Reward positivity elicited by predictive cues

A recent theory holds that a component of the human event-related brain potential called the reward positivity reflects a reward prediction error signal. We investigated this idea in gambling-like task in which, on each trial, a visual stimulus predicted a subsequent rewarding or nonrewarding outcome with 80% probability. Consistent with earlier results, we found that the reward positivity was larger to unexpected than to expected outcomes. In addition, we found that the predictive cues also elicited a reward positivity, as proposed by the theory. These results indicate that the reward positivity reflects the initial assessment of whether a trial will end in success or failure and the reappraisal of that information once the outcome actually occurs. NeuroReport 22:249-252 (C) 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins

Reward feedback stimuli elicit high-beta EEG oscillations in human dorsolateral prefrontal cortex

Reward-related feedback stimuli have been observed to elicit a burst of power in the beta frequency range over frontal areas of the human scalp. Recent discussions have suggested possible neural sources for this activity but there is a paucity of empirical evidence on the question. Here we recorded EEG from participants while they navigated a virtual T-maze to find monetary rewards. Consistent with previous studies, we found that the reward feedback stimuli elicited an increase in beta power (20-30 Hz) over a right-frontal area of the scalp. Source analysis indicated that this signal was produced in the right dorsolateral prefrontal cortex (DLPFC). These findings align with previous observations of reward-related beta oscillations in the DLPFC in non-human primates. We speculate that increased power in the beta frequency range following reward receipt reflects the activation of task-related neural assemblies that encode the stimulus-response mapping in working memory

The feedback correct-related positivity : sensitivity of the event-related brain potential to unexpected positive feedback

The N200 and the feedback error-related negativity (fERN) are two components of the event-related brain potential (ERP) that share similar scalp distributions, time courses, morphologies, and functional dependencies, which raises the question as to whether they are actually the same phenomenon. To investigate this issue, we recorded the ERP from participants engaged in two tasks that independently elicited the N200 and fERN. Our results indicate that they are, in fact, the same ERP component and further suggest that positive feedback elicits a positive-going deflection in the time range of the fERN. Taken together, these results indicate that negative feedback elicits a common N200 and that modulation of fERN amplitude results from the superposition on correct trials of a positive-going deflection that we term the feedback correct-related positivity

Model-free and model-based reward prediction errors in EEG

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world’s structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain

Thumbs up or thumbs down? Effects of neuroticism and depressive symptoms on psychophysiological responses to social evaluation in healthy students

The effects of neuroticism and depressive symptoms on psychophysiological responses in a social judgment task were examined in a sample of 101 healthy young adults. Participants performed a social judgment task in which they had to predict whether or not a virtual peer presented on a computer screen liked them. After the prediction, the actual judgment was shown, and behavioral, electrocortical, and cardiac responses to this judgment were measured. The feedback-related negativity (FRN) was largest after unexpected feedback. The largest P3 was found after the expected “like” judgments, and cardiac deceleration was largest following unexpected “do not like” judgments. Both the P3 and cardiac deceleration were affected by gender—that is, only males showed differential P3 responses to social judgments, and males showed stronger cardiac decelerations. Time–frequency analyses were performed to explore theta and delta oscillations. Theta oscillations were largest following unexpected outcomes and correlated with FRN amplitudes. Delta oscillations were largest following expected “like” judgments and correlated with P3 amplitudes. Self-reported trait neuroticism was significantly related to social evaluative predictions and cardiac reactivity to social feedback, but not to the electrocortical responses. That is, higher neuroticism scores were associated with a more negative prediction bias and with smaller cardiac responses to judgments for which a positive outcome was predicted. Depressive symptoms did not affect the behavioral and psychophysiological responses in this study. The results confirmed the differential sensitivities of various outcome measures to different psychological processes, but the found individual differences could only partly be ascribed to the collected subjective measures