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Reconciling Predictive Coding and Biased Competition Models of Cortical Function
A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the...
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Formato: | Texto |
Lenguaje: | English |
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Frontiers Research Foundation
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2576514/ https://www.ncbi.nlm.nih.gov/pubmed/18978957 http://dx.doi.org/10.3389/neuro.10.004.2008 |
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author | Spratling, Michael W. |
author_facet | Spratling, Michael W. |
author_sort | Spratling, Michael W. |
collection | PubMed |
description | A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model. |
format | Text |
id | pubmed-2576514 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-25765142008-10-31 Reconciling Predictive Coding and Biased Competition Models of Cortical Function Spratling, Michael W. Front Comput Neurosci Neuroscience A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model. Frontiers Research Foundation 2008-10-21 /pmc/articles/PMC2576514/ /pubmed/18978957 http://dx.doi.org/10.3389/neuro.10.004.2008 Text en Copyright © 2008 Spratling. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited. |
spellingShingle | Neuroscience Spratling, Michael W. Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title | Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title_full | Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title_fullStr | Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title_full_unstemmed | Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title_short | Reconciling Predictive Coding and Biased Competition Models of Cortical Function |
title_sort | reconciling predictive coding and biased competition models of cortical function |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2576514/ https://www.ncbi.nlm.nih.gov/pubmed/18978957 http://dx.doi.org/10.3389/neuro.10.004.2008 |
work_keys_str_mv | AT spratlingmichaelw reconcilingpredictivecodingandbiasedcompetitionmodelsofcorticalfunction |