Latent and Abnormal Functional Connectivity Circuits in Autism Spectrum Disorder - Chen, Shuo; Xing, Yishi; Kang, Jian (Frontiers in Neuroscience, 2017)
Autism spectrum disorders (ASD) are associated with disrupted brain networks. Neuromimaging techniques provide a non-invasive pathway to understand the underlying abnormal connectivity patterns in ASDs. In this study, we investigate the differentially expressed functional connectivity networks between patients of ASD and typical controls (TC) by using the neuroimaging data sets from the Autism Brain Imaging Data Exchange (ABIDE) project. Specifically, we focus on examining the characteristics of intrinsic functional connectivity (FC) based on the data collected by using the resting state functional magnetic resonance imaging (rs-fMRI) technique. We aim to extract disrupted brain connectivity patterns in the unit of networks instead of individual edges by leveraging the advanced statistical methods. Unlike many brain connectome studies that pre-specify the networks and then compare the connectivity of edges within the networks between clinical groups, we detect the latent differentially expressed networks automatically. Our network level analysis results successfully identify abnormal connectome networks that i) include a high proportion proportion of differentially expressed edges between ASDs and TCs; and (ii) show well-organized graph topological structures. These findings may provide a new perspective to study the underlying neuropsychiatric mechanism of ASD.