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The role of the orbitofrontal cortex in human adaptive learning under strategic environments

Author

Listed:
  • Kazuhiro Miyagawa

    () (Graduate School of Economics, Hitotsubashi University)

  • Tadanobu Misawa

    () (Graduate School of Science and Engineering, University of Toyama)

  • Tetsuya Shimokawa

    () (School of Management, Tokyo University of Science)

Abstract

This 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.

Suggested Citation

  • Kazuhiro Miyagawa & Tadanobu Misawa & Tetsuya Shimokawa, 2011. "The role of the orbitofrontal cortex in human adaptive learning under strategic environments," Economics Bulletin, AccessEcon, vol. 31(3), pages 2284-2297.
  • Handle: RePEc:ebl:ecbull:eb-11-00201
    as

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    References listed on IDEAS

    as
    1. Camelia Kuhnen & Brian Knutson, 2005. "The Neural Basis of Financial Risk Taking," Experimental 0509001, EconWPA.
    2. R. H. Strotz, 1955. "Myopia and Inconsistency in Dynamic Utility Maximization," Review of Economic Studies, Oxford University Press, vol. 23(3), pages 165-180.
    3. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    4. David Laibson, 1997. "Golden Eggs and Hyperbolic Discounting," The Quarterly Journal of Economics, Oxford University Press, vol. 112(2), pages 443-478.
    5. Knutson, Brian & Peterson, Richard, 2005. "Neurally reconstructing expected utility," Games and Economic Behavior, Elsevier, vol. 52(2), pages 305-315, August.
    6. 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.
    7. 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.
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    More about this item

    Keywords

    neuroeconomics; learning model; orbitofrontal cortex; neural network;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C0 - Mathematical and Quantitative Methods - - General

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