van den Berg, R and Roerdink, JBTM and Cornelissen, FW (2010) A neurophysiologically plausible population code model for feature integration explains visual crowding. PLoS Comput Biol, 6. e1000646-.Full text not available from this repository.
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.
|Uncontrolled Keywords:||Anisotropy Computational Biology Computer Simulation Fovea Centralis Humans Models, Neurological Photic Stimulation Visual Fields|
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||09 Dec 2016 17:15|
|Last Modified:||24 Mar 2017 23:19|