Learning‐related changes in reward expectancy are reflected in the feedback‐related negativity

Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures--that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model predicts an FRN on negative prediction errors, as well as implying a role for the FRN in learning and the adaptation of behavior. However, these predictions have recently been challenged. Notably, studies so far have used tasks in which the outcomes have been contingent on the response. In these paradigms, the need to adapt behavioral responses is present only for negative, not for positive feedback. The goal of the present study was to investigate the effects of positive as well as negative violations of expectancy on FRN amplitudes, without the usual confound of behavioral adjustments. A reversal-learning task was employed in which outcome value and outcome expectancy were orthogonalized; that is, both positive and negative outcomes were equally unexpected. The results revealed a double dissociation, with effects of valence but not expectancy on the FRN and, conversely, effects of expectancy but not valence on the P300. While FRN amplitudes were largest for negative-outcome trials, irrespective of outcome expectancy, P300 amplitudes were largest for unexpected-outcome trials, irrespective of outcome valence. These FRN effects were interpreted to reflect an evaluation along a good-bad dimension, rather than reflecting a negative prediction error or a role in behavioral adaptation. By contrast, the P300 reflects the updating of information relevant for behavior in a changing context.

Asymmetric Modulation of FRN by the Probability and Value of Outcomes in Auditory Mid Task

Decision-making is a fundamental aspect of human behavior, especially in uncertain situations where social interactions play a significant role. Social dominance, which involves power dynamics within groups, holds the potential to shape decision-making. Individuals' expectations and certainty about outcomes are crucial for monitoring their performance in social dominance situations. However, the impact of expected and unexpected uncertainty on decision-making in social dominance contexts remains unclear. This study aimed to unravel the neural and behavioral patterns associated with decision-making across varying social dominance levels under conditions of uncertainty. Researchers investigated this by analyzing brain activity in 51 students. Participants were presented with both positive and negative feedback under conditions of both expectation and uncertainty, while their brain activity was recorded using electroencephalography (EEG). Specifically, we investigated the properties of key neural correlates of feedback processing, including feedback-related negativity (FRN), and P3 components of event-related potential (ERP), and reward prediction error (RPE) signals. The results revealed that the low-dominance group exhibited a larger FRN amplitude than the high-dominance group. Also, unexpected-uncertain negative feedback elicits a stronger FRN amplitude than other conditions. P3 amplitude was larger for high-dominance compared to low-dominance individuals. Additionally, P3 amplitude varied by feedback valence and condition, with larger amplitudes for positive feedback and unexpected-uncertain conditions. In FRN wave difference, the high-dominance individuals exhibited more negative amplitude in unexpected-uncertain conditions. This reveals distinct neural responses to uncertainty and feedback between individuals with high and low dominance, suggesting that social hierarchy modulates brain mechanisms underlying decision-making and reward processing.

Feedback and reward processing in high-functioning autism

In action monitoring, i.e., evaluating an outcome of our behavior, a reward prediction error signal is calculated as the difference between actual and predicted outcomes and is used to adjust future behavior. Previous studies demonstrate that this signal, which is reflected by an event-related brain potential called feedback-related negativity (FRN), occurs in response to not only one's own outcomes, but also those of others. However, it is still unknown if predictions of different actors' performance interact with each other. Thus, we investigated how predictions from one’s own and another’s performance history affect each other by manipulating the task difficulty for participants themselves and their partners independently. Pairs of participants performed a time estimation task, randomly switching the roles of actor and observer from trial to trial. Results show that the history of the other’s performance did not modulate the amplitude of the FRN for the evaluation of one’s own outcomes. In contrast, the amplitude of the observer FRN for the other’s outcomes differed according to the frequency of one’s own action outcomes. In conclusion, the monitoring system tracks the histories of one’s own and observed outcomes separately and considers information related to one’s own action outcomes to be more important.

Older adults who worry about their own cognitive capabilities declining, but who do not show evidence of actual cognitive decline in neuropsychological tests, are at an increased risk of being diagnosed with dementia at a later time. Since neural markers may be more sensitive to early stages of cognitive decline, in the present study we examined whether event-related potential responses of feedback processing, elicited in a probabilistic learning task, differ between healthy older adults recruited from the community, who either did (subjective cognitive decline/SCD-group) or did not report (No-SCD group) worry about their own cognition declining beyond the normal age-related development. In the absence of group differences in learning from emotionally charged feedback in the probabilistic learning task, the amplitude of the feedback-related negativity (FRN) varied with feedback valence differently in the two groups: In the No-SCD group, the FRN was larger for positive than negative feedback, while in the SCD group, FRN amplitude did not differ between positive and negative feedback. The P3b was enhanced for negative feedback in both groups, and group differences in P3b amplitude were not significant. Altered sensitivity in neural processing of negative versus positive feedback may be a marker of SCD.

Adolescence has frequently been characterized as a period of increased risk taking, which may be largely driven by maturational changes in neural areas that process incentives. To investigate age- and gender-related differences in reward processing, we recorded event-related potentials (ERPs) from 80 participants in a gambling game, in which monetary wins and losses were either large or small. We measured two ERP components: the feedback-related negativity (FRN) and the feedback P3 (fP3). The FRN was sensitive to the size of a win in both adult (aged 23-35 years) and adolescent (aged 13-17 years) males, but not in females. Small wins appeared to be less rewarding for males than for females, which may in part explain more approach-driven behavior in males in general. Furthermore, adolescent boys showed both delayed FRNs to high losses and less differentiation in FRN amplitude between wins and losses in comparison to girls. The fP3, which is thought to index the salience of the feedback at a more conscious level than the FRN, was also larger in boys than in girls. Taken together, these results imply that higher levels of risk taking that are commonly reported in adolescent males may be driven both by hypersensitivity to high rewards and insensitivity to punishment or losses.

Processing of performance-related feedback is an essential prerequisite for adaptive behavior. Even though in everyday life feedback is rarely immediate, to date very few studies have investigated whether the feedback-related negativity (FRN), a relative negativity in the ERP approximately 200 to 300 ms after feedback that is sensitive to feedback valence and predictability, is modulated by feedback timing, and findings are inconsistent. The present study investigated effects of gradually increasing feedback delays on feedback processing in the FRN time window. Subjects completed a probabilistic learning task in which feedback was provided after short, intermediate, or long delays. Difference wave-based analyses showed that amplitudes decreased linearly with increasing feedback delay. A distinct pattern was observed for the FRN as defined in the original waveforms, with FRN amplitudes being largest for long and smallest for short delays. This pattern of results is consistent with the notion that the neural systems underlying feedback processing vary depending on feedback timing. The gradually reduced difference wave signal might reflect a gradual shift away from processing in frontostriatal circuits toward medial temporal involvement. To what extent increased signal amplitudes for longer delays in the original waveforms are related to processing in certain brain structures will need to be determined in future studies.

You did not mean it: Perceived good intentions alleviate sense of unfairness

Dissociable medial frontal negativities from a common monitoring system for self- and externally caused failure of goal achievement

Impaired social cognition in schizophrenia during the Ultimatum Game: An EEG study

Outcome evaluations in group decision-making using authority rule: An electrophysiological study

Increased perseverative errors following high-definition transcranial direct current stimulation over the ventrolateral cortex during probabilistic reversal learning

Reduced risk avoidance and altered neural correlates of feedback processing in patients with borderline personality disorder

Losses and errors often slow down subsequent reaction times (RTs). This is classically explained in terms of a shift towards more cautious, therefore slow, behaviour. Recent studies of gambling, however, reported faster RTs following losses, so-called post-loss speeding, often attributing these to behavioural impulsivity arising from frustration. Here we instead investigated post-loss speeding in the context of a task that allowed behavioural adaptation and learning, namely probabilistic reversal learning (PRL). We additionally used electroencephalography (EEG) to investigate how losses influence subsequent markers of action generation (readiness potential [RP]) and outcome evaluation (feedback-related negativity [FRN] and P300). Our results confirm faster RTs after losses than after wins in PRL, thus extending post-loss speeding from gambling to cognitive contexts where learning is possible. Previous losses did not affect subsequent RP amplitudes. However, compared to wins, previous losses led to more positive FRN and more positive P300 amplitudes elicited by subsequent outcomes. Furthermore, faster RTs were associated with more negative FRN amplitudes irrespective of previous or outcome valence. We hypothesise that post-loss speeding in PRL may represent a form of signal chasing, allowing participants to behaviourally modulate neurophysiological responses and thereby potentially establish agency by influencing internal neurophysiological signals.