title: Neural differentiation of expected reward and risk in human subcortical structures.
abstract: In decision-making under uncertainty, economic studies emphasize the importance of risk in addition to expected reward. Studies in neuroscience focus on expected reward and learning rather than risk. We combined functional imaging with a simple gambling task to vary expected reward and risk simultaneously and in an uncorrelated manner. Drawing on financial decision theory, we modeled expected reward as mathematical expectation of reward, and risk as reward variance. Activations in dopaminoceptive structures correlated with both mathematical parameters. These activations differentiated spatially and temporally. Temporally, the activation related to expected reward was immediate, while the activation related to risk was delayed. Analyses confirmed that our paradigm minimized confounds from learning, motivation, and salience. These results suggest that the primary task of the dopaminergic system is to convey signals of upcoming stochastic rewards, such as expected reward and risk, beyond its role in learning, motivation, and salience.
authors.affiliation: Computation and Neural Systems Program, Social Cognitive Neuroscience Laboratory, California Institute of Technology, 1200 East California Boulevard, 228-77, Pasadena, California 91125, USA. kerstinp@caltech.edu
authors.forename: Kerstin
authors.initials: K
authors.lastname: Preuschoff
authors.forename: Peter
authors.initials: P
authors.lastname: Bossaerts
authors.forename: Steven R
authors.initials: SR
authors.lastname: Quartz
mesh_terms: D000293:Adolescent; D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D004193:Discrimination Learning / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D011597:Psychomotor Performance / Q000502:physiology*; D012201:Reward; D012309:Risk-Taking