Boldt, Annika; Desender, Kobe; (2023) Dis-confirmatory evidence drives confidence. In: 2023 Conference on Cognitive Computational Neuroscience. (pp. pp. 436-438). Cognitive Computational Neuroscience

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Abstract

Assessing one's own decisions is a crucial component of cognition, enabling adaptive behavior. According to normative models, the brain employs available evidence optimally to evaluate decisions. If decision confidence (judging the accuracy of a decision) were to be assessed, the normative strategy would involve giving equal weight to each sample. However, recent findings instead suggest that the brain tends to overweight decisioncongruent information when forming confidence judgements, a finding referred to as the "positiveevidence bias" (PEB). Here, we report the re-analysis of nine datasets involving human participants who judged the average color of eight shapes and rated their confidence in this decision. Our findings suggest that participants overly relied on evidence that conflicted with their choice, contrary to both the normative model and the PEB. We furthermore fitted a log-posterior-ratio (LPR) model to our data and show that our findings can instead be explained by a robust averaging principle.

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