Cooper, Nicole
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Publication Neuroanatomy Predicts Individual Risk Attitudes(2014-09-10) Gilaie-Dotan, Sharon; Cooper, Nicole; Tymula, Agnieszka; Kable, Joseph W; Glimcher, Paul W; Levy, IfatOver the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers.Publication The Neural Representation of Value and individual Differences in Human Intertemporal Choice(2013-01-01) Cooper, NicoleIntertemporal choices, or decisions that involve tradeoffs between rewards and time, are ubiquitous in our daily lives. The tendency to devalue, or discount, future rewards has been linked to maladaptive long-term health and financial outcomes. Despite their broad clinical relevance, individual differences in discounting preferences are poorly understood. In this thesis, we make progress on the understanding of the neural basis of these decisions and factors that affect individual differences. The first two chapters focus on neurobiology. Chapter 2 investigates the decision-related variables that best explain the observed patterns of BOLD activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) during intertemporal choice. We find that these regions carry different signals and likely contribute to different stages of the choice process. Across the brain, we find four kinds of value-responsive regions, each carrying different combinations of value-related signals. Next, we examine whether we can predict participants' choices from any or all of these groups of regions, and find that we can predict choice from most value-responsive regions, with interesting exceptions. In Chapter 3, we identify a novel brain predictor of individual differences in discounting. When participants are making judgments about how far away some number of days feels, discount rates, measured a week later, can be predicted from how VMPFC and VS respond as a function of temporal distance. This difference in the basic response to delayed time intervals could be a target for interventions aiming to reduce discount rates. In the final chapter, we find several behavioral manipulations that are able to reduce discount rates persistently and to a significant degree. We find that there is a general lack of knowledge about the normative strategy in the monetary discounting task, and that providing information about this strategy - to accept all delayed offers that provide higher interest rates than one could obtain elsewhere - reduces discounting significantly, for at least one month. Information about peers' strategies for making these decisions also reduces discounting. Taken together, this work advances our understanding of individual differences in discounting and further suggests interventions that could be used to reduce discounting.