Arousal impacts distributed hubs modulating the integration of brain functional connectivity

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Functional Neuroimaging

Background:

• Resting-state brain activity exhibits reproducible patterns, but distinct brain states and their modulators remain unclear.
• Arousal is a potential factor influencing functional interactions between brain regions.
• Understanding arousal's role is crucial for defining brain states and their impact on connectivity.

Purpose of the Study:

• To investigate the impact of arousal levels, indexed by pupil area, on large-scale brain network integration during rest.
• To identify brain regions involved in between-network integration across different arousal levels.
• To explore how arousal modulates functional connectivity and network organization.

Main Methods:

• Simultaneous resting-state functional magnetic resonance imaging (fMRI) and pupillometry were employed.
• A novel sparse dictionary learning method was used to measure k-hubness, quantifying network overlaps in brain regions.
• Brain network integration was analyzed, stratified by arousal levels derived from pupil data.

Main Results:

• Arousal significantly impacts brain-wide functional connectivity, with decreased integration and inter-subject variability observed at lower arousal levels.
• Differences in network integration were found across multiple large-scale brain networks, including frontoparietal, default mode, motor, limbic, and cerebellum.
• State-dependent changes in k-hubness indicate a transition towards global synchronization and reduced network overlaps with decreasing arousal.

Conclusions:

• Pupil-linked arousal exerts a brain-wide influence on functional connectivity, extending beyond known arousal-regulating areas.
• Arousal modulates high-level between-network communication and integration, suggesting a global effect on brain states.
• Findings highlight the importance of considering arousal in functional connectivity studies and its potential impact on analytical conclusions, particularly concerning global signal regression.