Topological Alterations in Brain Functional Connectivity between ASD and Typically Developing Individuals: A Graph-Theoretical Analysis using Multi-Site Resting-State fMRI Data

Abstract Autism spectrum disorder (ASD) is increasingly conceptualized as a disorder of large-scale functional brain network organization rather than isolated regional abnormalities. Graph-theoretical analysis provides a principled framework for characterizing such distributed network reconfiguration. Here, we investigated global, nodal, and system-level functional network topology in ASD using a large, multi-site resting-state fMRI dataset. Resting-state fMRI data from 996 participants (428 ASD, 568 healthy controls) were obtained from the ABIDE I and II data repositories. Whole-brain weighted resting state functional networks were constructed using Pearson correlation. To improve robustness and reduce threshold-selection bias, graph-theoretical metrics were computed across a range of network sparsity thresholds and summarized using an area-under-the-curve (AUC) approach. At the global level, ASD was associated with reduced assortativity, and local efficiency, along with altered normalized characteristic path length (λ), indicating local information processing and subtle deviations in network integration relative to an optimal small-world topology. Nodal analyses revealed non-random, region-specific alterations predominantly affecting higher-order associative systems. Increased nodal centrality and hub-like properties were observed in frontal and parietal regions within the frontoparietal control and dorsal attention networks, whereas reduced nodal efficiency and centrality were primarily localized to limbic and anterior temporal regions, including the temporal pole. System-level analyses, controlling for age, sex, and acquisition site, further demonstrated network-specific topological reorganization across multiple functional systems. Clinical correlation analyses identified modest but significant associations between nodal topology and core ASD symptom severity, particularly within default mode, limbic, and attention networks. Together, these findings indicate that ASD is characterized by subtle yet reproducible multi-scale reorganization of functional brain network topology, supporting a systems-level account of ASD neurobiology and highlighting the clinical relevance of large-scale network architecture.