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Neural signatures of perceptual inference
Generative models, such as predictive coding, posit that perception results from a combination of sensory input and prior prediction, each weighted by its precision (inverse variance), with incongruence between these termed prediction error (deviation from prediction) or surprise (negative log proba...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4841773/ https://www.ncbi.nlm.nih.gov/pubmed/26949254 http://dx.doi.org/10.7554/eLife.11476 |
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author | Sedley, William Gander, Phillip E Kumar, Sukhbinder Kovach, Christopher K Oya, Hiroyuki Kawasaki, Hiroto Howard, Matthew A Griffiths, Timothy D |
author_facet | Sedley, William Gander, Phillip E Kumar, Sukhbinder Kovach, Christopher K Oya, Hiroyuki Kawasaki, Hiroto Howard, Matthew A Griffiths, Timothy D |
author_sort | Sedley, William |
collection | PubMed |
description | Generative models, such as predictive coding, posit that perception results from a combination of sensory input and prior prediction, each weighted by its precision (inverse variance), with incongruence between these termed prediction error (deviation from prediction) or surprise (negative log probability of the sensory input). However, direct evidence for such a system, and the physiological basis of its computations, is lacking. Using an auditory stimulus whose pitch value changed according to specific rules, we controlled and separated the three key computational variables underlying perception, and discovered, using direct recordings from human auditory cortex, that surprise due to prediction violations is encoded by local field potential oscillations in the gamma band (>30 Hz), changes to predictions in the beta band (12-30 Hz), and that the precision of predictions appears to quantitatively relate to alpha band oscillations (8-12 Hz). These results confirm oscillatory codes for critical aspects of generative models of perception. DOI: http://dx.doi.org/10.7554/eLife.11476.001 |
format | Online Article Text |
id | pubmed-4841773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-48417732016-04-25 Neural signatures of perceptual inference Sedley, William Gander, Phillip E Kumar, Sukhbinder Kovach, Christopher K Oya, Hiroyuki Kawasaki, Hiroto Howard, Matthew A Griffiths, Timothy D eLife Neuroscience Generative models, such as predictive coding, posit that perception results from a combination of sensory input and prior prediction, each weighted by its precision (inverse variance), with incongruence between these termed prediction error (deviation from prediction) or surprise (negative log probability of the sensory input). However, direct evidence for such a system, and the physiological basis of its computations, is lacking. Using an auditory stimulus whose pitch value changed according to specific rules, we controlled and separated the three key computational variables underlying perception, and discovered, using direct recordings from human auditory cortex, that surprise due to prediction violations is encoded by local field potential oscillations in the gamma band (>30 Hz), changes to predictions in the beta band (12-30 Hz), and that the precision of predictions appears to quantitatively relate to alpha band oscillations (8-12 Hz). These results confirm oscillatory codes for critical aspects of generative models of perception. DOI: http://dx.doi.org/10.7554/eLife.11476.001 eLife Sciences Publications, Ltd 2016-03-07 /pmc/articles/PMC4841773/ /pubmed/26949254 http://dx.doi.org/10.7554/eLife.11476 Text en © 2016, Sedley et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Sedley, William Gander, Phillip E Kumar, Sukhbinder Kovach, Christopher K Oya, Hiroyuki Kawasaki, Hiroto Howard, Matthew A Griffiths, Timothy D Neural signatures of perceptual inference |
title | Neural signatures of perceptual inference |
title_full | Neural signatures of perceptual inference |
title_fullStr | Neural signatures of perceptual inference |
title_full_unstemmed | Neural signatures of perceptual inference |
title_short | Neural signatures of perceptual inference |
title_sort | neural signatures of perceptual inference |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4841773/ https://www.ncbi.nlm.nih.gov/pubmed/26949254 http://dx.doi.org/10.7554/eLife.11476 |
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