The Dynamic Spatiotemporal Features Based on Rich Club Organization in Autism Spectrum Disorder

The dynamic operational mechanisms of the brain in autism spectrum disorder (ASD) remain unclear. In this study, utilizing resting-state functional magnetic resonance imaging (fMRI) technology, we aimed to analyze the spatiotemporal characteristics of brain networks based on the rich club Organization, extracting time-varying features in individuals with ASD. We evaluated differences in spatiotemporal similarity of dynamic brain networks between ASD patients and healthy controls (HC). Results revealed unstable composition of the rich club in ASD patients over time, with weaker spatiotemporal similarity compared to healthy controls. Furthermore, employing spatiotemporal transformation features based on network topology, we classified ASD patients and healthy controls. Our findings demonstrate higher classification accuracy using time-varying features compared to static brain network topology features. This study enhances our understanding of the dynamic brain network mechanisms in ASD and suggests reliable methods for early diagnosis.