Visual adaptation selective for individual limbs reveals hierarchical human body representation

Alexander Bratch, Yixiong Chen, Stephen A. Engel, Daniel J. Kersten

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The spatial relationships between body parts are a rich source of information for person perception, with even simple pairs of parts providing highly valuable information. Computation of these relationships would benefit from a hierarchical representation, where body parts are represented individually. We hypothesized that the human visual system makes use of such representations. To test this hypothesis, we used adaptation to determine whether observers were sensitive to changes in the length of one body part relative to another. Observers viewed forearm/upper arm pairs where the forearm had been either lengthened or shortened, judging the perceived length of the forearm. Observers then adapted to a variety of different stimuli (e.g., arms, objects, etc.) in different orientations and visual field locations. We found that following adaptation to distorted limbs, but not non-limb objects, observers experienced a shift in perceived forearm length. Furthermore, this effect partially transferred across different orientations and visual field locations. Taken together, these results suggest the effect arises in high level mechanisms specialized for specific body parts, providing evidence for a representation of bodies based on parts and their relationships.

Original languageEnglish (US)
Pages (from-to)1-10
Number of pages10
JournalJournal of vision
Issue number5
StatePublished - 2021

Bibliographical note

Funding Information:
Supported by the National Institutes of Health (NIH) Training Grant in Neuroimaging (NIH T32 EB008389), the NIH Training Grant in Translational Vision Sciences (NIH T32 EY025187), and by NIH R01 EY029700.

Publisher Copyright:
© 2021. All Rights Reserved.


  • body perception
  • hierarchical processing
  • visual adaptation

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural


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