Computation-Based Feature Representation of Body Expressions in the Human Brain

Marta Poyo Solanas, Maarten Vaessen, Beatrice de Gelder*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Web of Science)

Abstract

Humans and other primate species are experts at recognizing body expressions. To understand the underlying perceptual mechanisms, we computed postural and kinematic features from affective whole-body movement videos and related them to brain processes. Using representational similarity and multivoxel pattern analyses, we showed systematic relations between computation-based body features and brain activity. Our results revealed that postural rather than kinematic features reflect the affective category of the body movements. The feature limb contraction showed a central contribution in fearful body expression perception, differentially represented in action observation, motor preparation, and affect coding regions, including the amygdala. The posterior superior temporal sulcus differentiated fearful from other affective categories using limb contraction rather than kinematics. The extrastriate body area and fusiform body area also showed greater tuning to postural features. The discovery of midlevel body feature encoding in the brain moves affective neuroscience beyond research on high-level emotion representations and provides insights in the perceptual features that possibly drive automatic emotion perception.

Original languageEnglish
Pages (from-to)6376-6390
Number of pages15
JournalCerebral Cortex
Volume30
Issue number12
Early online date7 Aug 2020
DOIs
Publication statusPublished - Dec 2020

Keywords

  • body
  • emotion
  • fMRI
  • movement
  • posture
  • TRANSCRANIAL MAGNETIC STIMULATION
  • NEURAL MECHANISMS
  • EMOTIONAL EXPRESSIONS
  • COGNITIVE FUNCTIONS
  • FACIAL EXPRESSION
  • BIOLOGICAL MOTION
  • CINGULATE CORTEX
  • MOTOR AREA
  • PERCEPTION
  • PREMOTOR

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