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The Neural Computation on Animal Collision Detection

PROMOTION: The time-to-collision (TTC) in collision course is a critical neural computation for an animal to response quickly and accurately on collision detection, such as to avoid a looming object. The physical formula of TTC was not feasible for neural computation realization. OUR WORK: We deduce...

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Detalles Bibliográficos
Autores principales: Wang, Ling, Yao, Zhong D. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393676/
http://dx.doi.org/10.1068/ic278
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author Wang, Ling
Yao, Zhong D. E.
author_facet Wang, Ling
Yao, Zhong D. E.
author_sort Wang, Ling
collection PubMed
description PROMOTION: The time-to-collision (TTC) in collision course is a critical neural computation for an animal to response quickly and accurately on collision detection, such as to avoid a looming object. The physical formula of TTC was not feasible for neural computation realization. OUR WORK: We deduce a new approximation of TTC, i.e. 1/τ=Mθ−P/(θ+Q)+N, where θ is the visual angle subtended to the incoming object while M,P,Q and N are constants determined by a practical collision course. Accordingly, we construct a neural computational model (NCM) to carry out the TTC. RESULTS: The simulated results showed that NCM with neurons of sigmoid response can accurately estimate TTC and well reconstruct the practical animal collision experiments. CONCLUSION: The NCM might be a potential and realizable neural computation mechanism on animal collision detection.
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spelling pubmed-53936762017-04-24 The Neural Computation on Animal Collision Detection Wang, Ling Yao, Zhong D. E. Iperception Article PROMOTION: The time-to-collision (TTC) in collision course is a critical neural computation for an animal to response quickly and accurately on collision detection, such as to avoid a looming object. The physical formula of TTC was not feasible for neural computation realization. OUR WORK: We deduce a new approximation of TTC, i.e. 1/τ=Mθ−P/(θ+Q)+N, where θ is the visual angle subtended to the incoming object while M,P,Q and N are constants determined by a practical collision course. Accordingly, we construct a neural computational model (NCM) to carry out the TTC. RESULTS: The simulated results showed that NCM with neurons of sigmoid response can accurately estimate TTC and well reconstruct the practical animal collision experiments. CONCLUSION: The NCM might be a potential and realizable neural computation mechanism on animal collision detection. SAGE Publications 2011-05-01 2011-05 /pmc/articles/PMC5393676/ http://dx.doi.org/10.1068/ic278 Text en © 2011 SAGE Publications Ltd. Manuscript content on this site is licensed under Creative Commons Licenses http://creativecommons.org/licenses/by-nc-nd/3.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License (http://www.creativecommons.org/licenses/by-nc-nd/3.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (http://www.uk.sagepub.com/aboutus/openaccess.htm).
spellingShingle Article
Wang, Ling
Yao, Zhong D. E.
The Neural Computation on Animal Collision Detection
title The Neural Computation on Animal Collision Detection
title_full The Neural Computation on Animal Collision Detection
title_fullStr The Neural Computation on Animal Collision Detection
title_full_unstemmed The Neural Computation on Animal Collision Detection
title_short The Neural Computation on Animal Collision Detection
title_sort neural computation on animal collision detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393676/
http://dx.doi.org/10.1068/ic278
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