Topographic independent component analysis as a model of V1, organization and receptive fields

Independent component analysis (ICA) has been recently used as a model of n atural image statistics and V1 simple cell receptive fields. Here we show h ow to extend the ICA model to explain V1 topography as well, This is done b y relaxing the independence assumption and ordering the basis vectors so th at vectors with strong higher-order correlations are near each other. This is a new principle of topographic organization, and may be more relevant to natural image statistics than the more conventional topographic ordering b ased on Euclidean distances. For example, our ordering leads to simultaneou s emergence of complex cell properties: topographic neighborhoods act like complex cells. (C) 2001 Elsevier Science B.V. All rights reserved.