A structured model of video reproduces primary visual cortical organisation.

ABSTRACT: The visual system must learn to infer the presence of objects and features in the world from the images it encounters, and as such it must, either implicitly or explicitly, model the way these elements interact to create the image. Do the response properties of cells in the mammalian visual system reflect this constraint? To address this question, we constructed a probabilistic model in which the identity and attributes of simple visual elements were represented explicitly and learnt the parameters of this model from unparsed, natural video sequences. After learning, the behaviour and grouping of variables in the probabilistic model corresponded closely to functional and anatomical properties of simple and complex cells in the primary visual cortex (V1). In particular, feature identity var

SUBMITTER: Berkes P 

PROVIDER: S-EPMC2726939 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature