Using the past to estimate sensory uncertainty
To form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophy...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2020-12-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/54172 |
| _version_ | 1811202614225797120 |
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| author | Ulrik Beierholm Tim Rohe Ambra Ferrari Oliver Stegle Uta Noppeney |
| author_facet | Ulrik Beierholm Tim Rohe Ambra Ferrari Oliver Stegle Uta Noppeney |
| author_sort | Ulrik Beierholm |
| collection | DOAJ |
| description | To form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophysical experiments, in which human observers localized auditory signals that were presented synchronously with spatially disparate visual signals. Critically, the visual noise changed dynamically over time continuously or with intermittent jumps. Our results show that observers integrate audiovisual inputs weighted by sensory uncertainty estimates that combine information from past and current signals consistent with an optimal Bayesian learner that can be approximated by exponential discounting. Our results challenge leading models of perceptual inference where sensory uncertainty estimates depend only on the current stimulus. They demonstrate that the brain capitalizes on the temporal dynamics of the external world and estimates sensory uncertainty by combining past experiences with new incoming sensory signals. |
| first_indexed | 2024-04-12T02:41:45Z |
| format | Article |
| id | doaj.art-2737348bac964456ab3e84d3581ff6ce |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T02:41:45Z |
| publishDate | 2020-12-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-2737348bac964456ab3e84d3581ff6ce2022-12-22T03:51:18ZengeLife Sciences Publications LtdeLife2050-084X2020-12-01910.7554/eLife.54172Using the past to estimate sensory uncertaintyUlrik Beierholm0https://orcid.org/0000-0002-7296-7996Tim Rohe1https://orcid.org/0000-0001-9713-3712Ambra Ferrari2https://orcid.org/0000-0003-1946-3884Oliver Stegle3Uta Noppeney4Psychology Department, Durham University, Durham, United KingdomDepartment of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany; Department of Psychology, Friedrich-Alexander University Erlangen-Nuernberg, Erlangen, GermanyCentre for Computational Neuroscience and Cognitive Robotics, University of Birmingham, Birmingham, United KingdomMax Planck Institute for Intelligent Systems, Tübingen, Germany; European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany; Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany, Heidelberg, GermanyCentre for Computational Neuroscience and Cognitive Robotics, University of Birmingham, Birmingham, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, NetherlandsTo form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophysical experiments, in which human observers localized auditory signals that were presented synchronously with spatially disparate visual signals. Critically, the visual noise changed dynamically over time continuously or with intermittent jumps. Our results show that observers integrate audiovisual inputs weighted by sensory uncertainty estimates that combine information from past and current signals consistent with an optimal Bayesian learner that can be approximated by exponential discounting. Our results challenge leading models of perceptual inference where sensory uncertainty estimates depend only on the current stimulus. They demonstrate that the brain capitalizes on the temporal dynamics of the external world and estimates sensory uncertainty by combining past experiences with new incoming sensory signals.https://elifesciences.org/articles/54172perceptionBayesian inference and learningsensory uncertaintycue combinationmultisensory integration |
| spellingShingle | Ulrik Beierholm Tim Rohe Ambra Ferrari Oliver Stegle Uta Noppeney Using the past to estimate sensory uncertainty eLife perception Bayesian inference and learning sensory uncertainty cue combination multisensory integration |
| title | Using the past to estimate sensory uncertainty |
| title_full | Using the past to estimate sensory uncertainty |
| title_fullStr | Using the past to estimate sensory uncertainty |
| title_full_unstemmed | Using the past to estimate sensory uncertainty |
| title_short | Using the past to estimate sensory uncertainty |
| title_sort | using the past to estimate sensory uncertainty |
| topic | perception Bayesian inference and learning sensory uncertainty cue combination multisensory integration |
| url | https://elifesciences.org/articles/54172 |
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