Decoding the neural substrates of reward-related decision making with functional MRI
- Creators
- Hampton, Alan N.
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O'Doherty, John P.
Abstract
Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we measured brain activity using functional MRI in a group of subjects while they performed a simple reward-based decision-making task: probabilistic reversal-learning. We recorded brain activity from nine distinct regions of interest previously implicated in decision making and separated out local spatially distributed signals in each region from global differences in signal. Using a multivariate analysis approach, we determined the extent to which global and local signals could be used to decode subjects' subsequent behavioral choice, based on their brain activity on the preceding trial. We found that subjects' decisions could be decoded to a high level of accuracy on the basis of both local and global signals even before they were required to make a choice, and even before they knew which physical action would be required. Furthermore, the combined signals from three specific brain areas (anterior cingulate cortex, medial prefrontal cortex, and ventral striatum) were found to provide all of the information sufficient to decode subjects' decisions out of all of the regions we studied. These findings implicate a specific network of regions in encoding information relevant to subsequent behavioral choice.
Additional Information
© 2007 by The National Academy of Sciences. Edited by Marcus E. Raichle, Washington University School of Medicine, St. Louis, MO, and approved December 7, 2006 (received for review July 25, 2006) We thank Dirk Neumann for helpful discussions. This work was supported by a grant from the Gimbel Discovery Fund For Neuroscience and a grant from the Gordon and Betty Moore Foundation (to J.P.O.). Author contributions: A.N.H. and J.P.O. designed research; A.N.H. performed research; A.N.H. analyzed data; and A.N.H. and J.P.O. wrote the paper. The authors declare no conflict of interest. This article is a PNAS direct submission. This article contains supporting information online at www.pnas.org/cgi/content/full/0606297104/DC1.Attached Files
Published - zpq1377.pdf
Supplemental Material - 06297Fig10.pdf
Supplemental Material - 06297Fig4.pdf
Supplemental Material - 06297Fig5.pdf
Supplemental Material - 06297Fig6.pdf
Supplemental Material - 06297Fig7.pdf
Supplemental Material - 06297Fig8.pdf
Supplemental Material - 06297Fig9.pdf
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Additional details
- PMCID
- PMC1783089
- Eprint ID
- 99474
- DOI
- 10.1073/pnas.0606297104
- Resolver ID
- CaltechAUTHORS:20191025-161102914
- Gimbel Discovery Fund
- Gordon and Betty Moore Foundation
- Created
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2019-10-28Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field