Electrophysiological correlates of confidence differ across correct and erroneous perceptual decisions

Every decision we make is accompanied by an estimate of the probability that our decision is accurate or appropriate. This probability estimate is termed our degree of decision confidence. Recent work has uncovered event-related potential (ERP) correlates of confidence both during decision formation and after a decision has been made. However, the interpretation of these findings is complicated by methodological issues related to ERP amplitude measurement that are prevalent across existing studies. To more accurately characterise the neural correlates of confidence, we presented participants with a difficult perceptual decision task that elicited a broad range of confidence ratings. We identified a frontal ERP component within an onset prior to the behavioural response, which exhibited more positive-going amplitudes in trials with higher confidence ratings. This frontal effect also biased measures of the centro-parietal positivity (CPP) component at parietal electrodes via volume conduction. Amplitudes of the error positivity (Pe) component that followed each decision were negatively associated with confidence for trials with decision errors, but not for trials with correct decisions, with Bayes factors providing moderate evidence for the null in the latter case. We provide evidence for both pre- and post-decisional neural correlates of decision confidence that are observed in trials with correct and erroneous decisions, respectively. Our findings suggest that certainty in having made a correct response is associated with frontal activity during decision formation, whereas certainty in having committed an error is instead associated with the post-decisional Pe component. These findings also highlight the possibility that some previously reported associations between decision confidence and CPP/Pe component amplitudes may have been a consequence of ERP amplitude measurement-related confounds. Re-analysis of existing datasets may be useful to test this hypothesis more directly.