Risky business: the neuroeconomics of decision making under uncertainty

Many decisions involve uncertainty, or imperfect knowledge about how choices lead to outcomes. Colloquial notions of uncertainty, particularly when describing a decision as 'risky', often carry connotations of potential danger as well. Gambling on a long shot, whether a horse at the racetrack or a foreign oil company in a hedge fund, can have negative consequences, but the impact of uncertainty on decision making extends beyond gambling. Indeed, uncertainty in some form pervades nearly all our choices in daily life. Stepping into traffic to hail a cab, braving an ice storm to be the first at work, or dating the boss's son or daughter also offer potentially great windfalls, at the expense of surety. We continually face trade-offs between options that promise safety and others that offer an uncertain potential for jackpot or bust. When mechanisms for dealing with uncertain outcomes fail, as in mental disorders such as problem gambling or addiction, the results can be disastrous. Thus, understanding decision making—indeed, understanding behavior itself—requires knowing how the brain responds to and uses information about uncertainty.

This is a preview of subscription content, access via your institution

Access options

Subscribe to this journal

Receive 12 print issues and online access

206,07 € per year

only 17,17 € per issue

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

Heuristics in risky decision-making relate to preferential representation of information

Article Open access 20 May 2024

Individual risk attitudes arise from noise in neurocognitive magnitude representations

Article 17 July 2023

Risk taking for potential losses but not gains increases with time of day

Article Open access 04 April 2023

References

  1. Bernoulli, D. Specimen theoriae novae de mensura sortis. Commentarii Academiae Scientarum Imperialis Petropolitanae5, 175–192 (1738). Google Scholar
  2. Samuelson, P.A. Consumption theory in terms of revealed preference. Economica15, 243–253 (1948). ArticleGoogle Scholar
  3. Camerer, C.F. Prospect theory in the wild: evidence from the field. in Choices, Values, and Frames (eds. Kahneman, D. & Tversky, A.) 288–300 (Cambridge Univ. Press, Cambridge, UK, 1981). Google Scholar
  4. Post, T., van den Assem, M., Baltussen, G. & Thaler, R.H. Deal or no deal? Decision making under risk in a large-payoff game show. Am. Econ. Rev. (in the press).
  5. Knight, F.H. Risk, Uncertainty, and Profit (Houghton Mifflin, New York, 1921). Google Scholar
  6. Ellsberg, D. Risk, ambiguity, and the Savage axioms. Q. J. Econ.75, 643–669 (1961). ArticleGoogle Scholar
  7. Kahneman, D. & Tversky, A. Prospect theory: an analysis of decision under risk. Econometrica47, 263–291 (1979). ArticleGoogle Scholar
  8. Tversky, A. & Kahneman, D. Advances in prospect theory: cumulative representation of uncertainty. J. Risk Uncertain.5, 297–323 (1992). ArticleGoogle Scholar
  9. Camerer, C. & Weber, M. Recent developments in modeling preferences: uncertainty and ambiguity. J. Risk Uncertain.5, 325–370 (1992). ArticleGoogle Scholar
  10. Ghirardato, P., Maccheroni, F. & Marinacci, M. Differentiating ambiguity and ambiguity attitude. J. Econ. Theory118, 133–173 (2004). ArticleGoogle Scholar
  11. Tversky, A. & Fox, C.R. Weighing risk and uncertainty. Psychol. Rev.102, 269–283 (1995). ArticleGoogle Scholar
  12. MacCrimmon, K.R. & Wehrung, D.A. Taking Risks: The Management of Uncertainty (Free Press, New York, 1986). Google Scholar
  13. Slovic, P. Assessment of risk taking behavior. Psychol. Bull.61, 220–233 (1964). ArticleCASPubMedGoogle Scholar
  14. Weber, E.U., Blais, A.R. & Betz, E. A domain specific risk-attitude scale: measuring risk perceptions and risk behaviors. J. Behav. Decis. Making15, 263–290 (2002). ArticleGoogle Scholar
  15. Hsee, C.K. & Weber, E.U. Cross-national differences in risk preference and lay predictions. J. Behav. Decis. Making12, 165–179 (1999). ArticleGoogle Scholar
  16. Bontempo, R.N., Bottom, W.P. & Weber, E.U. Cross-cultural differences in risk perception: a model-based approach. Risk Anal.17, 479–488 (1997). ArticleGoogle Scholar
  17. Kacelnik, A. & Bateson, M. Risky theories—the effects of variance on foraging decisions. Am. Zool.36, 402–434 (1996). ArticleGoogle Scholar
  18. Stephens, D.W. & Krebs, J.R. Foraging Theory (Princeton Univ. Press, Princeton, New Jersey, USA, 1986). Google Scholar
  19. Caraco, T. Energy budgets, risk and foraging preferences in dark-eyed juncos (Junco hyemalis). Behav. Ecol. Sociobiol.8, 213–217 (1981). ArticleGoogle Scholar
  20. Gilby, I.C. & Wrangham, R.W. Risk-prone hunting by chimpanzees (Pan troglodytes schweinfurthii) increases during periods of high diet quality. Behav. Ecol. Sociobiol.61, 1771–1779 (2007). ArticleGoogle Scholar
  21. Kacelnik, A. Normative and descriptive models of decision making: time discounting and risk sensitivity. Ciba Found. Symp.208, 51–67 discussion 208, 67–70 (1997). CASPubMedGoogle Scholar
  22. Bateson, M. & Kacelnik, A. Starlings' preferences for predictable and unpredictable delays to food. Anim. Behav.53, 1129–1142 (1997). ArticleCASPubMedGoogle Scholar
  23. Mazur, J.E. An adjusting procedure for studying delayed reinforcement. in The Effect of Delay and of Intervening Events on Reinforcement Value (eds. Commons, M., Mazur, J., Nevin, J. & Rachlin, H.) 55–73 (Erlbaum, Hillsdale, New Jersey, USA, 1987). Google Scholar
  24. Gibbon, J. Scalar expectancy theory and Weber's law in animal timing. Psychol. Rev.84, 279–335 (1977). ArticleGoogle Scholar
  25. McNamara, J.M. & Houston, A.I. The common currency for behavioral decisions. Am. Nat.127, 358–378 (1986). ArticleGoogle Scholar
  26. Kalenscher, T. Decision making: don't risk a delay. Curr. Biol.17, R58–R61 (2007). ArticleCASPubMedGoogle Scholar
  27. Rachlin, H. The Science of Self-Control (Harvard Univ. Press, Cambridge, Massachusetts, USA, 2000). Google Scholar
  28. Hayden, B.Y. & Platt, M.L. Temporal discounting predicts risk sensitivity in rhesus macaques. Curr. Biol.17, 49–53 (2007). ArticleCASPubMedPubMed CentralGoogle Scholar
  29. Volz, K.G., Schubotz, R.I. & von Cramon, D.Y. Predicting events of varying probability: uncertainty investigated by fMRI. Neuroimage19, 271–280 (2003). ArticlePubMedGoogle Scholar
  30. Volz, K.G., Schubotz, R.I. & von Cramon, D.Y. Why am I unsure? Internal and external attributions of uncertainty dissociated by fMRI. Neuroimage21, 848–857 (2004). ArticlePubMedGoogle Scholar
  31. Elliott, R. & Dolan, R.J. Activation of different anterior cingulate foci in association with hypothesis testing and response selection. Neuroimage8, 17–29 (1998). ArticleCASPubMedGoogle Scholar
  32. Schubotz, R.I. & von Cramon, D.Y. A blueprint for target motion: fMRI reveals perceived sequential complexity to modulate premotor cortex. Neuroimage16, 920–935 (2002). ArticlePubMedGoogle Scholar
  33. Huettel, S.A., Song, A.W. & McCarthy, G. Decisions under uncertainty: probabilistic context influences activity of prefrontal and parietal cortices. J. Neurosci.25, 3304–3311 (2005). ArticleCASPubMedPubMed CentralGoogle Scholar
  34. Paulus, M.P. et al. Prefrontal, parietal, and temporal cortex networks underlie decision-making in the presence of uncertainty. Neuroimage13, 91–100 (2001). ArticleCASPubMedGoogle Scholar
  35. Koechlin, E., Ody, C. & Kouneiher, F. The architecture of cognitive control in the human prefrontal cortex. Science302, 1181–1185 (2003). ArticleCASPubMedGoogle Scholar
  36. Miller, E.K. & Cohen, J.D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci.24, 167–202 (2001). ArticleCASPubMedGoogle Scholar
  37. Bunge, S.A., Hazeltine, E., Scanlon, M.D., Rosen, A.C. & Gabrieli, J.D. Dissociable contributions of prefrontal and parietal cortices to response selection. Neuroimage17, 1562–1571 (2002). ArticlePubMedGoogle Scholar
  38. Dehaene, S., Piazza, M., Pinel, P. & Cohen, L. Three parietal circuits for number processing. Cogn. Neuropsychol.20, 487–506 (2003). ArticlePubMedGoogle Scholar
  39. Schultz, W. & Dickinson, A. Neuronal coding of prediction errors. Annu. Rev. Neurosci.23, 473–500 (2000). ArticleCASPubMedGoogle Scholar
  40. Montague, P.R., Dayan, P. & Sejnowski, T.J. A framework for mesencephalic dopamine systems based on predictive Hebbian learning. J. Neurosci.16, 1936–1947 (1996). ArticleCASPubMedPubMed CentralGoogle Scholar
  41. Schultz, W., Dayan, P. & Montague, P.R. A neural substrate of prediction and reward. Science275, 1593–1599 (1997). ArticleCASPubMedGoogle Scholar
  42. Knutson, B., Fong, G.W., Adams, C.M., Varner, J.L. & Hommer, D. Dissociation of reward anticipation and outcome with event-related fMRI. Neuroreport12, 3683–3687 (2001). ArticleCASPubMedGoogle Scholar
  43. Knutson, B., Taylor, J., Kaufman, M., Peterson, R. & Glover, G. Distributed neural representation of expected value. J. Neurosci.25, 4806–4812 (2005). ArticleCASPubMedPubMed CentralGoogle Scholar
  44. Berns, G.S., McClure, S.M., Pagnoni, G. & Montague, P.R. Predictability modulates human brain response to reward. J. Neurosci.21, 2793–2798 (2001). ArticleCASPubMedPubMed CentralGoogle Scholar
  45. McClure, S.M., Berns, G.S. & Montague, P.R. Temporal prediction errors in a passive learning task activate human striatum. Neuron38, 339–346 (2003). ArticleCASPubMedGoogle Scholar
  46. Delgado, M.R., Nystrom, L.E., Fissell, C., Noll, D.C. & Fiez, J.A. Tracking the hemodynamic responses to reward and punishment in the striatum. J. Neurophysiol.84, 3072–3077 (2000). ArticleCASPubMedGoogle Scholar
  47. Breiter, H.C., Aharon, I., Kahneman, D., Dale, A. & Shizgal, P. Functional imaging of neural responses to expectancy and experience of monetary gains and losses. Neuron30, 619–639 (2001). ArticleCASPubMedGoogle Scholar
  48. Azim, E., Mobbs, D., Jo, B., Menon, V. & Reiss, A.L. Sex differences in brain activation elicited by humor. Proc. Natl. Acad. Sci. USA102, 16496–16501 (2005). ArticleCASPubMedPubMed CentralGoogle Scholar
  49. Aharon, I. et al. Beautiful faces have variable reward value: fMRI and behavioral evidence. Neuron32, 537–551 (2001). ArticleCASPubMedGoogle Scholar
  50. Lohrenz, T., McCabe, K., Camerer, C.F. & Montague, P.R. Neural signature of fictive learning signals in a sequential investment task. Proc. Natl. Acad. Sci. USA104, 9493–9498 (2007). ArticleCASPubMedPubMed CentralGoogle Scholar
  51. Preuschoff, K., Bossaerts, P. & Quartz, S.R. Neural differentiation of expected reward and risk in human subcortical structures. Neuron51, 381–390 (2006). ArticleCASPubMedGoogle Scholar
  52. Paulus, M.P., Rogalsky, C., Simmons, A., Feinstein, J.S. & Stein, M.B. Increased activation in the right insula during risk-taking decision making is related to harm avoidance and neuroticism. Neuroimage19, 1439–1448 (2003). ArticlePubMedGoogle Scholar
  53. Kuhnen, C.M. & Knutson, B. The neural basis of financial risk taking. Neuron47, 763–770 (2005). ArticleCASPubMedGoogle Scholar
  54. Paulus, M.P., Lovero, K.L., Wittmann, M. & Leland, D.S. Reduced behavioral and neural activation in stimulant users to different error rates during decision making. Biol. Psychiatry, published online 23 October 2007 (doi:10.1016/j.biopsych.2007.09.007). ArticlePubMedGoogle Scholar
  55. Venkatraman, V., Chuah, Y.M., Huettel, S.A. & Chee, M.W. Sleep deprivation elevates expectation of gains and attenuates response to losses following risky decisions. Sleep30, 603–609 (2007). ArticlePubMedGoogle Scholar
  56. Damasio, A.R. The somatic marker hypothesis and the possible functions of the prefrontal cortex. Phil. Trans. R. Soc. Lond. B351, 1413–1420 (1996). ArticleCASGoogle Scholar
  57. Craig, A.D. How do you feel? Interoception: the sense of the physiological condition of the body. Nat. Rev. Neurosci.3, 655–666 (2002). ArticleCASPubMedGoogle Scholar
  58. Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E. & Cohen, J.D. The neural basis of economic decision-making in the Ultimatum Game. Science300, 1755–1758 (2003). ArticleCASPubMedGoogle Scholar
  59. Tom, S.M., Fox, C.R., Trepel, C. & Poldrack, R.A. The neural basis of loss aversion in decision-making under risk. Science315, 515–518 (2007). ArticleCASPubMedGoogle Scholar
  60. Kringelbach, M.L. The human orbitofrontal cortex: linking reward to hedonic experience. Nat. Rev. Neurosci.6, 691–702 (2005). ArticleCASPubMedGoogle Scholar
  61. O'Doherty, J., Kringelbach, M.L., Rolls, E.T., Hornak, J. & Andrews, C. Abstract reward and punishment representations in the human orbitofrontal cortex. Nat. Neurosci.4, 95–102 (2001). ArticleCASPubMedGoogle Scholar
  62. Seymour, B., Daw, N., Dayan, P., Singer, T. & Dolan, R. Differential encoding of losses and gains in the human striatum. J. Neurosci.27, 4826–4831 (2007). ArticleCASPubMedPubMed CentralGoogle Scholar
  63. Hsu, M., Bhatt, M., Adolphs, R., Tranel, D. & Camerer, C.F. Neural systems responding to degrees of uncertainty in human decision-making. Science310, 1680–1683 (2005). ArticleCASPubMedGoogle Scholar
  64. Huettel, S.A., Stowe, C.J., Gordon, E.M., Warner, B.T. & Platt, M.L. Neural signatures of economic preferences for risk and ambiguity. Neuron49, 765–775 (2006). ArticleCASPubMedGoogle Scholar
  65. Rustichini, A., Dickhaut, J., Ghirardato, P., Smith, K. & Pardo, J.V. A brain imaging study of the choice procedure. Games Econ. Behav.52, 257–282 (2005). ArticleGoogle Scholar
  66. Daw, N.D., O'Doherty, J.P., Dayan, P., Seymour, B. & Dolan, R.J. Cortical substrates for exploratory decisions in humans. Nature441, 876–879 (2006). ArticleCASPubMedPubMed CentralGoogle Scholar
  67. Fiorillo, C.D., Tobler, P.N. & Schultz, W. Discrete coding of reward probability and uncertainty by dopamine neurons. Science299, 1898–1902 (2003). ArticleCASPubMedGoogle Scholar
  68. Niv, Y., Duff, M.O. & Dayan, P. Dopamine, uncertainty and TD learning. Behav. Brain Funct.1, 6 (2005). ArticlePubMedPubMed CentralGoogle Scholar
  69. Fiorillo, C.D., Tobler, P.N. & Schultz, W. Evidence that the delay-period activity of dopamine neurons corresponds to reward uncertainty rather than backpropagating TD errors. Behav. Brain Funct.1, 7 (2005). ArticlePubMedPubMed CentralGoogle Scholar
  70. Cardinal, R.N. & Howes, N.J. Effects of lesions of the nucleus accumbens core on choice between small certain rewards and large uncertain rewards in rats. BMC Neurosci.6, 37 (2005). ArticlePubMedPubMed CentralGoogle Scholar
  71. Dodd, M.L. et al. Pathological gambling caused by drugs used to treat Parkinson disease. Arch. Neurol.62, 1377–1381 (2005). ArticlePubMedGoogle Scholar
  72. Driver-Dunckley, E., Samanta, J. & Stacy, M. Pathological gambling associated with dopamine agonist therapy in Parkinson's disease. Neurology61, 422–423 (2003). ArticleCASPubMedGoogle Scholar
  73. McCoy, A.N. & Platt, M.L. Risk-sensitive neurons in macaque posterior cingulate cortex. Nat. Neurosci.8, 1220–1227 (2005). ArticleCASPubMedGoogle Scholar
  74. Vogt, B.A., Finch, D.M. & Olson, C.R. Functional heterogeneity in cingulate cortex: the anterior executive and posterior evaluative regions. Cereb. Cortex2, 435–443 (1992). CASPubMedGoogle Scholar
  75. Smith, K., Dickhaut, J., McCabe, K. & Pardo, J.V. Neuronal substrates for choice under ambiguity, risk, gains, and losses. Manage. Sci.48, 711–718 (2002). ArticleGoogle Scholar
  76. Kable, J.W. & Glimcher, P.W. The neural correlates of subjective value during intertemporal choice. Nat. Neurosci.10, 1625–1633 (2007). ArticleCASPubMedPubMed CentralGoogle Scholar
  77. Small, D.M., Zatorre, R.J., Dagher, A., Evans, A.C. & Jones-Gotman, M. Changes in brain activity related to eating chocolate: from pleasure to aversion. Brain124, 1720–1733 (2001). ArticleCASPubMedGoogle Scholar
  78. Dean, H.L., Crowley, J.C. & Platt, M.L. Visual and saccade-related activity in macaque posterior cingulate cortex. J. Neurophysiol.92, 3056–3068 (2004). ArticlePubMedGoogle Scholar
  79. Olson, C.R., Musil, S.Y. & Goldberg, M.E. Single neurons in posterior cingulate cortex of behaving macaque: eye movement signals. J. Neurophysiol.76, 3285–3300 (1996). ArticleCASPubMedGoogle Scholar
  80. McCoy, A.N., Crowley, J.C., Haghighian, G., Dean, H.L. & Platt, M.L. Saccade reward signals in posterior cingulate cortex. Neuron40, 1031–1040 (2003). ArticleCASPubMedGoogle Scholar
  81. Meyer, G. et al. Casino gambling increases heart rate and salivary cortisol in regular gamblers. Biol. Psychiatry48, 948–953 (2000). ArticleCASPubMedGoogle Scholar

Acknowledgements

The authors wish to thank B. Hayden for comments on the manuscript and D. Smith for assistance with figure construction. The Center for Neuroeconomic Studies at Duke University is supported by the Office of the Provost and by the Duke Institute for Brain Sciences. The authors are also supported by MH-070685 (S.A.H.), EY-13496 (M.L.P.) and MH-71817 (M.L.P.).

Author information

Authors and Affiliations

  1. Center for Neuroeconomic Studies, Room B243F LSRC Building, Duke University, Durham, 27708-0999, North Carolina, USA Michael L Platt & Scott A Huettel
  1. Michael L Platt