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Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex
A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation o...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684760/ https://www.ncbi.nlm.nih.gov/pubmed/31417386 http://dx.doi.org/10.3389/fncom.2019.00051 |
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author | Turova, Tatyana Rolls, Edmund T. |
author_facet | Turova, Tatyana Rolls, Edmund T. |
author_sort | Turova, Tatyana |
collection | PubMed |
description | A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition operates. The analytic results are supported by simulations that illustrate the operation of the system with parameters selected from the analysis. The findings provide a detailed mathematical analysis of the operation of these neural systems with nodes connected by feedforward (bottom-up) and feedback (top-down) connections. The analysis provides the critical value of the top-down attentional bias that enables biased competition to operate for a range of input values to the network, and derives this as a function of all the parameters in the model. The critical value of the top-down bias depends linearly on the value of the other inputs, but the coefficients in the function reveal non-linear relations between the remaining parameters. The results provide reasons why the backprojections should not be very much weaker than the forward connections between two cortical areas. The major advantage of the analytical approach is that it discloses relations between all the parameters of the model. |
format | Online Article Text |
id | pubmed-6684760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-66847602019-08-15 Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex Turova, Tatyana Rolls, Edmund T. Front Comput Neurosci Neuroscience A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition operates. The analytic results are supported by simulations that illustrate the operation of the system with parameters selected from the analysis. The findings provide a detailed mathematical analysis of the operation of these neural systems with nodes connected by feedforward (bottom-up) and feedback (top-down) connections. The analysis provides the critical value of the top-down attentional bias that enables biased competition to operate for a range of input values to the network, and derives this as a function of all the parameters in the model. The critical value of the top-down bias depends linearly on the value of the other inputs, but the coefficients in the function reveal non-linear relations between the remaining parameters. The results provide reasons why the backprojections should not be very much weaker than the forward connections between two cortical areas. The major advantage of the analytical approach is that it discloses relations between all the parameters of the model. Frontiers Media S.A. 2019-07-31 /pmc/articles/PMC6684760/ /pubmed/31417386 http://dx.doi.org/10.3389/fncom.2019.00051 Text en Copyright © 2019 Turova and Rolls. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Turova, Tatyana Rolls, Edmund T. Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title | Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title_full | Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title_fullStr | Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title_full_unstemmed | Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title_short | Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex |
title_sort | analysis of biased competition and cooperation for attention in the cerebral cortex |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684760/ https://www.ncbi.nlm.nih.gov/pubmed/31417386 http://dx.doi.org/10.3389/fncom.2019.00051 |
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