cortical sensitivity to visual features in natural scenes皮质对视觉敏感特性的自然场景.pdfVIP

cortical sensitivity to visual features in natural scenes皮质对视觉敏感特性的自然场景.pdf

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cortical sensitivity to visual features in natural scenes皮质对视觉敏感特性的自然场景

Open access, freely available online PLoS BIOLOGY Cortical Sensitivity to Visual Features in Natural Scenes Gidon Felsen1,2¤a, Jon Touryan2,3¤b, Feng Han2,3, Yang Dan1,2,3* 1 Division of Neurobiology, Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America, 2 Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America, 3 Group in Vision Science, University of California, Berkeley, California, United States of America A central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identified the visual features selectively represented by each cortical neuron from its responses to natural images. We then measured the neuronal sensitivity to these features when they were present in either natural images or random stimuli. We found that in the responses of complex cells, but not of simple cells, the sensitivity was markedly higher for natural images than for random stimuli. Such elevated sensitivity leads to increased detectability of the visual features and thus an improved cortical representation of natural scenes. Interestingly, this effect is due not to the spatial power spectra of natural images, but to their phase regularities. These results point to a distinct visual-coding strategy that is mediated by contextual modulation of cortical responses tuned to the spatial-phase structure of natural scenes. Citation: Felsen G, Touryan J, Han F, Dan Y (2005) Cortical sensitivity to visual features in natural scenes. PLoS Biol 3(10): e342. Introduction signal the p

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