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Investigation of functional brain network reconfiguration during vocal emotional processing using graph-theoretical analysis
Abstract
Vocal expression is essential for conveying the emotion during social interaction. Although vocal emotion has been explored in previous studies, little is known about how perception of different vocal emotional expressions modulates the functional brain network topology. In this study, we aimed to investigate the functional brain networks under different attributes of vocal emotion by graph-theoretical network analysis. Functional magnetic resonance imaging (fMRI) experiments were performed on 36 healthy participants. We utilized the Power-264 functional brain atlas to calculate the interregional functional connectivity (FC) from fMRI data under resting state and vocal stimuli at different arousal and valence levels. The orthogonal minimal spanning trees method was used for topological filtering. The paired-sample t-test with Bonferroni correction across all regions and arousal–valence levels were used for statistical comparisons. Our results show that brain network exhibits significantly altered network attributes at FC, nodal and global levels, especially under high-arousal or negative-valence vocal emotional stimuli. The alterations within/between well-known large-scale functional networks were also investigated. Through the present study, we have gained more insights into how comprehending emotional speech modulates brain networks. These findings may shed light on how the human brain processes emotional speech and how it distinguishes different emotional conditions.
Figures
Significant changes of FC associated with arousal stimuli and resting state.
Significant changes of FC associated with arousal stimuli and resting state.
Significant changes of averaged intra-network or inter-network FCs with respect to the 12 large-scale functional networks (without CB and unlabeled) associated with the valence stimuli and resting state.
Significant changes of averaged intra-network or inter-network FCs with respect to the 12 large-scale functional networks (without CB and unlabeled) associated with the valence stimuli and resting state.
Keywords
functional magnetic resonance imaging | vocal emotion | resting state | brain network | graph-theoretical analysis
Authors
Publication Date
2019/04/10
Journal
Social Cognitive and Affective Neuroscience
Social Cognitive and Affective Neuroscience 2019 Vol. 14
DOI
10.1093/scan/nsz025
Publisher
Oxford University Press