A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding |
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Authors: | Ronald van den Berg Jos B T M Roerdink Frans W Cornelissen |
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Institution: | 1.Institute of Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands;2.Laboratory for Experimental Ophthalmology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands;3.School for Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, The Netherlands;Northwestern University, United States of America |
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Abstract: | 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. |
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