A single evidence accumulation process informs perceptual choices and subsequent confidence reports

How is the content of our decision making processes translated into subjective confidence? Current computational models designed to account for choice- and confidence-reporting behaviour disagree on two fundamental questions: do choice and confidence reports arise from shared versus distinct evaluation processes and what stopping-rule is applied to evidence sampling for confidence reports? Here, we employed a neurally-informed modelling approach in which competing models were compared both based on their fits to behaviour and their ability to recapitulate human electrophysiological signatures of evidence accumulation. Participants made self-paced confidence reports after indicating perceptual choices on a random dot motion task. Model comparison based on behavioural data alone showed that boundary-based stopping rules for confidence reporting provided superior fits than time-based stopping rules. However, results were inconclusive when comparing models with a single evidence accumulation process dictating choice and confidence reports compared to models invoking distinct processes. Importantly, the single-process model markedly outperformed the other models in its ability to account for the observed neural evidence accumulation patterns, including the fact that signal amplitudes predicted reported confidence several hundred milliseconds before the initial choice had been reported. Our study demonstrates that choice behaviour, subjective confidence, and associated neural decision signals can be jointly explained by a model invoking a single process of evidence accumulation with separate boundaries for the initial choice and subsequent confidence reports.