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Pooling strategies in V1 can account for the functional and structural diversity across species
Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high selectivity in simple cells to low selectivity in complex cells. Various computational models have suggested a possible link between the presence of phase invariant c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345491/ https://www.ncbi.nlm.nih.gov/pubmed/35862423 http://dx.doi.org/10.1371/journal.pcbi.1010270 |
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author | Boutin, Victor Franciosini, Angelo Chavane, Frédéric Perrinet, Laurent U. |
author_facet | Boutin, Victor Franciosini, Angelo Chavane, Frédéric Perrinet, Laurent U. |
author_sort | Boutin, Victor |
collection | PubMed |
description | Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high selectivity in simple cells to low selectivity in complex cells. Various computational models have suggested a possible link between the presence of phase invariant cells and the existence of orientation maps in higher mammals’ V1. These models, however, do not explain the emergence of complex cells in animals that do not show orientation maps. In this study, we build a theoretical model based on a convolutional network called Sparse Deep Predictive Coding (SDPC) and show that a single computational mechanism, pooling, allows the SDPC model to account for the emergence in V1 of complex cells with or without that of orientation maps, as observed in distinct species of mammals. In particular, we observed that pooling in the feature space is directly related to the orientation map formation while pooling in the retinotopic space is responsible for the emergence of a complex cells population. Introducing different forms of pooling in a predictive model of early visual processing as implemented in SDPC can therefore be viewed as a theoretical framework that explains the diversity of structural and functional phenomena observed in V1. |
format | Online Article Text |
id | pubmed-9345491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93454912022-08-03 Pooling strategies in V1 can account for the functional and structural diversity across species Boutin, Victor Franciosini, Angelo Chavane, Frédéric Perrinet, Laurent U. PLoS Comput Biol Research Article Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high selectivity in simple cells to low selectivity in complex cells. Various computational models have suggested a possible link between the presence of phase invariant cells and the existence of orientation maps in higher mammals’ V1. These models, however, do not explain the emergence of complex cells in animals that do not show orientation maps. In this study, we build a theoretical model based on a convolutional network called Sparse Deep Predictive Coding (SDPC) and show that a single computational mechanism, pooling, allows the SDPC model to account for the emergence in V1 of complex cells with or without that of orientation maps, as observed in distinct species of mammals. In particular, we observed that pooling in the feature space is directly related to the orientation map formation while pooling in the retinotopic space is responsible for the emergence of a complex cells population. Introducing different forms of pooling in a predictive model of early visual processing as implemented in SDPC can therefore be viewed as a theoretical framework that explains the diversity of structural and functional phenomena observed in V1. Public Library of Science 2022-07-21 /pmc/articles/PMC9345491/ /pubmed/35862423 http://dx.doi.org/10.1371/journal.pcbi.1010270 Text en © 2022 Boutin et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Boutin, Victor Franciosini, Angelo Chavane, Frédéric Perrinet, Laurent U. Pooling strategies in V1 can account for the functional and structural diversity across species |
title | Pooling strategies in V1 can account for the functional and structural diversity across species |
title_full | Pooling strategies in V1 can account for the functional and structural diversity across species |
title_fullStr | Pooling strategies in V1 can account for the functional and structural diversity across species |
title_full_unstemmed | Pooling strategies in V1 can account for the functional and structural diversity across species |
title_short | Pooling strategies in V1 can account for the functional and structural diversity across species |
title_sort | pooling strategies in v1 can account for the functional and structural diversity across species |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345491/ https://www.ncbi.nlm.nih.gov/pubmed/35862423 http://dx.doi.org/10.1371/journal.pcbi.1010270 |
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