Independent Components of Color Natural Scenes Resemble V1 Neurons in Their Spatial and Color Tuning

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Abstract
It has been hypothesized that mammalian sensory systems are efficient because they reduce the redundancy of natural sensory input. If correct, this theory could unify our understanding of sensory coding; here, we test its predictions for color coding in the primate primary visual cortex (V1). We apply independent component analysis (ICA) to simulated cone responses to natural scenes, obtaining a set of colored independent component (IC) filters that form a redundancy-reducing visual code. We compare IC filters with physiologically measured V1 neurons, and find great spatial similarity between IC filters and V1 simple cells. On cursory inspection, there is little chromatic similarity; however, we find that many apparent differences result from biases in the physiological measurements and ICA analysis. After correcting these biases, we find that the chromatic tuning of IC filters does indeed resemble the population of V1 neurons, supporting the redundancy-reduction hypothesis.