Summary

जोखिम भरा है और अस्पष्ट प्रायोगिक अर्थशास्त्र और कार्यात्मक एमआरआई तरीके का उपयोग कर के विकल्प के व्यक्तिपरक मूल्य को मापने

Published: September 19, 2012
doi:

Summary

कार्यात्मक एमआरआई और व्यवहार के तरीके का उपयोग करने के लिए मानव मस्तिष्क में जोखिम भरा है और अस्पष्ट विकल्पों में से व्यक्तिपरक मूल्य के तंत्रिका प्रतिनिधित्व निर्धारित.

Abstract

Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed “risky”. In other cases when probabilities cannot be estimated, this is a condition described as “ambiguous”. While most people are averse to both risk and ambiguity1,2, the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3 to assess the neural representation of the subjective values of risky and ambiguous options4. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations.

In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual’s choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.

Protocol

1. प्रयोग की तैयारी पहले कदम के लिए जोखिम भरा है और अस्पष्ट विकल्प कि स्कैनर में स्क्रीन पर प्रस्तुत किया जाएगा का प्रतिनिधित्व दृश्य उत्तेजनाओं डिजाइन है. हम चित्रा 1 में प्रस्तुत पोकर चिप्स…

Discussion

हम प्रयोगात्मक अर्थशास्त्र से एक विधि का इस्तेमाल किया है 'विषयों व्यवहार की विशेषताएँ और जोखिम और अस्पष्टता की ओर व्यक्तिगत दृष्टिकोण का अनुमान. हम तो इन अनुमानों का इस्तेमाल करने के लिए तंत्रिका ?…

Divulgazioni

The authors have nothing to disclose.

Acknowledgements

हम उपयोगी और डिजाइन पर विचार – विमर्श और टिप्पणियों के लिए Aldo Rustichini धन्यवाद.
आईएल और पीडब्ल्यूजी तक एनआईए R01 AG033406 अनुदान द्वारा वित्त पोषित है.

Materials

Name Company Comments
Allegra Head Only 3.0 T MRI Scanner Siemens A whole body scanner can also be used
NM-011 transmit head coil Nova Medical  
E-prime Psychology Software Tools Stimuli presentation software
Matlab MathWorks  

Riferimenti

  1. Glimcher, P. W. Understanding risk: a guide for the perplexed. Cogn. Affect Behav. Neurosci. 8, 348-354 (2008).
  2. Camerer, C., Weber, M. Recent Developments in Modeling Preferences – Uncertainty and Ambiguity. Journal of Risk and Uncertainty. 5, 325-370 (1992).
  3. Holt, C. A., Laury, S. K. Risk aversion and incentive effects. Am. Econ. Rev. 92, 1644-1655 (2002).
  4. Levy, I., Snell, J., Nelson, A. J., Rustichini, A., Glimcher, P. W. Neural representation of subjective value under risk and ambiguity. J. Neurophysiol. 103, 1036-1047 (2010).
  5. Kahneman, D., Tversky, A. Prospect Theory – Analysis of Decision under Risk. Econometrica. 47, 263-291 (1979).
  6. Deichmann, R., Gottfried, J. A., Hutton, C., Turner, R. Optimized EPI for fMRI studies of the orbitofrontal cortex. Neuroimage. 19, 430-441 (2003).
  7. Gilboa, I., Schmeidler, D. Maxmin Expected Utility with Non-Unique Prior. J. Math Econ. 18, 141-153 (1989).
  8. Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., Camerer, C. F. Neural systems responding to degrees of uncertainty in human decision-making. Science. 310, 1680-1683 (2005).
  9. Boynton, G. A., Engel, S. A., Glover, G., Heeger, D. . J Neurosci. 16, 4207-4221 (1996).
  10. Forman, S. D. Improved Assessment of Significant Activation in Functional Magnetic-Resonance-Imaging (Fmri) – Use of a Cluster-Size Threshold. Magnetic Resonance in Medicine. 33, 636-647 (1995).
  11. Genovese, C. R., Lazar, N. A., Nichols, T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage. 15, 870-878 (2002).
  12. Huettel, S. A., Stowe, C. J., Gordon, E. M., Warner, B. T., Platt, M. L. Neural signatures of economic preferences for risk and ambiguity. Neuron. 49, 765-775 (2006).
  13. Smith, V. L. . Papers in experimental economics. , (1991).
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Citazione di questo articolo
Levy, I., Rosenberg Belmaker, L., Manson, K., Tymula, A., Glimcher, P. W. Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods. J. Vis. Exp. (67), e3724, doi:10.3791/3724 (2012).

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