Cortical Brain Activity Reflecting Attentional Biasing Toward Reward-Predicting Cues Covaries with Economic Decision-Making Performance.

Journal Article

Adaptive choice behavior depends critically on identifying and learning from outcome-predicting cues. We hypothesized that attention may be preferentially directed toward certain outcome-predicting cues. We studied this possibility by analyzing event-related potential (ERP) responses in humans during a probabilistic decision-making task. Participants viewed pairs of outcome-predicting visual cues and then chose to wager either a small (i.e., loss-minimizing) or large (i.e., gain-maximizing) amount of money. The cues were bilaterally presented, which allowed us to extract the relative neural responses to each cue by using a contralateral-versus-ipsilateral ERP contrast. We found an early lateralized ERP response, whose features matched the attention-shift-related N2pc component and whose amplitude scaled with the learned reward-predicting value of the cues as predicted by an attention-for-reward model. Consistently, we found a double dissociation involving the N2pc. Across participants, gain-maximization positively correlated with the N2pc amplitude to the most reliable gain-predicting cue, suggesting an attentional bias toward such cues. Conversely, loss-minimization was negatively correlated with the N2pc amplitude to the most reliable loss-predicting cue, suggesting an attentional avoidance toward such stimuli. These results indicate that learned stimulus-reward associations can influence rapid attention allocation, and that differences in this process are associated with individual differences in economic decision-making performance.

Full Text

Duke Authors

Cited Authors

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

Published Date

  • January 2016

Published In

Volume / Issue

  • 26 / 1

Start / End Page

  • 1 - 11

PubMed ID

  • 25139941

Electronic International Standard Serial Number (EISSN)

  • 1460-2199

International Standard Serial Number (ISSN)

  • 1047-3211

Digital Object Identifier (DOI)

  • 10.1093/cercor/bhu160

Language

  • eng