An automatic domain-general error signal is shared across tasks and predicts confidence in different sensory modalities

Abstract

Understanding the ability to self-evaluate decisions is an active area of research. This research has primarily focused on the neural correlates of self-evaluation during visual-tasks, and whether pre- or post-decisional neural correlates capture subjective confidence in that decision. This focus has been useful, yet also precludes an investigation of key every-day features of metacognitive self-evaluation: that decisions are rapid, must be evaluated without explicit feedback, and unfold in a multisensory world. These considerations lead us to hypothesise that an automatic domain-general metacognitive signal may be shared between sensory modalities, which we tested in the present study with multivariate decoding of electroencephalographic (EEG) data. Participants (N=21, 12 female) first performed a visual task with no request for self-evaluations of performance, prior to an auditory task that included rating decision confidence on each trial. A multivariate classifier trained to predict errors in the speeded visual-task generalised to predict errors in the subsequent non-speeded auditory discrimination. This generalisation was unique to classifiers trained on the visual response-locked data, and further predicted subjective confidence on the subsequent auditory task. This evidence of overlapping neural activity across the two tasks provides evidence for automatic encoding of confidence independent of any explicit request for metacognitive reports, and a shared basis for metacognitive evaluations across sensory modalities.