Components and characteristics of the dopamine reward utility signal.
Rewards are defined by their behavioral functions in learning (positive reinforcement), approach behavior, economic choices, and emotions. Dopamine neurons respond to rewards with two components, similar to higher order sensory and cognitive neurons. The initial, rapid, unselective dopamine detection component reports all salient environmental events irrespective of their reward association. It is highly sensitive to factors related to reward and thus detects a maximal number of potential rewards. It also senses aversive stimuli but reports their physical impact rather than their aversiveness. The second response component processes reward value accurately and starts early enough to prevent confusion with unrewarded stimuli and objects. It codes reward value as a numeric, quantitative utility prediction error, consistent with formal concepts of economic decision theory. Thus, the dopamine reward signal is fast, highly sensitive and appropriate for driving and updating economic decisions.
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom.
William R
WR
Stauffer
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom.
Armin
A
Lak
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom.
Shunsuke
S
Kobayashi
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom.
Wolfram
W
Schultz
D000818:Animals; D001921:Brain / Q000502:physiology*; D002755:Choice Behavior / Q000502:physiology; D004298:Dopamine / Q000378:metabolism; D059290:Dopaminergic Neurons / Q000502:physiology*; D006801:Humans; D007858:Learning / Q000502:physiology; D012201:Reward
D004298:Dopamine
neuroeconomics; risk; stimulus components; subjective value; temporal discounting; utility