Skip Navigation


Social Cognitive and Affective Neuroscience Advance Access originally published online on September 18, 2006
Social Cognitive and Affective Neuroscience 2007 2(1):20-30; doi:10.1093/scan/nsl021
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
2/1/20    most recent
nsl021v1
Right arrow E-letters: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when E-letters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by Cohen, M. X
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cohen, M. X
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2006). Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Individual differences and the neural representations of reward expectation and reward prediction error

Michael X Cohen

Department of Epilepsy, University of Bonn, Sigmund-Freud-Str. 25, Bonn 53105, Germany and Department of Psychology and Center for Neuroscience, University of California, Davis, CA 95616, USA

Reward expectation and reward prediction errors are thought to be critical for dynamic adjustments in decision-making and reward-seeking behavior, but little is known about their representation in the brain during uncertainty and risk-taking. Furthermore, little is known about what role individual differences might play in such reinforcement processes. In this study, it is shown behavioral and neural responses during a decision-making task can be characterized by a computational reinforcement learning model and that individual differences in learning parameters in the model are critical for elucidating these processes. In the fMRI experiment, subjects chose between high- and low-risk rewards. A computational reinforcement learning model computed expected values and prediction errors that each subject might experience on each trial. These outputs predicted subjects’ trial-to-trial choice strategies and neural activity in several limbic and prefrontal regions during the task. Individual differences in estimated reinforcement learning parameters proved critical for characterizing these processes, because models that incorporated individual learning parameters explained significantly more variance in the fMRI data than did a model using fixed learning parameters. These findings suggest that the brain engages a reinforcement learning process during risk-taking and that individual differences play a crucial role in modeling this process.

Keywords: reward prediction error; reward expectation; fMRI; decision-making; reinforcement learning; risk-taking



Correspondence should be addressed to: Michael X Cohen, Department of Epilepsy, University of Bonn, Sigmund-Freud-Str. 25, Bonn 53105, Germany. E-mail: mcohen{at}ucdavis.edu

Received May 11, 2006. Accepted August 8, 2006.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.