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Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis
Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical levels are connected by backward connections carrying predictions, as well as forward connections carrying prediction errors. To date, however, predictive coding models have largely negl...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506824/ https://www.ncbi.nlm.nih.gov/pubmed/31064839 http://dx.doi.org/10.1523/ENEURO.0412-18.2019 |
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author | Hogendoorn, Hinze Burkitt, Anthony N. |
author_facet | Hogendoorn, Hinze Burkitt, Anthony N. |
author_sort | Hogendoorn, Hinze |
collection | PubMed |
description | Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical levels are connected by backward connections carrying predictions, as well as forward connections carrying prediction errors. To date, however, predictive coding models have largely neglected to take into account that neural transmission itself takes time. For a time-varying stimulus, such as a moving object, this means that backward predictions become misaligned with new sensory input. We present an extended model implementing both forward and backward extrapolation mechanisms that realigns backward predictions to minimize prediction error. This realignment has the consequence that neural representations across all hierarchical levels become aligned in real time. Using visual motion as an example, we show that the model is neurally plausible, that it is consistent with evidence of extrapolation mechanisms throughout the visual hierarchy, that it predicts several known motion–position illusions in human observers, and that it provides a solution to the temporal binding problem. |
format | Online Article Text |
id | pubmed-6506824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-65068242019-05-09 Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis Hogendoorn, Hinze Burkitt, Anthony N. eNeuro Theory/New Concepts Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical levels are connected by backward connections carrying predictions, as well as forward connections carrying prediction errors. To date, however, predictive coding models have largely neglected to take into account that neural transmission itself takes time. For a time-varying stimulus, such as a moving object, this means that backward predictions become misaligned with new sensory input. We present an extended model implementing both forward and backward extrapolation mechanisms that realigns backward predictions to minimize prediction error. This realignment has the consequence that neural representations across all hierarchical levels become aligned in real time. Using visual motion as an example, we show that the model is neurally plausible, that it is consistent with evidence of extrapolation mechanisms throughout the visual hierarchy, that it predicts several known motion–position illusions in human observers, and that it provides a solution to the temporal binding problem. Society for Neuroscience 2019-05-06 /pmc/articles/PMC6506824/ /pubmed/31064839 http://dx.doi.org/10.1523/ENEURO.0412-18.2019 Text en Copyright © 2019 Hogendoorn and Burkitt http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Theory/New Concepts Hogendoorn, Hinze Burkitt, Anthony N. Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title | Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title_full | Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title_fullStr | Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title_full_unstemmed | Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title_short | Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis |
title_sort | predictive coding with neural transmission delays: a real-time temporal alignment hypothesis |
topic | Theory/New Concepts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506824/ https://www.ncbi.nlm.nih.gov/pubmed/31064839 http://dx.doi.org/10.1523/ENEURO.0412-18.2019 |
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