Faculty Bibliography

How do humans make choices between different types of rewards? Economists have long argued on theoretical grounds that humans typically make these choices as if the values of the options they consider have been mapped to a single common scale for comparison. Neuroimaging studies in humans have recently begun to suggest the existence of a small group of specific brain sites that appear to encode the subjective values of different types of rewards on a neural common scale, almost exactly as predicted by theory. We have conducted a meta analysis using data from thirteen different functional magnetic resonance imaging studies published in recent years and we show that the principle brain area associated with this common representation is a subregion of the ventromedial prefrontal cortex (vmPFC)/orbitofrontal cortex (OFC). The data available today suggest that this common valuation path is a core system that participates in day-to-day decision making suggesting both a neurobiological foundation for standard economic theory and a tool for measuring preferences neurobiologically. Perhaps even more exciting is the possibility that our emerging understanding of the neural mechanisms for valuation and choice may provide fundamental insights into pathological choice behaviors like addiction, obesity and gambling.

Adolescents engage in a wide range of risky behaviors that their older peers shun, and at an enormous cost. Despite being older, stronger, and healthier than children, adolescents face twice the risk of mortality and morbidity faced by their younger peers. Are adolescents really risk-seekers or does some richer underlying preference drive their love of the uncertain? To answer that question, we used standard experimental economic methods to assess the attitudes of 65 individuals ranging in age from 12 to 50 toward risk and ambiguity. Perhaps surprisingly, we found that adolescents were, if anything, more averse to clearly stated risks than their older peers. What distinguished adolescents was their willingness to accept ambiguous conditions-situations in which the likelihood of winning and losing is unknown. Though adults find ambiguous monetary lotteries undesirable, adolescents find them tolerable. This finding suggests that the higher level of risk-taking observed among adolescents may reflect a higher tolerance for the unknown. Biologically, such a tolerance may make sense, because it would allow young organisms to take better advantage of learning opportunities; it also suggests that policies that seek to inform adolescents of the risks, costs, and benefits of unexperienced dangerous behaviors may be effective and, when appropriate, could be used to complement policies that limit their experiences.

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 ambiguity(1,2), 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 method(3 )to assess the neural representation of the subjective values of risky and ambiguous options(4). 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.

To survive in a dynamic environment, an organism must be able to effectively learn, store, and recall the expected benefits and costs of potential actions. The nature of the valuation and decision processes is thus of fundamental interest to researchers at the intersection of psychology, neuroscience, and economics. Although normative theories of choice have outlined the theoretical structure of these valuations, recent experiments have begun to reveal how value is instantiated in the activity of neurons and neural circuits. Here, we review the various forms of value coding that have been observed in different brain systems and examine the implications of these value representations for both neural circuits and behavior. In particular, we focus on emerging evidence that value coding in a number of brain areas is context dependent, varying as a function of both the current choice set and previously experienced values. Similar contextual modulation occurs widely in the sensory system, and efficient coding principles derived in the sensory domain suggest a new framework for understanding the neural coding of value.

The ability of human subjects to choose between disparate kinds of rewards suggests that the neural circuits for valuing different reward types must converge. Economic theory suggests that these convergence points represent the subjective values (SVs) of different reward types on a common scale for comparison. To examine these hypotheses and to map the neural circuits for reward valuation we had food and water-deprived subjects make risky choices for money, food, and water both in and out of a brain scanner. We found that risk preferences across reward types were highly correlated; the level of risk aversion an individual showed when choosing among monetary lotteries predicted their risk aversion toward food and water. We also found that partially distinct neural networks represent the SVs of monetary and food rewards and that these distinct networks showed specific convergence points. The hypothalamic region mainly represented the SV for food, and the posterior cingulate cortex mainly represented the SV for money. In both the ventromedial prefrontal cortex (vmPFC) and striatum there was a common area representing the SV of both reward types, but only the vmPFC significantly represented the SVs of money and food on a common scale appropriate for choice in our data set. A correlation analysis demonstrated interactions across money and food valuation areas and the common areas in the vmPFC and striatum. This may suggest that partially distinct valuation networks for different reward types converge on a unified valuation network, which enables a direct comparison between different reward types and hence guides valuation and choice.

A number of recent advances have been achieved in the study of midbrain dopaminergic neurons. Understanding these advances and how they relate to one another requires a deep understanding of the computational models that serve as an explanatory framework and guide ongoing experimental inquiry. This intertwining of theory and experiment now suggests very clearly that the phasic activity of the midbrain dopamine neurons provides a global mechanism for synaptic modification. These synaptic modifications, in turn, provide the mechanistic underpinning for a specific class of reinforcement learning mechanisms that now seem to underlie much of human and animal behavior. This review describes both the critical empirical findings that are at the root of this conclusion and the fantastic theoretical advances from which this conclusion is drawn.

The representation of value is a critical component of decision making. Rational choice theory assumes that options are assigned absolute values, independent of the value or existence of other alternatives. However, context-dependent choice behavior in both animals and humans violates this assumption, suggesting that biological decision processes rely on comparative evaluation. Here we show that neurons in the monkey lateral intraparietal cortex encode a relative form of saccadic value, explicitly dependent on the values of the other available alternatives. Analogous to extra-classical receptive field effects in visual cortex, this relative representation incorporates target values outside the response field and is observed in both stimulus-driven activity and baseline firing rates. This context-dependent modulation is precisely described by divisive normalization, indicating that this standard form of sensory gain control may be a general mechanism of cortical computation. Such normalization in decision circuits effectively implements an adaptive gain control for value coding and provides a possible mechanistic basis for behavioral context-dependent violations of rationality.