Punishment sensitivity modulates the processing of negative feedback but not error-induced learning

Abstract

Accumulating evidence suggests that individual differences in punishment and reward sensitivity are associated with functional alterations in neural systems underlying error and feedback processing. In particular, individuals highly sensitive to punishment have been found to be characterized by larger mediofrontal error signals as reflected in the error negativity/error-related negativity (Ne/ERN) and the feedback-related negativity (FRN). By contrast, reward sensitivity has been shown to relate to the error positivity (Pe). Given that Ne/ERN, FRN, and Pe have been functionally linked to flexible behavioral adaptation, the aim of the present research was to examine how these electrophysiological reflections of error and feedback processing vary as a function of punishment and reward sensitivity during reinforcement learning. We applied a probabilistic learning task that involved three different conditions of feedback validity (100%, 80%, and 50%). In contrast to prior studies using response competition tasks, we did not find reliable correlations between punishment sensitivity and the Ne/ERN. Instead, higher punishment sensitivity predicted larger FRN amplitudes, irrespective of feedback validity. Moreover, higher reward sensitivity was associated with a larger Pe. However, only reward sensitivity was related to better overall learning performance and higher post-error accuracy, whereas highly punishment sensitive participants showed impaired learning performance, suggesting that larger negative feedback-related error signals were not beneficial for learning or even reflected maladaptive information processing in these individuals. Thus, although our findings indicate that individual differences in reward and punishment sensitivity are related to electrophysiological correlates of error and feedback processing, we found less evidence for influences of these personality characteristics on the relation between performance monitoring and feedback-based learning.

Reward and punishment hyposensitivity in problem gamblers: A study of event-related potentials using a principal components analysis

“…The current study also failed to find a correlation between FRN amplitude following Losses and ratings of punishment sensitivity, as indicated by BIS scores, in either the PG or HC group, which is in contrast to previous research that examined this relationship using traditional ERP quantification methods (Balconi and Crivelli, 2010;De Pascalis et al, 2010;Santesso et al, 2011;Unger et al, 2012;Van den Berg et al, 2011). This was perhaps due to the fact that the relationship between the FRN and BIS scores was only quantified at Fz in the current study, and not at fronto-central (Santesso et al, 2011;Unger et al, 2012), central (De Pascalis et al, 2010), or centro-posterior (Balconi and Crivelli, 2010) sites, as in prior studies.…”

“…Impulsivity has been found to be strongly associated with problem gambling (see van Holst et al, 2010 for a review); however, the few studies that have investigated self-reported sensitivity to reward and punishment in problem gamblers have reported mixed results (Goudriaan et al, 2006;Loxton et al, 2008). Research on the relationship between individual differences in reward and punishment sensitivity and psychophysiological indicators of incentive processing in healthy controls has shown individuals who score higher on self-reported punishment sensitivity measures also display higher FRN amplitudes following unfavourable feedback (Balconi and Crivelli, 2010;De Pascalis et al, 2010;Santesso et al, 2011;Sato et al, 2005;Unger et al, 2012), and that individuals who report higher reward sensitivity also demonstrate greater P300 amplitudes following positive feedback (Van den Berg et al, 2011); however, this relationship has not been examined in problem gamblers. Due to the potential of using self-report measures as screening instruments in the identification of individuals at risk of problem gambling, it is worthwhile examining whether these subjective measures correlate with objective neural responses.…”

Spared internal but impaired external reward prediction error signals in major depressive disorder during reinforcement learning

“…We used a probabilistic learning task previously devised by Eppinger et al (2008) and used by Bakic, Jepma, De Raedt, and Pourtois (2014)), as well as by Unger et al (2012). After a fixation cross of 250 ms duration, and a blank screen (250 ms), a visual stimulus (S) was presented for 500 ms on each trial against a white homogenous background on a 17-inch computer screen.…”

“…In this study, we tested a well-defined cohort of treatment resistant MDD patients (with high level of anhedonia) and compared their learning performance and RPE signals (using conventional EEG/ERP methods) during a probabilistic learning task (Eppinger, Kray, Mock, & Mecklinger, 2008;Unger, Heintz, & Kray, 2012) to a group of age and education level matched healthy controls (HCs). We assessed if MDD could impair internal (ERN) and/or external (FRN) RPE signals, and whether it would be associated with decreased RL (at the behavioral level) compared to HCs in this task (Pizzagalli et al, 2009).…”

Factors mediating performance monitoring in humans—from context to personality

“…In a comment to this study, Tops and Koole (2012) extended the discussion of the findings arguing that traits related to higher task engagement predict ERN amplitude. Unger et al (2012), on the other hand, reported a positive association between higher punishment sensitivity and higher FRN amplitudes, independent of feedback validity, which at the same time appeared to be related to poorer behavioral learning performance.…”