title: Neural coding of uncertainty and probability.
abstract: Organisms must act in the face of sensory, motor, and reward uncertainty stemming from a pandemonium of stochasticity and missing information. In many tasks, organisms can make better decisions if they have at their disposal a representation of the uncertainty associated with task-relevant variables. We formalize this problem using Bayesian decision theory and review recent behavioral and neural evidence that the brain may use knowledge of uncertainty, confidence, and probability.
authors.affiliation: Center for Neural Science and Department of Psychology, New York University, New York, New York 10003; email: weijima@nyu.edu.
authors.forename: Wei Ji
authors.initials: WJ
authors.lastname: Ma
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Jazayeri
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D011336:Probability; D035501:Uncertainty
keywords: Bayesian inference; decision making; perception; population encoding