title: Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia.
abstract: Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting-state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia, which may underscore the abnormal brain performance in this mental illness.
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA. Electronic address: qyu@mrn.org.
authors.forename: Qingbao
authors.initials: Q
authors.lastname: Yu
authors.affiliation: Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87113, USA.
authors.forename: Erik B
authors.initials: EB
authors.lastname: Erhardt
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Sui
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; School of Information and Communication Engineering, North University of China, Taiyuan 030051, China.
authors.forename: Yuhui
authors.initials: Y
authors.lastname: Du
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: He
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; Department of Computer Science, University of New Mexico, Albuquerque, NM 87106, USA.
authors.forename: Devon
authors.initials: D
authors.lastname: Hjelm
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; Department of Computer Science, University of New Mexico, Albuquerque, NM 87106, USA.
authors.forename: Mustafa S
authors.initials: MS
authors.lastname: Cetin
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA.
authors.forename: Srinivas
authors.initials: S
authors.lastname: Rachakonda
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA.
authors.forename: Robyn L
authors.initials: RL
authors.lastname: Miller
authors.affiliation: Olin Neuropsychiatry Research Center, Hartford, CT 06106, USA; Department of Psychiatry, Yale University, New Haven, CT 06520, USA; Department of Neurobiology, Yale University, New Haven, CT 06520, USA.
authors.forename: Godfrey
authors.initials: G
authors.lastname: Pearlson
authors.affiliation: The Mind Research Network, Albuquerque, NM 87106, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA; Olin Neuropsychiatry Research Center, Hartford, CT 06106, USA; Department of Psychiatry, Yale University, New Haven, CT 06520, USA. Electronic address: vcalhoun@unm.edu.
authors.forename: Vince D
authors.initials: VD
authors.lastname: Calhoun
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000473:pathology; D012559:Schizophrenia / Q000473:pathology*; D055815:Young Adult
keywords: Brain graph; Dynamic; ICA; R-fMRI; Schizophrenia; Time varying