Reward and Decision Making in Corticobasal Ganglia Networks

Edited by Edited by Bernard W. Balleine (University of California, Los Angeles, California), Kenji Doya (Okinawa Institute of Science and Technology, Japan), and John O'Doherty (California Institute of Technology, Pasadena, California)
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Reward and Decision Making in Corticobasal Ganglia Networks

Published: July 2007

Volume 1104

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The neural bases of decision-making processes are currently generating considerable experimental and theoretical interest. Several recent developments in neuroscience, psychology, and economics have helped to focus thinking on this issue: the computational description of cortico-striatal networks in terms of reinforcement learning models, recognition that midbrain dopaminergic activity could reflect an error correction learning signal, improvements in imaging technology, the recognition that multiple controllers of actions and of values contribute to the development of adaptive behavior, and the recognition that theories of value derived from economics can provide a principled means of incorporating intangible factors such as risk, uncertainty, and temporal discounting into computational models of neural system.