Evidence map›Paper›PMID 34007989›Full record

ArticleJournal of vision2021

Visual adaptation selective for individual limbs reveals hierarchical human body representation.

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

Abstract read
In one paragraph

Article in Journal of vision, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alexander BratchDepartment of Psychology, University of Minnesota, Minneapolis, MN, USA.
Yixiong ChenDepartment of Psychology, University of Minnesota, Minneapolis, MN, USA.
Stephen A EngelDepartment of Psychology, University of Minnesota, Minneapolis, MN, USA.
Daniel J KerstenDepartment of Psychology, University of Minnesota, Minneapolis, MN, USA.

Funding

Integrative Training Program in NeuroimagingT32EB008389 · NIBIB · UNIVERSITY OF MINNESOTA · PI CHEN, WEI · 2008 to 2019
$1.4M
Towards a Compositional Generative Model of Human VisionR01EY029700 · NEI · UNIVERSITY OF MINNESOTA · PI KERSTEN, DANIEL J · 2019 to 2022
$1.3M
Training Program in Translational Vision SciencesT32EY025187 · NEI · UNIVERSITY OF MINNESOTA · PI Glenn P Lobo, LINDA K. MCLOON · 2016 to 2026
$1.2M
NEI NIH HHS R01 EY029700NEI NIH HHS T32 EY025187NIBIB NIH HHS T32 EB008389
6 · The paper itself

Abstract

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.

Indexed as

Body ImageHuman BodyArmHumansVisual Perception

Identifiers

PMID34007989
PMCPMC8142707

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.