Research report
Prospect theory on the brain? Toward a cognitive neuroscience of decision under risk

https://doi.org/10.1016/j.cogbrainres.2005.01.016Get rights and content

Abstract

Most decisions must be made without advance knowledge of their consequences. Economists and psychologists have devoted much attention to modeling decisions made under conditions of risk in which options can be characterized by a known probability distribution over possible outcomes. The descriptive shortcomings of classical economic models motivated the development of prospect theory (D. Kahneman, A. Tversky, Prospect theory: An analysis of decision under risk. Econometrica, 4 (1979) 263–291; A. Tversky, D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4) (1992) 297–323) the most successful behavioral model of decision under risk. In the prospect theory, subjective value is modeled by a value function that is concave for gains, convex for losses, and steeper for losses than for gains; the impact of probabilities are characterized by a weighting function that overweights low probabilities and underweights moderate to high probabilities. We outline the possible neural bases of the components of prospect theory, surveying evidence from human imaging, lesion, and neuropharmacology studies as well as animal neurophysiology studies. These results provide preliminary suggestions concerning the neural bases of prospect theory that include a broad set of brain regions and neuromodulatory systems. These data suggest that focused studies of decision making in the context of quantitative models may provide substantial leverage towards a fuller understanding of the cognitive neuroscience of decision making.

Introduction

Most decisions entail some degree of risk. Should one purchase an extended warranty on a new car or take one's chances? Dash through the middle of a busy street or take the long way via a crosswalk? Opt for surgery or radiation therapy for a tumor? Invest retirement savings in the stock market or treasury bills? From mundane dilemmas to life-defining decisions, we are usually forced to choose without knowing in advance what the consequences will be.

The study of decision making under risk has been a major thrust of microeconomics for most of the last century; however, it has only received significant attention from psychologists in the last few decades. Early behavioral studies provided simple cognitive accounts of preferences between chance gambles, with more recent studies exploring the role of affect, motivation, and social context in such decisions. The newest, and possibly most exciting, frontier in this research area is the effort to understand the ways in which neural processes mediate risk-taking behavior. The last few years have seen a tremendous push by neuroscientists and their collaborators to apply modern neurophysiology methods (e.g., ERP, fMRI, and animal models) to economic decisions. The purpose of this paper is to take stock of some of these early efforts and relate them to more traditional behavioral research on decision making under risk.

The lay concept of “risk” is associated with hazards that fill one with dread and/or are poorly understood [112]. In a financial context, people tend to think of risk as increasing with the magnitude and probability of potential losses [79]. Decision theorists, in contrast, view risk as increasing with the variance in the probability distribution of possible outcomes. Thus, a bet that offers $100 if a fair coin lands heads and nothing if it lands tails is more “risky” than an option that offers $60 if a fair coin lands heads and $40 if it lands tails. Economists following Knight [68] distinguish risk from uncertainty. Decisions under risk entail options that have well-specified or transparent outcome probabilities, such as a bet on a coin toss or a lottery with a known number of tickets. Decisions under uncertainty, by contrast, entail options whose outcomes depend on natural events such as a victory by the home team or a rise in interest rates, so that probabilities must be estimated by the decision maker with some degree of vagueness or imprecision. In the present paper, we focus our attention primarily on decisions under risk for the following practical reasons: (1) Risk is a simpler domain that is better understood and more thoroughly characterized by behavioral decision theorists, (2) most extant work in cognitive neuroscience at this early juncture speaks more directly to decisions under risk than to decisions under uncertainty.

The following section of this paper provides a brief historical overview of traditional models of decision making under risk, culminating in prospect theory [61], [123], the most influential descriptive account that has emerged to date. Next, we distill the most important facets of prospect theory and map them onto relevant neuroscience studies. In particular, we draw on basic neurophysiology, computational modeling, and clinical neuroimaging to advance a novel framework that describes several candidate mechanisms underlying risky choice behaviors. Finally, we conclude by suggesting promising avenues for future research. Naturally, at this early juncture, our conclusions are preliminary and highly speculative.

Section snippets

The Classical theory of decision under risk

The primitives in most traditional models of decision under risk and uncertainty are acts, states, and consequences. An act is an action that is associated with a set of possible consequences that depend on which one of a set of possible states of the world obtains. To illustrate, consider a gambler who considers betting a dollar on a single spin of a roulette wheel (see Table 1). The gambler considers two possible acts: Bet on “red” or bet on “black.” The consequence of this decision depends

Prospect theory

The Allais Paradox and fourfold pattern of risk attitudes are accommodated neatly by prospect theory [61], [123], the leading behavioral model of decision making under risk, and the major work for which psychologist Daniel Kahneman was awarded the 2002 Nobel Prize in economics. According to prospect theory, the value V of a simple prospect that pays $x with probability p (and nothing otherwise) is given byV(x,p)=v(x)w(p),where v measures the subjective value of the consequence x, and w measures

The neural basis of risky decision making

Although the study of decision making using cognitive neuroscience techniques is relatively young, a growing body of evidence suggests that decision making under risk is mediated by a network of cortical and limbic structures devoted to processing sensory, cognitive, and affective information, as well as widely-projecting neuromodulatory systems. In the discussion to follow, we will outline a set of preliminary hypotheses regarding the neural systems that may underlie some of the specific

Future directions

As the foregoing review outlines, there is a large body of suggestive evidence regarding the neural basis of decision making, and it is possible to at least weakly associate neural systems with the different components of prospect theory. Further work will be needed to better judge the degree to which this theory provides leverage towards understanding the neural basis of decision making. Some of the most interesting outstanding questions include:

Acknowledgments

Preparation of the manuscript was supported by NSF Grant DMI-0433693. Thanks to Sabrina Tom for assistance with manuscript preparation and Adam Aron, Liat Hadar, and Elizabeth Phelps for helpful comments.

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