Idiosyncratic organization of cortical networks in autism spectrum disorder

Abstract

Neuroimaging studies of Autism Spectrum Disorder (ASD) have yielded inconsistent results indicating either increases or decreases in functional connectivity, or both. Recent findings suggest that these seemingly divergent results might be underpinned by greater inter-individual variability in brain network connectivity in ASD. We tested the hypothesis that the spatial patterns of intrinsic connectivity networks (ICNs) are more idiosyncratic in ASD, and demonstrated that this increased variability is associated with symptomatology. We estimated whole brain functional connectivity based on resting state functional magnetic resonance imaging (fMRI) data obtained from the Autism Brain Imaging Data Exchange I & II (ABIDE I & II) repository: 422 (69 females) participants with ASD and 424 (59 females) typically developing (TD) participants between 6 and 30 years of age. We clustered individuals' patterns of resting state functional connectivity into seven networks, each representing an ICN, and assessed the heterogeneity of each vertex on the cortical surface across individuals in terms of its incorporation into a particular ICN. We found that the incorporation of individual anatomical locations (vertices) to a common network was less consistent across individuals in ASD, indicating a more idiosyncratic organization of ICNs in the ASD brain. This spatial shifting effect was particularly pronounced in the Sensory-Motor Network (SMN) and the Default Mode Network (DMN). We also found that this idiosyncrasy in large-scale brain network organization was correlated with ASD symptomatology (ADOS). These results support the view that idiosyncratic functional connectivity is a hallmark of the ASD brain. We provide the first evidence that the anatomical organization of ICNs is idiosyncratic in ASD, as well as providing evidence that such abnormalities in brain network organization may contribute to the symptoms of ASD.

Keywords: Autism spectrum disorder; Functional connectivity; Intrinsic connectivity network; Network clustering; Resting state; fMRI.