Recently, statistical models of natural images have shown emergence of several properties of the visual cortex. Most models have considered the non-Gaussian properties of static image patches, leading to sparse coding or independent component analysis. Here we consider the basic statistical time dependencies of image sequences. 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 that have previously been used to explain complex cell receptive fields. © Springer-Verlag Berlin Heidelberg 2002.
CITATION STYLE
Hurri, J., & Hyvärinen, A. (2002). Receptive fields similar to simple cells maximize temporal coherence in natural video. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2415 LNCS, pp. 33–38). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_6
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