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We present a law of human perception. The law expresses a mathematical relation between our ability to perceptually discriminate a stimulus from similar ones and our bias in the perceived stimulus value. We derived the relation based on theoretical assumptions about how the brain represents sen- sory information and how it interprets this information to cre- ate a percept. Our main assumption is that both encoding and decoding are optimized for the specific statistical structure of the sensory environment. We found large experimental sup- port for the law in the literature, which includes biases and changes in discriminability induced by contextual modulation (e.g., adaptation). Our results imply that human perception generally relies on statistically optimized processes.

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This page is a summary of: Lawful relation between perceptual bias and discriminability, Proceedings of the National Academy of Sciences, September 2017, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.1619153114.
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