Network Representations of Facial and Bodily Expressions: Evidence From Multivariate Connectivity Pattern Classification.

ABSTRACT: Emotions can be perceived from both facial and bodily expressions. Our previous study has found the successful decoding of facial expressions based on the functional connectivity (FC) patterns. However, the role of the FC patterns in the recognition of bodily expressions remained unclear, and no neuroimaging studies have adequately addressed the question of whether emotions perceiving from facial and bodily expressions are processed rely upon common or different neural networks. To address this, the present study collected functional magnetic resonance imaging (fMRI) data from a block design experiment with facial and bodily expression videos as stimuli (three emotions: anger, fear, and joy), and conducted multivariate pattern classification analysis based on the estimated FC patterns. We

SUBMITTER: Liang Y 

PROVIDER: S-EPMC6828617 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature