The role of the orbitofrontal cortex in human adaptive learning under strategic environments
AbstractThis paper proposes an augmented learning model from a neuroscience perspective. This model contains brain activity data of the orbitofrontal cortex as a predictive variable of human strategic behavior. A Bayesian 3-layer perceptron, which shows the complex relationship between decision factors, was adopted to describe the learning behavior. However, the model's complexity creates the possibility of over tting. To avoid this problem, we adopt the Bayesian estimation and Akaike's Bayesian information criteria, which provide the statistical basis of the model selection, to select the model. Our experience shows that this model can better predict human strategic behavior than do existing behavioral learning models.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by AccessEcon in its journal Economics Bulletin.
Volume (Year): 31 (2011)
Issue (Month): 3 ()
Contact details of provider:
neuroeconomics; learning model; orbitofrontal cortex; neural network;
Find related papers by JEL classification:
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C0 - Mathematical and Quantitative Methods - - General
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Camelia Kuhnen & Brian Knutson, 2005. "The Neural Basis of Financial Risk Taking," Experimental 0509001, EconWPA.
- Tyran, Jean-Robert, 2003. "Behavioral Game Theory. Experiments in Strategic Interaction: Colin F. Camerer, Princeton University Press, Princeton, New Jersey, 2003, p. 550, Price $65.00/[UK pound]42.95, ISBN 0-691-09039-4," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(6), pages 717-720, December.
- Knutson, Brian & Peterson, Richard, 2005. "Neurally reconstructing expected utility," Games and Economic Behavior, Elsevier, vol. 52(2), pages 305-315, August.
- Laibson, David, 1997.
"Golden Eggs and Hyperbolic Discounting,"
The Quarterly Journal of Economics,
MIT Press, vol. 112(2), pages 443-77, May.
- Amos Tversky & Daniel Kahneman, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Levine's Working Paper Archive
7656, David K. Levine.
- Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March.
- Tversky, Amos & Kahneman, Daniel, 1992. " Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (John P. Conley).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.