Arousal impacts distributed hubs modulating the integration of brain functional connectivity

被引:9
|
作者
Lee, Kangjoo [1 ]
Horien, Corey [2 ]
O'Connor, David [3 ]
Garand-Sheridan, Bronwen [4 ]
Tokoglu, Fuyuze [1 ]
Scheinost, Dustin [1 ,3 ,5 ,6 ]
Lake, Evelyn M. R. [1 ]
Constable, R. Todd [1 ,3 ,7 ]
机构
[1] Yale Univ, Sch Med, Dept Radiol & Bioimaging Sci, New Haven, CT 06520 USA
[2] Yale Univ, Sch Med, Interdept Neurosci Program, New Haven, CT 06520 USA
[3] Yale Univ, Dept Biomed Engn, New Haven, CT 06520 USA
[4] Yale Univ, Dept Mus, New Haven, CT 06520 USA
[5] Yale Univ, Child Study Ctr, Sch Med, New Haven, CT 06520 USA
[6] Yale Univ, Dept Stat & Data Sci, New Haven, CT 06511 USA
[7] Yale Univ, Sch Med, Dept Neurosurg, New Haven, CT 06520 USA
关键词
Arousal; Network hubs; Resting state; fMRI; Pupillometry; PROPOFOL-INDUCED LOSS; DEFAULT MODE NETWORK; RESTING-STATE; GLOBAL SIGNAL; HEAD MOTION; FMRI; FLUCTUATIONS; CONNECTOME; ARCHITECTURE; WAKEFULNESS;
D O I
10.1016/j.neuroimage.2022.119364
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
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.
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收藏
页数:17
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