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Increased Segregation in Functional Connectivity Networks When Watching Unpleasant Arousing Videos: A Generalized
Yuqian Ni1, Xia Zheng2, Richard Betzel3
1The Media School, Indiana University Bloomington, Bloomington, Indiana, USA.
Viewing unpleasant, arousing videos significantly alters brain functional connectivity (FC), leading to increased network segregation, particularly in association systems. This suggests a shift in brain state due to highly aversive stimuli.
Area of Science:
- Neuroscience
- Cognitive Neuroscience
- Affective Neuroscience
Background:
- Functional connectivity (FC) properties, including network integration and segregation, are linked to human behaviors like attention and motor tasks.
- Previous research indicates that attention increases integration, while simple motor tasks increase segregation.
Purpose of the Study:
- To investigate how viewing video clips varying in valence and arousal affects integration-segregation properties in task-based FC networks.
- To explore changes in brain network dynamics in response to different affective stimuli.
Main Methods:
- Analysis of an open dataset using generalized psychophysiological interaction (gPPI) analysis.
- Application of network analysis and community detection to examine brain network dynamics during video viewing.
- Categorization of videos based on affective valence (unpleasant/pleasant) and arousal (arousing/calm).
Main Results:
- Unpleasant arousing videos caused greater FC deviation from baseline (task-induced FC deviation [tiFCd]).
- These videos perturbed the brain into a more segregated state compared to other video types.
- Increased segregation was specifically observed in association systems, not sensorimotor systems.
Conclusions:
- Unpleasant arousing content induces a distinct brain state, potentially related to disengagement or heightened alertness.
- Combining gPPI analysis with community detection and network segregation measures enhances understanding of behavior-brain state links.
- Affective stimuli significantly influence brain network dynamics, particularly the balance between integration and segregation.
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