A neurophysiologically plausible population code model for feature integration explains visual crowding.

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results fr...

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Autores principales:	Ronald van den Berg, Jos B T M Roerdink, Frans W Cornelissen
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/e4d1275a4b4e49ccb4cdb56ede06307c
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id	oai:doaj.org-article:e4d1275a4b4e49ccb4cdb56ede06307c
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spelling	oai:doaj.org-article:e4d1275a4b4e49ccb4cdb56ede06307c2021-11-25T05:42:42ZA neurophysiologically plausible population code model for feature integration explains visual crowding.1553-734X1553-735810.1371/journal.pcbi.1000646https://doaj.org/article/e4d1275a4b4e49ccb4cdb56ede06307c2010-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20098499/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.Ronald van den BergJos B T M RoerdinkFrans W CornelissenPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 6, Iss 1, p e1000646 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Ronald van den Berg Jos B T M Roerdink Frans W Cornelissen A neurophysiologically plausible population code model for feature integration explains visual crowding.
description	An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.
format	article
author	Ronald van den Berg Jos B T M Roerdink Frans W Cornelissen
author_facet	Ronald van den Berg Jos B T M Roerdink Frans W Cornelissen
author_sort	Ronald van den Berg
title	A neurophysiologically plausible population code model for feature integration explains visual crowding.
title_short	A neurophysiologically plausible population code model for feature integration explains visual crowding.
title_full	A neurophysiologically plausible population code model for feature integration explains visual crowding.
title_fullStr	A neurophysiologically plausible population code model for feature integration explains visual crowding.
title_full_unstemmed	A neurophysiologically plausible population code model for feature integration explains visual crowding.
title_sort	neurophysiologically plausible population code model for feature integration explains visual crowding.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/e4d1275a4b4e49ccb4cdb56ede06307c
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A neurophysiologically plausible population code model for feature integration explains visual crowding.

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