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TY - GEN ID - cogprints2706 UR - http://cogprints.org/2706/ A1 - Berkes, Pietro A1 - Wiskott, Laurenz Y1 - 2002/// N2 - We apply Slow Feature Analysis (SFA) to image sequences generated from natural images using a range of spatial transformations. An analysis of the resulting receptive fields shows that they have a rich spectrum of invariances and share many properties with complex and hypercomplex cells of the primary visual cortex. Furthermore, the dependence of the solutions on the statistics of the transformations is investigated. PB - Springer Verlag KW - Complex cells KW - slow feature analysis KW - temporal slowness KW - model KW - spatio-temporal KW - receptive fields TI - Applying Slow Feature Analysis to Image Sequences Yields a Rich Repertoire of Complex Cell Properties SP - 81 AV - public EP - 86 ER -