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Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding
Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach. For example, perception of an element stro...
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/PMC6549494/ https://www.ncbi.nlm.nih.gov/pubmed/31191291 http://dx.doi.org/10.3389/fnbot.2019.00033 |
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author | Bornet, Alban Kaiser, Jacques Kroner, Alexander Falotico, Egidio Ambrosano, Alessandro Cantero, Kepa Herzog, Michael H. Francis, Gregory |
author_facet | Bornet, Alban Kaiser, Jacques Kroner, Alexander Falotico, Egidio Ambrosano, Alessandro Cantero, Kepa Herzog, Michael H. Francis, Gregory |
author_sort | Bornet, Alban |
collection | PubMed |
description | Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach. For example, perception of an element strongly deteriorates when neighboring elements are presented in addition (visual crowding). As it was shown recently, the magnitude of deterioration depends not only on the directly neighboring elements but on almost all elements and their specific configuration. Hence, to fully explain human visual perception, one needs to take large parts of the visual field into account and combine all the aspects of vision that become relevant at such scale. These efforts require sophisticated and collaborative modeling. The Neurorobotics Platform (NRP) of the Human Brain Project offers a unique opportunity to connect models of all sorts of visual functions, even those developed by different research groups, into a coherently functioning system. Here, we describe how we used the NRP to connect and simulate a segmentation model, a retina model, and a saliency model to explain complex results about visual perception. The combination of models highlights the versatility of the NRP and provides novel explanations for inward-outward anisotropy in visual crowding. |
format | Online Article Text |
id | pubmed-6549494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65494942019-06-12 Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding Bornet, Alban Kaiser, Jacques Kroner, Alexander Falotico, Egidio Ambrosano, Alessandro Cantero, Kepa Herzog, Michael H. Francis, Gregory Front Neurorobot Neurorobotics Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach. For example, perception of an element strongly deteriorates when neighboring elements are presented in addition (visual crowding). As it was shown recently, the magnitude of deterioration depends not only on the directly neighboring elements but on almost all elements and their specific configuration. Hence, to fully explain human visual perception, one needs to take large parts of the visual field into account and combine all the aspects of vision that become relevant at such scale. These efforts require sophisticated and collaborative modeling. The Neurorobotics Platform (NRP) of the Human Brain Project offers a unique opportunity to connect models of all sorts of visual functions, even those developed by different research groups, into a coherently functioning system. Here, we describe how we used the NRP to connect and simulate a segmentation model, a retina model, and a saliency model to explain complex results about visual perception. The combination of models highlights the versatility of the NRP and provides novel explanations for inward-outward anisotropy in visual crowding. Frontiers Media S.A. 2019-05-29 /pmc/articles/PMC6549494/ /pubmed/31191291 http://dx.doi.org/10.3389/fnbot.2019.00033 Text en Copyright © 2019 Bornet, Kaiser, Kroner, Falotico, Ambrosano, Cantero, Herzog and Francis. 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 | Neurorobotics Bornet, Alban Kaiser, Jacques Kroner, Alexander Falotico, Egidio Ambrosano, Alessandro Cantero, Kepa Herzog, Michael H. Francis, Gregory Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title | Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title_full | Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title_fullStr | Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title_full_unstemmed | Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title_short | Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision – The Case of Visual Crowding |
title_sort | running large-scale simulations on the neurorobotics platform to understand vision – the case of visual crowding |
topic | Neurorobotics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6549494/ https://www.ncbi.nlm.nih.gov/pubmed/31191291 http://dx.doi.org/10.3389/fnbot.2019.00033 |
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