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Spatiochromatic Receptive Field Properties Derived from Information-Theoretic Analyses of Cone Mosaic Responses to Natural Scenes

edoi{at}ucsd.edu, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093, U.S.A., and Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

Toshio Inui

inui{at}cog.ist.i.kyoto-u.ac.jp, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

Te-Won Lee

tewon{at}salk.edu, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093, U.S.A., and Howard Hughes Medical Institute, Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, U.S.A.

Thomas Wachtler

wachtler{at}biologie.uni-freiburg.de, Neurobiology and Biophysics, Institute of Biology III, Albert-Ludwigs-Universität, 79104 Freiburg, Germany

Terrence J. Sejnowski

terry{at}salk.edu, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093, U.S.A., Howard Hughes Medical Institute, Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, U.S.A., and Department of Biology, University of California, San Diego, La Jolla, CA 92093, U.S.A.

Neurons in the early stages of processing in the primate visual system efficiently encode natural scenes. In previous studies of the chromatic properties of natural images, the inputs were sampled on a regular array, with complete color information at every location. However, in the retina cone photoreceptors with different spectral sensitivities are arranged in a mosaic. We used an unsupervised neural network model to analyze the statistical structure of retinal cone mosaic responses to calibrated color natural images. The second-order statistical dependencies derived from the covariance matrix of the sensory signals were removed in the first stage of processing. These decorrelating filters were similar to type I receptive fields in parvo- or konio-cellular LGN in both spatial and chromatic characteristics. In the subsequent stage, the decorrelated signals were linearly transformed to make the output as statistically independent as possible, using independent component analysis. The independent component filters showed luminance selectivity with simple-cell-like receptive fields, or had strong color selectivity with large, often double-opponent, receptive fields, both of which were found in the primary visual cortex (V1). These results show that the "form" and "color" channels of the early visual system can be derived from the statistics of sensory signals.

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