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The material-weight illusion is a Bayes-optimal percept under competing density priors
The material-weight illusion (MWI) is one example in a class of weight perception illusions that seem to defy principled explanation. In this illusion, when an observer lifts two objects of the same size and mass, but that appear to be made of different materials, the denser-looking (e.g., metal-loo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186408/ https://www.ncbi.nlm.nih.gov/pubmed/30324029 http://dx.doi.org/10.7717/peerj.5760 |
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author | Peters, Megan A.K. Zhang, Ling-Qi Shams, Ladan |
author_facet | Peters, Megan A.K. Zhang, Ling-Qi Shams, Ladan |
author_sort | Peters, Megan A.K. |
collection | PubMed |
description | The material-weight illusion (MWI) is one example in a class of weight perception illusions that seem to defy principled explanation. In this illusion, when an observer lifts two objects of the same size and mass, but that appear to be made of different materials, the denser-looking (e.g., metal-look) object is perceived as lighter than the less-dense-looking (e.g., polystyrene-look) object. Like the size-weight illusion (SWI), this perceptual illusion occurs in the opposite direction of predictions from an optimal Bayesian inference process, which predicts that the denser-looking object should be perceived as heavier, not lighter. The presence of this class of illusions challenges the often-tacit assumption that Bayesian inference holds universal explanatory power to describe human perception across (nearly) all domains: If an entire class of perceptual illusions cannot be captured by the Bayesian framework, how could it be argued that human perception truly follows optimal inference? However, we recently showed that the SWI can be explained by an optimal hierarchical Bayesian causal inference process (Peters, Ma & Shams, 2016) in which the observer uses haptic information to arbitrate among competing hypotheses about objects’ possible density relationship. Here we extend the model to demonstrate that it can readily explain the MWI as well. That hierarchical Bayesian inference can explain both illusions strongly suggests that even puzzling percepts arise from optimal inference processes. |
format | Online Article Text |
id | pubmed-6186408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61864082018-10-15 The material-weight illusion is a Bayes-optimal percept under competing density priors Peters, Megan A.K. Zhang, Ling-Qi Shams, Ladan PeerJ Neuroscience The material-weight illusion (MWI) is one example in a class of weight perception illusions that seem to defy principled explanation. In this illusion, when an observer lifts two objects of the same size and mass, but that appear to be made of different materials, the denser-looking (e.g., metal-look) object is perceived as lighter than the less-dense-looking (e.g., polystyrene-look) object. Like the size-weight illusion (SWI), this perceptual illusion occurs in the opposite direction of predictions from an optimal Bayesian inference process, which predicts that the denser-looking object should be perceived as heavier, not lighter. The presence of this class of illusions challenges the often-tacit assumption that Bayesian inference holds universal explanatory power to describe human perception across (nearly) all domains: If an entire class of perceptual illusions cannot be captured by the Bayesian framework, how could it be argued that human perception truly follows optimal inference? However, we recently showed that the SWI can be explained by an optimal hierarchical Bayesian causal inference process (Peters, Ma & Shams, 2016) in which the observer uses haptic information to arbitrate among competing hypotheses about objects’ possible density relationship. Here we extend the model to demonstrate that it can readily explain the MWI as well. That hierarchical Bayesian inference can explain both illusions strongly suggests that even puzzling percepts arise from optimal inference processes. PeerJ Inc. 2018-10-11 /pmc/articles/PMC6186408/ /pubmed/30324029 http://dx.doi.org/10.7717/peerj.5760 Text en ©2018 Peters et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Neuroscience Peters, Megan A.K. Zhang, Ling-Qi Shams, Ladan The material-weight illusion is a Bayes-optimal percept under competing density priors |
title | The material-weight illusion is a Bayes-optimal percept under competing density priors |
title_full | The material-weight illusion is a Bayes-optimal percept under competing density priors |
title_fullStr | The material-weight illusion is a Bayes-optimal percept under competing density priors |
title_full_unstemmed | The material-weight illusion is a Bayes-optimal percept under competing density priors |
title_short | The material-weight illusion is a Bayes-optimal percept under competing density priors |
title_sort | material-weight illusion is a bayes-optimal percept under competing density priors |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186408/ https://www.ncbi.nlm.nih.gov/pubmed/30324029 http://dx.doi.org/10.7717/peerj.5760 |
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