Decision Making under Risk and Ambiguity
Not all uncertain situations are created equally. In particular, economists distinguish between “risky” options – those whose outcome probabilities are fully known – and “ambiguous” options – those whose outcome probabilities are at least partly unknown. As it turns out, people vary substantially in their attitudes to risk and ambiguity, and there is little correlation between risk and ambiguity attitudes across individuals. One set of studies in our lab aims to characterize risk and ambiguity attitudes in various decision domains, to relate these attitudes to clinical symptoms and other personality traits, and to highlight the relevant neural mechanisms.
Decision making across the lifespan
Older adults must make complex financial and healthcare decisions in a highly uncertain and rapidly changing environment, prompting age-related changes in attitudes towards uncertainty throughout development. There is substantial evidence that choices older adults make lead to poorer outcomes compared to those made by their midlife counterparts. Little is known about the cognitive and motivational features underlying individual differences in decision making under uncertainty in these populations. This project aims to identify basic mechanisms that underlie individual differences and age-related changes in decision making under uncertainty. This research is crucial to fully understanding the neural mechanisms of individual decision traits, accurately predicting choice behavior under the many varying circumstances of real life, and designing effective decision aids for older adults.
Related Publications
Tymula, A., Belmaker, L. A. R., Roy, A. K., Ruderman, L., Manson, K., Glimcher, P. W., & Levy, I. (2012). Adolescents’ risk-taking behavior is driven by tolerance to ambiguity. Proceedings of the National Academy of Sciences, 109(42), 17135-17140.
Tymula, A., Belmaker, L. A. R., Ruderman, L., Glimcher, P. W., & Levy, I. (2013). Like cognitive function, decision making across the life span shows profound age-related changes. Proceedings of the National Academy of Sciences, 110(42), 17143-17148.
Grubb, M. A., Tymula, A., Gilaie-Dotan, S., Glimcher, P. W., & Levy, I. (2016). Neuroanatomy accounts for age-related changes in risk preferences. Nature communications, 7(1), 1-5.
In Collaboration With:
Michael Grubb, PhD at Trinity College
(Grubb et al., 2016)
rPPC grey-matter volume accounts for risk tolerance after controlling for age.
(Grubb et al., 2016)
Age-related declines in risk tolerance accounted for by age-related declines in rPPC grey matter volume
Using connectome-based predictive modeling to predict PTSD symptoms from decision-making attitudes
The neural networks involved in decision-making processes are large and span multiple regions within the brain. While regions such as the ventromedial PFC, anterior cingulate cortex, posterior cingulate cortex, and dorsal lateral PFC, ventral striatum, amygdala, and thalamus are all implicated in playing a dynamic role in decision-making processes, the functional connectivity underlying decision-making processes have yet to be examined. In collaboration with Dr. Ilan Harpaz-Rotem, this project seeks to understand how neural networks involved in decision-making processes differ between those with PTSD and controls and whether predictive models would be able to characterize symptoms based on observed differences in neural signatures.
In Collaboration With:
Ilan Harpaz-Rotem, PhD ABPP at Yale University
Dustin Scheinost, PhD at Yale University
Image Valuation
This project explores how irrelevant physical characteristics of images, such as size, impact valuation and decision-making. By manipulating image size, we study participants' reactions across key measures, including Likert ratings and willingness to pay. The study focuses on understanding how these non-informative features affect choices, even when they do not change the underlying value of the images. Insights from this research aim to reveal how subtle visual cues can bias judgment and influence consumer behavior, contributing to fields such as neuromarketing and cognitive bias in decision-making.
This walnut wrapped in persimmon was AI-generated to ensure no associations with existing brands or personal attachments to the food, serving as an example of the stimuli presented to participants.
Food Valuation
Obesity with binge eating (OB-BE) is associated with impaired reward processing and cognitive flexibility, which may be linked to alterations in how previous reward experiences are integrated into current decisions. Critically, updating food values in favor of healthier choices defines dietary interventions, of which OB-BE has lower efficacy rates than obesity alone. Studies probing this often use monetary rewards; however, food valuation is evolutionary and reflects strong, heterogeneous preferences. Yet very little is known about how inherent – rather than learned or calorically assumed – food values are updated. The central objective of my research is to identify behavioral mechanisms and neural correlates of inherent food value updating with attention to individual differences and investigate the relationship between learning flexibility and binge eating. This research supplements our long-term goal of understanding OB-BE as a distinct phenotype requiring unique and personalized intervention strategies.
The images of foods are from the Columbia Center for Eating Disorders, and in the study, the foods will be associated with different levels of inherent values that are either positive or negative.
Exploration of the Unknown: The Neural Basis of Trying Something New
This project seeks to uncover how the brain navigates novel choices, addressing central decision-making questions . By examining the neural circuits involved when individuals face new choice options and how these decisions are shaped by past outcomes, we aim to understand the cognitive principles behind novelty-driven exploration. Utilizing fMRI and computational modeling, the study will identify the brain circuits responsible for valuing and choosing new options. This research not only advances our understanding of human behavior but also holds potential applications in fields ranging from creativity to cognitive disorders and mental health.
In everyday life, individuals frequently face decisions with unknown outcomes. These scenarios range from something as simple as deciding whether to try a new dish.
Fear Memories, Learning, and PTSD-Related Projects
Levy Lab has also collaborated with a number of other labs and investigated topics related to fear memories, fear conditioning, and PTSD. Levy Lab collaborates with Dr. Ilan Harpaz-Rotem’s lab to study the effects of a one-time ketamine infusion alongside prolonged exposure psychotherapy in PTSD patients. Another project explores whether the memory reconsolidation window can be leveraged to treat PTSD, using fMRI and a novel fear conditioning paradigm, potentially leading to new therapies. The third project investigates the relationship between Cannabinoid receptor 1 (CB1r) availability, brain activation, and PTSD severity in U.S. veterans, focusing on the fear circuit.
Related Publications
Schiller, D., Kanen, J. W., LeDoux, J. E., Monfils, M. H., & Phelps, E. A. (2013). Extinction during reconsolidation of threat memory diminishes prefrontal cortex involvement. Proceedings of the National Academy of Sciences, 110(50), 20040-20045
In Collaboration With:
Ilan Harpaz-Rotem, PhD ABPP at Yale University
Daniela Schiller, PhD at Mount Sinai
Kelly Cosgrove, PhD at Yale University
(Schiller et al., 2013)
(A) Functional connectivity during early extinction using the vmPFC ROI as seed revealed robust coupling with amygdala (FDR < 0.05). (B) Psychophysiological interaction (PPI) analysis revealed stronger vmPFC–amygdala coupling during the nonreminded CS+ versus the reminded CS+ and the CS− (P < 0.05, corrected).