title: Computing motivation: Incentive salience boosts of drug or appetite states.
abstract: Current computational models predict reward based solely on learning. Real motivation involves that but also more. Brain reward systems can dynamically generate incentive salience, by integrating prior learned values with even novel physiological states (e.g., natural appetites; drug-induced mesolimbic sensitization) to cause intense desires that were themselves never learned. We hope future computational models may capture this too.
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI 48109.
authors.forename: Kent C
authors.initials: KC
authors.lastname: Berridge
authors.forename: Jun
authors.initials: J
authors.lastname: Zhang
authors.forename: J Wayne
authors.initials: JW
authors.lastname: Aldridge