The confidence-noise confidence-boost (CNCB) model of confidence rating data.

ABSTRACT: Over the last decade, different approaches have been proposed to interpret confidence rating judgments obtained after perceptual decisions. One very popular approach is to compute meta-d' which is a global measure of the sensibility to discriminate the confidence rating distributions for correct and incorrect perceptual decisions. Here, we propose a generative model of confidence based on two main parameters, confidence noise and confidence boost, that we call CNCB model. Confidence noise impairs confidence judgements above and beyond how sensory noise affects perceptual sensitivity. The confidence boost parameter reflects whether confidence uses the same information that was used for perceptual decisions, or some new information. This CNCB model offers a principled way to estimate a confi

SUBMITTER: Mamassian P 

PROVIDER: S-EPMC12043244 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature