Computational and neural mechanisms of statistical pain learning

Abstract

Pain fluctuates over time in ways that are non-random. Here, the authors show that the human brain can learn to predict these changes in a manner consistent with optimal Bayesian inference by engaging sensorimotor, parietal, and premotor regions.