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Evidence for the intrinsically nonlinear nature of receptive fields in vision

The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it...

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Autores principales: Bertalmío, Marcelo, Gomez-Villa, Alex, Martín, Adrián, Vazquez-Corral, Javier, Kane, David, Malo, Jesús
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530701/
https://www.ncbi.nlm.nih.gov/pubmed/33004868
http://dx.doi.org/10.1038/s41598-020-73113-0
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author Bertalmío, Marcelo
Gomez-Villa, Alex
Martín, Adrián
Vazquez-Corral, Javier
Kane, David
Malo, Jesús
author_facet Bertalmío, Marcelo
Gomez-Villa, Alex
Martín, Adrián
Vazquez-Corral, Javier
Kane, David
Malo, Jesús
author_sort Bertalmío, Marcelo
collection PubMed
description The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence.
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spelling pubmed-75307012020-10-02 Evidence for the intrinsically nonlinear nature of receptive fields in vision Bertalmío, Marcelo Gomez-Villa, Alex Martín, Adrián Vazquez-Corral, Javier Kane, David Malo, Jesús Sci Rep Article The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence. Nature Publishing Group UK 2020-10-01 /pmc/articles/PMC7530701/ /pubmed/33004868 http://dx.doi.org/10.1038/s41598-020-73113-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Bertalmío, Marcelo
Gomez-Villa, Alex
Martín, Adrián
Vazquez-Corral, Javier
Kane, David
Malo, Jesús
Evidence for the intrinsically nonlinear nature of receptive fields in vision
title Evidence for the intrinsically nonlinear nature of receptive fields in vision
title_full Evidence for the intrinsically nonlinear nature of receptive fields in vision
title_fullStr Evidence for the intrinsically nonlinear nature of receptive fields in vision
title_full_unstemmed Evidence for the intrinsically nonlinear nature of receptive fields in vision
title_short Evidence for the intrinsically nonlinear nature of receptive fields in vision
title_sort evidence for the intrinsically nonlinear nature of receptive fields in vision
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530701/
https://www.ncbi.nlm.nih.gov/pubmed/33004868
http://dx.doi.org/10.1038/s41598-020-73113-0
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