Faculty Bibliography

Economists, psychologists, and neuroscientists have long been interested in methods that elicit individuals' true valuations of goods. In this paper, we take 1 of the most popular of such mechanisms, the Becker-DeGroot-Marschak (BDM) procedure, and study the nature of the dependence of the valuations obtained using the BDM procedure on the distribution of prices presented to subjects when the method is implemented. In a within-subject design with products with a high market value, we show that this effect of price distribution occurs quite frequently, significantly impacts reported valuations, and is unlikely to be caused by misconceptions about the BDM procedure. This effect is largest when pricing distributions show a large peak close to an individual's average valuation of the good. A simple nonincentive-compatible subjective rating of the desirability of goods can be used to predict the likelihood that pricing distributions will influence BDM valuations; valuations for goods that subjects report to most want to purchase are most likely to be influenced by distributional structure. Our results challenge some of the dominant theoretical models of how BDM-like valuation procedures relate to standard notions of utility and shed light on how to interpret the data obtained using the BDM method.

Uncertainty, which is ubiquitous in decision-making, can be fractionated into known probabilities (risk) and unknown probabilities (ambiguity). Although research has illustrated that individuals more often avoid decisions associated with ambiguity compared to risk, it remains unclear why ambiguity is perceived as more aversive. Here we examine the role of arousal in shaping the representation of value and subsequent choice under risky and ambiguous decisions. To investigate the relationship between arousal and decisions of uncertainty, we measure skin conductance response-a quantifiable measure reflecting sympathetic nervous system arousal-during choices to gamble under risk and ambiguity. To quantify the discrete influences of risk and ambiguity sensitivity and the subjective value of each option under consideration, we model fluctuating uncertainty, as well as the amount of money that can be gained by taking the gamble. Results reveal that although arousal tracks the subjective value of a lottery regardless of uncertainty type, arousal differentially contributes to the computation of value-that is, choice-depending on whether the uncertainty is risky or ambiguous: Enhanced arousal adaptively decreases risk-taking only when the lottery is highly risky but increases risk-taking when the probability of winning is ambiguous (even after controlling for subjective value). Together, this suggests that the role of arousal during decisions of uncertainty is modulatory and highly dependent on the context in which the decision is framed. (PsycINFO Database Record

Many decisions involve uncertainty, or 'risk', regarding potential outcomes, and substantial empirical evidence has demonstrated that human aging is associated with diminished tolerance for risky rewards. Grey matter volume in a region of right posterior parietal cortex (rPPC) is predictive of preferences for risky rewards in young adults, with less grey matter volume indicating decreased tolerance for risk. That grey matter loss in parietal regions is a part of healthy aging suggests that diminished rPPC grey matter volume may have a role in modulating risk preferences in older adults. Here we report evidence for this hypothesis and show that age-related declines in rPPC grey matter volume better account for age-related changes in risk preferences than does age per se. These results provide a basis for understanding the neural mechanisms that mediate risky choice and a glimpse into the neurodevelopmental dynamics that impact decision-making in an aging population.

BACKGROUND: Video-based noninvasive eye trackers are an extremely useful tool for many areas of research. Many open-source eye trackers are available but current open-source systems are not designed to track eye movements with the temporal resolution required to investigate the mechanisms of oculomotor behavior. Commercial systems are available but employ closed source hardware and software and are relatively expensive, limiting wide-spread use. NEW METHOD: Here we present Oculomatic, an open-source software and modular hardware solution to eye tracking for use in humans and non-human primates. RESULTS: Oculomatic features high temporal resolution (up to 600Hz), real-time eye tracking with high spatial accuracy (<0.5 degrees ), and low system latency ( approximately 1.8ms, 0.32ms STD) at a relatively low-cost. COMPARISON WITH EXISTING METHOD(S): Oculomatic compares favorably to our existing scleral search-coil system while being fully non invasive. CONCLUSIONS: We propose that Oculomatic can support a wide range of research into the properties and neural mechanisms of oculomotor behavior.

Background: Impulsivity is a core feature of substance use disorders. Temporal discounting (TD) paradigms provide a modelbased approach to studying the dynamics of impulsive decisionmaking as drug-addicted individuals undergo treatment. Here we examine (1) how TD changes as opioid use disorder (OUD) subjects stabilize on maintenance therapy; and (2) how TD is predicted by (or is predictive of) relevant clinical outcomes. Methods: 30 individuals initiating treatment for OUD and 29 matched community controls (CC) were assessed weekly (up to 15 weeks) on a TD task. Drug use was monitored by urine toxicology and chart review. We analyzed the data with a hyperbolic discounting model and derived subject-specific parameters forTD rate, and the non-parametric proportion of immediate choices. Results: OUD subjects showed higher TD rates than CC (Means: 0.039 versus 0.139 respectively, p = 0.005). Although this measure had high test-retest reliability, OUD subjects exhibited more variability across the repeated measures. Subjects in the initial phase of treatment showed a progressive decrease of TD (p = 0.007). Recent heroin use predicted subjects' level of impulsivity: positive use in the previous week correlated with a significantly higher proportion of immediate choices (p = 0.02). We did not And a predictive effect of TD on heroin use the following week. Conclusions: These results suggest that TD greatly fluctuates in treatment-seeking heroin users, in contrast to its stability in CC. TD is both sensitive to the initial phase of treatment for OUD and to recent heroin use, but not predictive of future use in this population

Positive mood can affect a person's tendency to gamble, possibly because positive mood fosters unrealistic optimism. At the same time, unexpected positive outcomes, often called prediction errors, influence mood. However, a linkage between positive prediction errors-the difference between expected and obtained outcomes-and consequent risk taking has yet to be demonstrated. Using a large data set of New York City lottery gambling and a model inspired by computational accounts of reward learning, we found that people gamble more when incidental outcomes in the environment (e.g., local sporting events and sunshine) are better than expected. When local sports teams performed better than expected, or a sunny day followed a streak of cloudy days, residents gambled more. The observed relationship between prediction errors and gambling was ubiquitous across the city's socioeconomically diverse neighborhoods and was specific to sports and weather events occurring locally in New York City. Our results suggest that unexpected but incidental positive outcomes influence risk taking.

It is well known that hormones affect both brain and behavior, but less is known about the extent to which hormones affect economic decision-making. Numerous studies demonstrate gender differences in attitudes to risk and loss in financial decision-making, often finding that women are more loss and risk averse than men. It is unclear what drives these effects and whether cyclically varying hormonal differences between men and women contribute to differences in economic preferences. We focus here on how economic rationality and preferences change as a function of menstrual cycle phase in women. We tested adherence to the Generalized Axiom of Revealed Preference (GARP), the standard test of economic rationality. If choices satisfy GARP then there exists a well-behaved utility function that the subject's decisions maximize. We also examined whether risk attitudes and loss aversion change as a function of cycle phase. We found that, despite large fluctuations in hormone levels, women are as technically rational in their choice behavior as their male counterparts at all phases of the menstrual cycle. However, women are more likely to choose risky options that can lead to potential losses while ovulating; during ovulation women are less loss averse than men and therefore more economically rational than men in this regard. These findings may have market-level implications: ovulating women more effectively maximize expected value than do other groups.

Empirical decision-making in diverse species deviates from the predictions of normative choice theory, but why such suboptimal behavior occurs is unknown. Here, we propose that deviations from optimality arise from biological decision mechanisms that have evolved to maximize choice performance within intrinsic biophysical constraints. Sensory processing utilizes specific computations such as divisive normalization to maximize information coding in constrained neural circuits, and recent evidence suggests that analogous computations operate in decision-related brain areas. These adaptive computations implement a relative value code that may explain the characteristic context-dependent nature of behavioral violations of classical normative theory. Examining decision-making at the computational level thus provides a crucial link between the architecture of biological decision circuits and the form of empirical choice behavior.