Rapid brain responses independently predict gain maximization and loss minimization during economic decision making.
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Success in many decision-making scenarios depends on the ability to maximize gains and minimize losses. Even if an agent knows which cues lead to gains and which lead to losses, that agent could still make choices yielding suboptimal rewards. Here, by analyzing event-related potentials (ERPs) recorded in humans during a probabilistic gambling task, we show that individuals' behavioral tendencies to maximize gains and to minimize losses are associated with their ERP responses to the receipt of those gains and losses, respectively. We focused our analyses on ERP signals that predict behavioral adjustment: the frontocentral feedback-related negativity (FRN) and two P300 (P3) subcomponents, the frontocentral P3a and the parietal P3b. We found that, across participants, gain maximization was predicted by differences in amplitude of the P3b for suboptimal versus optimal gains (i.e., P3b amplitude difference between the least good and the best gains). Conversely, loss minimization was predicted by differences in the P3b amplitude to suboptimal versus optimal losses (i.e., difference between the worst and the least bad losses). Finally, we observed that the P3a and P3b, but not the FRN, predicted behavioral adjustment on subsequent trials, suggesting a specific adaptive mechanism by which prior experience may alter ensuing behavior. These findings indicate that individual differences in gain maximization and loss minimization are linked to individual differences in rapid neural responses to monetary outcomes.
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Published Version (Please cite this version)10.1523/JNEUROSCI.4242-12.2013
Publication InfoAppelbaum, Lawrence Gregory; Huettel, Scott; Pearson, John Michael; San Martín, R; & Woldorff, Marty G (2013). Rapid brain responses independently predict gain maximization and loss minimization during economic decision making. J Neurosci, 33(16). pp. 7011-7019. 10.1523/JNEUROSCI.4242-12.2013. Retrieved from https://hdl.handle.net/10161/13524.
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Associate Professor in Psychiatry and Behavioral Sciences
Greg Appelbaum is an Associate Professor in the Department of Psychiatry and Behavioral Sciences in the Duke University School of Medicine. He is a member of the Brain Stimulation Division of Psychiatry, where he directs the Human Performance Optimization lab (Opti Lab) and the Brain Stimulation Research Center As a member
Professor in the Department of Psychology and Neuroscience
Research in my laboratory investigates the brain mechanisms underlying economic and social decision making; collectively, this research falls into the field of “decision neuroscience” or "neuroeconomics". My laboratory uses fMRI to probe brain function, behavioral assays to characterize individual differences, and other physiological methods (e.g., eye tracking, pharmacological manipulation, genetics) to link brain and behavior. Concurrent with research on basic processes, my labo
Assistant Professor of Biostatistics and Bioinformatics
My research focuses on the application of machine learning methods to the analysis of brain data and behavior. I have a special interest in the neurobiology of reward and decision-making, particularly issues surrounding foraging, impulsivity, and self-control. More generally, I am interested in computational principles underlying brain organization at the mesoscale, and work in my lab studies phenomena that range from complex social behaviors to coding principles of the retina.
Professor of Psychiatry and Behavioral Sciences
Dr. Woldorff's main research interest is in the cognitive neuroscience of attention. At each and every moment of our lives, we are bombarded by a welter of sensory information coming at us from a myriad of directions and through our various sensory modalities -- much more than we can fully process. We must continuously select and extract the most important information from this welter of sensory inputs. How the human brain accomplishes this is one of the core challenges of modern cognitive neuro
Alphabetical list of authors with Scholars@Duke profiles.