Rapid brain responses independently predict gain maximization and loss minimization during economic decision making.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • San Martín, R; Appelbaum, LG; Pearson, JM; Huettel, SA; Woldorff, MG

Published Date

  • April 2013

Published In

Volume / Issue

  • 33 / 16

Start / End Page

  • 7011 - 7019

PubMed ID

  • 23595758

Pubmed Central ID

  • 23595758

Electronic International Standard Serial Number (EISSN)

  • 1529-2401

International Standard Serial Number (ISSN)

  • 0270-6474

Digital Object Identifier (DOI)

  • 10.1523/JNEUROSCI.4242-12.2013

Language

  • eng