters to assess information exchange efficiency and volatility.
Main Results:
- Individuals with ASD exhibited significantly lower information exchange efficiencies within the DMN compared to neurotypical controls.
- The DMN in individuals with ASD demonstrated greater volatility in temporal dynamics.
- These DMN alterations were significantly associated with the severity of autistic symptoms.
Conclusions:
- The study provides evidence for altered functional network organization and temporal dynamics within the DMN in ASD.
- These findings suggest that DMN abnormalities contribute to the neurobiological profile of ASD and correlate with symptom severity.
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