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Computing motivation: Incentive salience boosts of drug or appetite states

Published online by Cambridge University Press:  29 July 2008

Kent C. Berridge ,
Jun Zhang  and
J. Wayne Aldridge
Kent C. Berridge
Affiliation:
Department of Psychology, University of Michigan, Ann Arbor, MI 48109
Jun Zhang
Affiliation:
Department of Psychology, University of Michigan, Ann Arbor, MI 48109
J. Wayne Aldridge
Affiliation:
Departments of Neurology and Psychology, University of Michigan, Ann Arbor, MI 48109. berridge@umich.eduhttp://www-personal.umich.edu/~berridge/junz@umich.eduhttp://www.lsa.umich.edu/psych/junz/jwaynea@umich.eduhttp://sitemaker.umich.edu/aldridgelab/home
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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.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 31 , Issue 4 , August 2008 , pp. 440 - 441
Copyright
Copyright © Cambridge University Press 2008

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