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

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Date
2016-01
Authors
San Martín, René
Appelbaum, Lawrence G
Huettel, Scott A
Woldorff, Marty G
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Abstract
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.
Type
Journal article
Subject
EEG
ERP
N2pc
learning
reward
Adolescent
Adult
Attention
Brain
Brain Mapping
Cues
Decision Making
Evoked Potentials
Female
Humans
Male
Photic Stimulation
Reaction Time
Reward
Space Perception
Visual Perception
Young Adult
Permalink
https://hdl.handle.net/10161/12006
Published Version (Please cite this version)
10.1093/cercor/bhu160
Publication Info
San Martín, René; Appelbaum, Lawrence G; Huettel, Scott A; & Woldorff, Marty G (2016). Cortical Brain Activity Reflecting Attentional Biasing Toward Reward-Predicting Cues Covaries with Economic Decision-Making Performance. Cereb Cortex, 26(1). pp. 1-11. 10.1093/cercor/bhu160. Retrieved from https://hdl.handle.net/10161/12006.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Appelbaum

Lawrence Gregory Appelbaum

Adjunct Associate Professor in the Department of Psychiatry and Behavioral Sciences
Greg Appelbaum is an Adjunct Associate Professor in the Department of Psychiatry and Behavioral Sciences in the Duke University School of Medicine.  Dr. Appelbaum's research interests primarily concern the brain mechanisms underlying visual cognition, how these capabilities differ among individuals, and how they can be improved through behavioral, neurofeedback, and neuromodulation interventions. Within the field of cognitive neuroscience, his research has addressed visual pe
Huettel

Scott Huettel

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
Woldorff

Marty G. Woldorff

Professor in 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
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