HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hurri, J. Articles by Hyvärinen, A. Search for Related Content PubMed PubMed Citation Articles by Hurri, J. Articles by Hyvärinen, A.

Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video

jarmo.hurri{at}hut.fi, Neural Networks Research Centre, Helsinki University of Technology, 02015 HUT, Finland

Aapo Hyvärinen

aapo.hyvarinen{at}hut.fi, Neural Networks Research Centre, Helsinki University of Technology, 02015 HUT, Finland

Recently, statistical models of natural images have shown the emergence of several properties of the visual cortex. Most models have considered the nongaussian properties of static image patches, leading to sparse coding or independent component analysis. Here we consider the basic time dependencies of image sequences instead of their nongaussianity. We show that simple-cell-type receptive fields emerge when temporal response strength correlation is maximized for natural image sequences. Thus, temporal response strength correlation, which is a nonlinear measure of temporal coherence, provides an alternative to sparseness in modeling simple-cell receptive field properties. Our results also suggest an interpretation of simple cells in terms of invariant coding principles, which have previously been used to explain complex-cell receptive fields.

This article has been cited by other articles:

				F. Creutzig and H. Sprekeler Predictive Coding and the Slowness Principle: An Information-Theoretic Approach Neural Comput., April 1, 2007; 20(4): 1026 - 1041. [Abstract] [Full Text] [PDF]

				Y. Karklin and M. S. Lewicki A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals Neural Comput., February 1, 2005; 17(2): 397 - 423. [Abstract] [Full Text] [PDF]

				M. L. Mata and D. L. Ringach Spatial Overlap of ON and OFF Subregions and Its Relation to Response Modulation Ratio in Macaque Primary Visual Cortex J Neurophysiol, February 1, 2005; 93(2): 919 - 928. [Abstract] [Full Text] [PDF]

				D. L. Ringach Mapping receptive fields in primary visual cortex J. Physiol., August 1, 2004; 558(3): 717 - 728. [Abstract] [Full Text] [PDF]

				K. P. Kording, C. Kayser, W. Einhauser, and P. Konig How Are Complex Cell Properties Adapted to the Statistics of Natural Stimuli? J Neurophysiol, January 1, 2004; 91(1): 206 - 212. [Abstract] [Full Text]