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Heuristics Used By Humans With Prefrontal Cortex Damage: Toward An Empirical Model Of Phineas Gage

Author

Listed:
  • Daniel Houser

    (George Mason University)

  • Kevin McCabe

    (George Mason University)

  • Michael Keane

    (Yale University)

  • Antoine Bechara

    (University of Iowa)

Abstract

In many research contexts it is necessary to group experimental subjects into behavioral “types.” Usually, this is done by pre-specifying a set of candidate decision-making heuristics and then assigning each subject to the heuristic that best describes his/her behavior. Such approaches might not perform well when used to explain the behavior of subjects with prefrontal cortex damage. The reason is that introspection is typically used to generate the candidate heuristic set, but this procedure is likely to fail when applied to the decision-making strategies of subjects with brain damage. This research uses the type classification approach introduced by Houser, Keane and McCabe (2002) to investigate the heuristics used by subjects in the gambling experiment (Bechara, Damasio, Damasio and Anderson, 1994). An advantage of our classification approach is that it does not require us to specify the nature of subjects’ heuristics in advance. Rather, both the number and nature of the heuristics used are discerned directly from the experimental data. Our sample includes normal subjects, as well as subjects with damage to the ventromedial (VM) area of the prefrontal cortex. Subjects are “clustered” according to similarities in their heuristic, and this clustering does not preclude some normal and VM subjects from using the same decision rule. Our results are consistent with what others have found in subsequent experimentation with VM patients.

Suggested Citation

  • Daniel Houser & Kevin McCabe & Michael Keane & Antoine Bechara, 2003. "Heuristics Used By Humans With Prefrontal Cortex Damage: Toward An Empirical Model Of Phineas Gage," Experimental 0308002, EconWPA.
  • Handle: RePEc:wpa:wuwpex:0308002
    Note: Type of Document - pdf; prepared on IBM PC ; to print on PostScript; pages: 18; figures: included
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    References listed on IDEAS

    as
    1. El-Gamal, Mahmoud A. & Grether, David M., 1995. "Are People Bayesian? Uncovering Behavioral Strategies," Working Papers 919, California Institute of Technology, Division of the Humanities and Social Sciences.
    2. Houser, Daniel & Winter, Joachim, 2004. "How Do Behavioral Assumptions Affect Structural Inference? Evidence from a Laboratory Experiment," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 64-79, January.
    3. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, May.
    4. John F. Geweke & Michael P. Keane, 1996. "Bayesian inference for dynamic choice models without the need for dynamic programming," Working Papers 564, Federal Reserve Bank of Minneapolis.
    5. Geweke, John & Houser, Dan & Keane, Michael, 1999. "Simulation Based Inference for Dynamic Multinomial Choice Models," MPRA Paper 54279, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    experiments; heuristics; neuroeconomics; behavioral economics;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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