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A neurophysiologically plausible population code model for feature integration explains visual crowding
Univ Groningen, Inst Math & Comp Sci, Groningen, Netherlands; Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Sch Behav & Cognit Neurosci, Groningen, Netherlands.
Univ Groningen, Inst Math & Comp Sci, Groningen, Netherlands; .
Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Sch Behav & Cognit Neurosci, Groningen, Netherlands.
2010 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 6, no 1, article id e1000646Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2010. Vol. 6, no 1, article id e1000646
National Category
Psychology (excluding Applied Psychology)
Identifiers
URN: urn:nbn:se:uu:diva-308859DOI: 10.1371/journal.pcbi.1000646ISI: 000274231500018PubMedID: 20098499OAI: oai:DiVA.org:uu-308859DiVA, id: diva2:1051010
Funder
EU, European Research Council, 043157 043261 033816Available from: 2016-11-30 Created: 2016-11-30 Last updated: 2017-11-29Bibliographically approved

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Van den Berg, Ronald

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