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Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models
Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154506/ https://www.ncbi.nlm.nih.gov/pubmed/27959919 http://dx.doi.org/10.1371/journal.pone.0165391 |
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author | Mendonça, Catarina Mandelli, Pietro Pulkki, Ville |
author_facet | Mendonça, Catarina Mandelli, Pietro Pulkki, Ville |
author_sort | Mendonça, Catarina |
collection | PubMed |
description | Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study, the audiovisual perception of distance was overall better explained by Bayesian causal inference than by other traditional models, such as sensory dominance and mandatory integration, and no interaction. Causal inference resolved with probability matching yielded the best fit to the data. Finally, we propose that sensory weights can also be estimated from causal inference. The analysis of the sensory weights allows us to obtain windows within which there is an interaction between the audiovisual stimuli. We find that the visual stimulus always contributes by more than 80% to the perception of visual distance. The visual stimulus also contributes by more than 50% to the perception of auditory distance, but only within a mobile window of interaction, which ranges from 1 to 4 m. |
format | Online Article Text |
id | pubmed-5154506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-51545062016-12-28 Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models Mendonça, Catarina Mandelli, Pietro Pulkki, Ville PLoS One Research Article Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study, the audiovisual perception of distance was overall better explained by Bayesian causal inference than by other traditional models, such as sensory dominance and mandatory integration, and no interaction. Causal inference resolved with probability matching yielded the best fit to the data. Finally, we propose that sensory weights can also be estimated from causal inference. The analysis of the sensory weights allows us to obtain windows within which there is an interaction between the audiovisual stimuli. We find that the visual stimulus always contributes by more than 80% to the perception of visual distance. The visual stimulus also contributes by more than 50% to the perception of auditory distance, but only within a mobile window of interaction, which ranges from 1 to 4 m. Public Library of Science 2016-12-13 /pmc/articles/PMC5154506/ /pubmed/27959919 http://dx.doi.org/10.1371/journal.pone.0165391 Text en © 2016 Mendonça 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, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mendonça, Catarina Mandelli, Pietro Pulkki, Ville Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title | Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title_full | Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title_fullStr | Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title_full_unstemmed | Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title_short | Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models |
title_sort | modeling the perception of audiovisual distance: bayesian causal inference and other models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154506/ https://www.ncbi.nlm.nih.gov/pubmed/27959919 http://dx.doi.org/10.1371/journal.pone.0165391 |
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