title: Atomic dynamic functional interaction patterns for characterization of ADHD.
abstract: Modeling abnormal temporal dynamics of functional interactions in psychiatric disorders has been of great interest in the neuroimaging field, and thus a variety of methods have been proposed so far. However, the temporal dynamics and disease-related abnormalities of functional interactions within specific data-driven discovered subnetworks have been rarely explored yet. In this work, we propose a novel computational framework composed of an effective Bayesian connectivity change point model for modeling functional brain interactions and their dynamics simultaneously and an effective variant of nonnegative matrix factorization for assessing the functional interaction abnormalities within subnetworks. This framework has been applied on the resting state fmagnetic resonance imaging (fMRI) datasets of 23 children with attention-deficit/hyperactivity disorder (ADHD) and 45 normal control (NC) children, and has revealed two atomic functional interaction patterns (AFIPs) discovered for ADHD and another two AFIPs derived for NC. Together, these four AFIPs could be grouped into two pairs, one common pair representing the common AFIPs in ADHD and NC, and the other abnormal pair representing the abnormal AFIPs in ADHD. Interestingly, by comparing the abnormal AFIP pair, two data-driven abnormal functional subnetworks are derived. Strikingly, by evaluating the approximation based on the four AFIPs, all of the ADHD children were successfully differentiated from NCs without any false positive.
authors.affiliation: School of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
authors.forename: Jinli
authors.initials: J
authors.lastname: Ou
authors.forename: Zhichao
authors.initials: Z
authors.lastname: Lian
authors.forename: Li
authors.initials: L
authors.lastname: Xie
authors.forename: Xiang
authors.initials: X
authors.lastname: Li
authors.forename: Peng
authors.initials: P
authors.lastname: Wang
authors.forename: Yun
authors.initials: Y
authors.lastname: Hao
authors.forename: Dajiang
authors.initials: D
authors.lastname: Zhu
authors.forename: Rongxin
authors.initials: R
authors.lastname: Jiang
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Wang
authors.forename: Yaowu
authors.initials: Y
authors.lastname: Chen
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.forename: Tianming
authors.initials: T
authors.lastname: Liu
mesh_terms: D001289:Attention Deficit Disorder with Hyperactivity / Q000473:pathology*; D001499:Bayes Theorem; D001921:Brain / Q000098:blood supply / Q000503:physiopathology*; D001931:Brain Mapping; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D017711:Nonlinear Dynamics; D010100:Oxygen / Q000097:blood
chemical_list: D010100:Oxygen
keywords: ADHD; brain networks; functional interaction; nonnegative matrix factorization; temporal dynamics