An fMRI-Based Centrality Analysis of Brain Connectivity in Autism Spectrum Disorder

Recent studies have probed Autism Spectral Disorder's (ASD's) neural substrates, analyzing brain connectivity patterns through techniques like centrality using the resting-state functional Magnetic Resonance imaging (rs-fMRI) data, revealing deficits in social communication, repetitive beh...

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Bibliographic Details
Main Authors: Uday, Nayana, George, Judy K, Sherly, Elizabeth
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Autism
Autism spectral disorders (ASD)
Brain modeling
Brain network
Centrality
Correlation
Functional connectivity (FC)
Functional magnetic resonance imaging
Functional magnetic resonance imaging (fMRI)
IEEE Regions
Machine learning
Measurement
Neuroimaging
Organizations
Substrates
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Description
Summary:Recent studies have probed Autism Spectral Disorder's (ASD's) neural substrates, analyzing brain connectivity patterns through techniques like centrality using the resting-state functional Magnetic Resonance imaging (rs-fMRI) data, revealing deficits in social communication, repetitive behaviors, and sensory processing. This research aims to observe alterations in information flow and communication networks by assessing the centrality of key brain regions, distinguishing individuals with ASD from neurotypical controls. Evaluating centrality measures' accuracy using a Graph Attention Network (GAT) model classifier and model interpretability with the attention score visualization unveils significant contributors to the model's performance, providing insights into ASD's neural mechanisms and enhancing our understanding of brain connectivity in this disorder.
ISSN:2642-6102
DOI:10.1109/TENSYMP61132.2024.10752195