Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain

Hongru Zhu, Yijun Ge, Alexander Bratch, Alan Yuille, Kendrick Kay, Daniel Kersten

Research output: Contribution to journalArticlepeer-review

Abstract

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

Original languageEnglish (US)
Article numbere2317707121
JournalProceedings of the National Academy of Sciences of the United States of America
Volume121
Issue number24
DOIs
StatePublished - Jun 11 2024

Bibliographical note

Publisher Copyright:
© 2024 the Author(s).

Keywords

  • 3D pose
  • body perception
  • natural images
  • visual cortex

PubMed: MeSH publication types

  • Journal Article

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