Neural signatures of economic preferences for risk and ambiguity

Scott A. Huettel, C. Jill Stowe, Evan M. Gordon, Brent T. Warner, Michael L. Platt

Research output: Contribution to journalArticlepeer-review

510 Scopus citations

Abstract

People often prefer the known over the unknown, sometimes sacrificing potential rewards for the sake of surety. Overcoming impulsive preferences for certainty in order to exploit uncertain but potentially lucrative options may require specialized neural mechanisms. Here, we demonstrate by functional magnetic resonance imaging (fMRI) that individuals' preferences for risk (uncertainty with known probabilities) and ambiguity (uncertainty with unknown probabilities) predict brain activation associated with decision making. Activation within the lateral prefrontal cortex was predicted by ambiguity preference and was also negatively correlated with an independent clinical measure of behavioral impulsiveness, suggesting that this region implements contextual analysis and inhibits impulsive responses. In contrast, activation of the posterior parietal cortex was predicted by risk preference. Together, this novel double dissociation indicates that decision making under ambiguity does not represent a special, more complex case of risky decision making; instead, these two forms of uncertainty are supported by distinct mechanisms.

Original languageEnglish
Pages (from-to)765-775
Number of pages11
JournalNeuron
Volume49
Issue number5
DOIs
StatePublished - Mar 2 2006

Bibliographical note

Funding Information:
This work is supported by grants from the National Institutes of Mental Health (NIMH 70685) and from the National Institute of Neurological Disorders and Stroke (NINDS 41328) and by institutional resources provided by Duke University. The authors thank D. Purves and J. Neil Bearden for helpful comments and Erin Douglas and Steven Green for assistance in manuscript preparation. The authors declare that they have no conflicts of interest, financial or otherwise.

ASJC Scopus subject areas

  • General Neuroscience

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