title: Latent and Abnormal Functional Connectivity Circuits in Autism Spectrum Disorder.
abstract: Autism spectrum disorder (ASD) is associated with disrupted brain networks. Neuroimaging techniques provide noninvasive methods of investigating abnormal connectivity patterns in ASD. In the present study, we compare functional connectivity networks in people with ASD with those in typical controls, using neuroimaging data from the Autism Brain Imaging Data Exchange (ABIDE) project. Specifically, we focus on the characteristics of intrinsic functional connectivity based on data collected by resting-state functional magnetic resonance imaging (rs-fMRI). Our aim was to identify disrupted brain connectivity patterns across all networks, instead of in individual edges, by using advanced statistical methods. Unlike many brain connectome studies, in which networks are prespecified before the edge connectivity in each network is compared between clinical groups, we detected the latent differentially expressed networks automatically. Our network-level analysis identified abnormal connectome networks that (i) included a high proportion of edges that were differentially expressed between people with ASD and typical controls; and (ii) showed highly-organized graph topology. These findings provide new insight into the study of the underlying neuropsychiatric mechanism of ASD.
authors.affiliation: Department of Epidemiology and Biostatistics, University of Maryland College Park, MD USA.
authors.forename: Shuo
authors.initials: S
authors.lastname: Chen
authors.affiliation: Department of Epidemiology and Biostatistics, University of Maryland College Park, MD USA.
authors.forename: Yishi
authors.initials: Y
authors.lastname: Xing
authors.affiliation: Department of Biostatistics, University of Michigan Ann Arbor, MI, USA.
authors.forename: Jian
authors.initials: J
authors.lastname: Kang
keywords: Autism spectrum disorder; biomarker; brain connectivity; fMRI; graph topology; network