Arousal impacts distributed hubs modulating the integration of brain functional connectivity

NeuroImage

Corey Horien¹  R. Todd Constable²  Bronwen Garand-Sheridan³  Fuyuze Tokoglu⁴  Dustin Scheinost⁵  Kangjoo Lee⁵  Evelyn M.R. Lake⁵  David O'Connor⁶ 

[1] Corresponding author.;Department of Biomedical Engineering, Yale University, New Haven, CT 06520, United States;Department of Biomedical Engineering, Yale University, New Haven, CT 06520, United States;Department of Music, Yale University, New Haven, CT 06520, United States;Department of Radiology and Bioimaging Sciences, Yale University School of Medicine, New Haven, CT 06520, United States;Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, United States;

关键词: Arousal;    Network hubs;    Resting state;    fMRI;    Pupillometry;   

DOI  :  

来源: DOAJ

【 摘 要 】

Even when subjects are at rest, it is thought that brain activity is organized into distinct brain states during which reproducible patterns are observable. Yet, it is unclear how to define or distinguish different brain states. A potential source of brain state variation is arousal, which may play a role in modulating functional interactions between brain regions. Here, we use simultaneous resting state functional magnetic resonance imaging (fMRI) and pupillometry to study the impact of arousal levels indexed by pupil area on the integration of large-scale brain networks. We employ a novel sparse dictionary learning-based method to identify hub regions participating in between-network integration stratified by arousal, by measuring k-hubness, the number (k) of functionally overlapping networks in each brain region. We show evidence of a brain-wide decrease in between-network integration and inter-subject variability at low relative to high arousal, with differences emerging across regions of the frontoparietal, default mode, motor, limbic, and cerebellum networks. State-dependent changes in k-hubness relate to the actual patterns of network integration within these hubs, suggesting a brain state transition from high to low arousal characterized by global synchronization and reduced network overlaps. We demonstrate that arousal is not limited to specific brain areas known to be directly associated with arousal regulation, but instead has a brain-wide impact that involves high-level between-network communications. Lastly, we show a systematic change in pairwise fMRI signal correlation structures in the arousal state-stratified data, and demonstrate that the choice of global signal regression could result in different conclusions in conventional graph theoretical analysis and in the analysis of k-hubness when studying arousal modulations. Together, our results suggest the presence of global and local effects of pupil-linked arousal modulations on resting state brain functional connectivity.

【 授权许可】

Unknown