Bayesian brain
BAY-zee-un BRAYN
ˈbeɪziən breɪnListen
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the hypothesis that the brain approximates Bayesian inference in its processing of sensory information, combining prior knowledge and expectations with incoming sensory evidence in a statistically optimal way to generate perceptual beliefs; named after Thomas Bayes, whose theorem describes how probabilities should be updated in the light of new evidence, the Bayesian brain hypothesis has generated a large body of experimental psychophysics research testing whether human perception and sensorimotor integration match the predictions of Bayesian models; the hypothesis intersects with predictive processing frameworks and has been applied to understanding perceptual disorders, multisensory integration, and the probabilistic structure of neural coding
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