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Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection
Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4468869/ https://www.ncbi.nlm.nih.gov/pubmed/26136664 http://dx.doi.org/10.3389/fncir.2015.00030 |
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author | Yang, Kai-Fu Li, Chao-Yi Li, Yong-Jie |
author_facet | Yang, Kai-Fu Li, Chao-Yi Li, Yong-Jie |
author_sort | Yang, Kai-Fu |
collection | PubMed |
description | Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical role in visual perception, the specific role of orientation-selective and non-selective inhibition in the task of contour detection is less known. To clarify above question, we first carried out computational analysis of the contour detection performance of V1 neurons with different types of surround inhibition, on the basis of which we then proposed two integrated models to evaluate their role in this specific perceptual task by combining the two types of surround inhibition with two different ways. The two models were evaluated with synthetic images and a set of challenging natural images, and the results show that both of the integrated models outperform the typical models with orientation-selective or non-selective inhibition alone. The findings of this study suggest that V1 neurons with different types of center–surround interaction work in cooperative and adaptive ways at least when extracting organized structures from cluttered natural scenes. This work is expected to inspire efficient phenomenological models for engineering applications in field of computational machine-vision. |
format | Online Article Text |
id | pubmed-4468869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-44688692015-07-01 Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection Yang, Kai-Fu Li, Chao-Yi Li, Yong-Jie Front Neural Circuits Neuroscience Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical role in visual perception, the specific role of orientation-selective and non-selective inhibition in the task of contour detection is less known. To clarify above question, we first carried out computational analysis of the contour detection performance of V1 neurons with different types of surround inhibition, on the basis of which we then proposed two integrated models to evaluate their role in this specific perceptual task by combining the two types of surround inhibition with two different ways. The two models were evaluated with synthetic images and a set of challenging natural images, and the results show that both of the integrated models outperform the typical models with orientation-selective or non-selective inhibition alone. The findings of this study suggest that V1 neurons with different types of center–surround interaction work in cooperative and adaptive ways at least when extracting organized structures from cluttered natural scenes. This work is expected to inspire efficient phenomenological models for engineering applications in field of computational machine-vision. Frontiers Media S.A. 2015-06-16 /pmc/articles/PMC4468869/ /pubmed/26136664 http://dx.doi.org/10.3389/fncir.2015.00030 Text en Copyright © 2015 Yang, Li and Li. 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) or licensor 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 Yang, Kai-Fu Li, Chao-Yi Li, Yong-Jie Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title | Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title_full | Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title_fullStr | Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title_full_unstemmed | Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title_short | Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
title_sort | potential roles of the interaction between model v1 neurons with orientation-selective and non-selective surround inhibition in contour detection |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4468869/ https://www.ncbi.nlm.nih.gov/pubmed/26136664 http://dx.doi.org/10.3389/fncir.2015.00030 |
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