Electrophysiological correlates of confidence differ across correct and erroneous perceptual decisions

Abstract

Every decision we make is accompanied by an estimate of the likelihood that our decision is accurate or appropriate. This likelihood 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. 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. We additionally show that some previously reported associations between decision confidence and CPP/Pe component amplitudes are (at least partly) a consequence of ERP amplitude measurement-related confounds.

Confidence is predicted by pre- and post-choice decision signal dynamics

“…Thus far, only a few studies have directly investigated the CPP’s relationship with confidence and these have yielded apparently mixed results. While several studies have reported positive relationships between pre-choice CPP amplitude and confidence (Davidson et al, 2021; Gherman & Philiastides, 2015, 2018; Herding et al, 2019; Pereira et al, 2021; Tagliabue et al, 2019), two studies found no such relationship (Feuerriegel et al, 2022; Rausch et al, 2020).…”

“…Elsewhere, it has been reported that a post-choice Centro-parietal signal with identical topography to the CPP, but traditionally labelled as the Error Positivity (Pe), also scales with choice confidence but in the opposite direction to that reported for the pre-choice CPP. The Pe is seen after erroneous choices that are explicitly reported to be incorrect (Falkenstein, 1990; Nieuwenhuis et al, 2001; Steinhauser & Yeung, 2010), and its amplitude increases the more certain participants are that they have made an error (Boldt & Yeung, 2015; Feuerriegel et al, 2022). The Pe also exhibits a build-to-threshold relationship with error signalling reports (Murphy et al, 2015), and predicts subsequent post-error slowing and post-choice information-seeking (Desender, Boldt, et al, 2019; Desender, Murphy, et al, 2019).…”

“…To our knowledge, there has not been a direct comparison of the post-commitment dynamics of neural evidence accumulation signals with versus without continued evidence presentation. Additionally, recent work has highlighted that the use of baseline correction to a time before just before the initial response may have caused pre-choice amplitude differences to be transferred to post-choice amplitude measurements (Feuerriegel et al, 2022). Finally, this previous work has not considered the important influence that optional stopping could have on trial-averaged signal amplitude measurements and their interpretation.…”

The relationship between response dynamics and the formation of confidence varies across the lifespan

“…In order to understand the age-related decline in metacognitive performance, it is essential to understand the basic mechanisms underlying the computation of confidence. It is still unclear which information is used to compute confidence, and how input from different sources is weighted ( Charles and Yeung, 2019 ; Feuerriegel et al, 2021 ). For instance, confidence has been related to the strength of stimulus evidence, stimulus discriminability ( Yeung and Summerfield, 2012 ; Charles and Yeung, 2019 ; Turner et al, 2021b ), or instructed time pressure ( Vickers and Packer, 1982 ).…”

The relationship between response dynamics and the formation of confidence varies across the lifespan

“…In order to understand the age-related decline in metacognitive performance, it is essential to understand the basic mechanisms underlying the computation of confidence. It is still unclear which information is used to compute confidence, and how input from different sources is weighted (Charles and Yeung, 2019; Feuerriegel et al, 2021). For instance, confidence has been related to the strength of stimulus evidence, stimulus discriminability (Charles and Yeung, 2019; Turner et al, 2021b; Yeung and Summerfield, 2012), or instructed time pressure (Vickers and Packer, 1982).…”