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Adaptation to statistical properties of visual scenes biases rapid categorization

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The initial categorization of complex visual scenes is a very rapid process. Here we find no differences in performance for upright and inverted images arguing for a neural mechanism that can function without involving high-level image orientation dependent identification processes. Using an adaptation paradigm we are able to demonstrate that artificial images composed to mimic the orientation distribution of either natural or man-made scenes systematically shift the judgement of human observers. This suggests a highly efficient feedforward system that makes use of "low-level" image features yet supports the rapid extraction of essential information for the categorization of complex visual scenes.
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Document Type: Research Article

Affiliations: Cognitive Neuroscience Laboratory, German Primate Centre, Goettingen, Germany

Publication date: 2007-01-01

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