title: Spontaneous functional network dynamics and associated structural substrates in the human brain.
abstract: Recent imaging connectomics studies have demonstrated that the spontaneous human brain functional networks derived from resting-state functional MRI (R-fMRI) include many non-trivial topological properties, such as highly efficient small-world architecture and densely connected hub regions. However, very little is known about dynamic functional connectivity (D-FC) patterns of spontaneous human brain networks during rest and about how these spontaneous brain dynamics are constrained by the underlying structural connectivity. Here, we combined sub-second multiband R-fMRI data with graph-theoretical approaches to comprehensively investigate the dynamic characteristics of the topological organization of human whole-brain functional networks, and then employed diffusion imaging data in the same participants to further explore the associated structural substrates. At the connection level, we found that human whole-brain D-FC patterns spontaneously fluctuated over time, while homotopic D-FC exhibited high connectivity strength and low temporal variability. At the network level, dynamic functional networks exhibited time-varying but evident small-world and assortativity architecture, with several regions (e.g., insula, sensorimotor cortex and medial prefrontal cortex) emerging as functionally persistent hubs (i.e., highly connected regions) while possessing large temporal variability in their degree centrality. Finally, the temporal characteristics (i.e., strength and variability) of the connectional and nodal properties of the dynamic brain networks were significantly associated with their structural counterparts. Collectively, we demonstrate the economical, efficient, and flexible characteristics of dynamic functional coordination in large-scale human brain networks during rest, and highlight their relationship with underlying structural connectivity, which deepens our understandings of spontaneous brain network dynamics in humans.
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China ; Center for Cognition and Brain Disorders, Hangzhou Normal University Hangzhou, China.
authors.forename: Xuhong
authors.initials: X
authors.lastname: Liao
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Yuan
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Tengda
authors.initials: T
authors.lastname: Zhao
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Zhengjia
authors.initials: Z
authors.lastname: Dai
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Ni
authors.initials: N
authors.lastname: Shu
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Mingrui
authors.initials: M
authors.lastname: Xia
authors.affiliation: Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health Baltimore, MD, USA.
authors.forename: Yihong
authors.initials: Y
authors.lastname: Yang
authors.affiliation: McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
authors.forename: Alan
authors.initials: A
authors.lastname: Evans
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: He
keywords: connectomics; functional dynamics; graph theory; hub; sliding window; small-world