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Published on: May 3, 2012
Outcome valence and stimulus frequency affect neural responses to rewards and punishments
James Glazer1, Robin Nusslock1
1Northwestern University, Evanston, Illinois, USA.
Abstract:
The Reward-Positivity (RewP) is a frontocentral event-related potential elicited following reward and punishment feedback. Reinforcement learning theories propose the RewP reflects a reward prediction error that increases following more favorable (vs. unfavorable) outcomes. An alternative perspective, however, proposes this component indexes a salience-prediction error that increases following more salient outcomes. Evidence from prior studies that included both reward and punishment conditions is mixed, supporting both accounts. However, these studies often varied how feedback stimuli were repeated across reward and punishment conditions. Differences in the frequency of feedback stimuli may drive inconsistencies by introducing salience effects for infrequent stimuli regardless of whether they are associated with rewards or punishments. To test this hypothesis, the current study examined the effect of outcome valence and stimulus frequency on the RewP and neighboring P2 and P3 components in reward, punishment, and neutral contexts across two separate experiments that varied how often feedback stimuli were repeated between conditions. Experiment 1 revealed infrequent feedback stimuli generated overlapping positivity across all three components. However, controlling for stimulus frequency, experiment 2 revealed favorable outcomes that increased RewP and P3 positivity. Together, these results suggest the RewP reflects some combination of reward- and salience-prediction error encoding. Results also indicate infrequent feedback stimuli elicited strong salience effects across all three components that may inflate, eliminate, or reverse outcome valence effects for the RewP and P3. These results resolve several inconsistencies in the literature and have important implications for electrocortical investigations of reward and punishment feedback processing.
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