Figure 1.

Schematic showing the theoretical dissociation between metacognitive sensitivity and bias. Each graph shows a hypothetical probability density of confidence ratings for correct and incorrect trials, with confidence increasing from left to right along each x-axis. Metacognitive sensitivity is the separation between the distributions—the extent to which confidence discriminates between correct and incorrect trials. Metacognitive bias is the overall level of confidence expressed, independent of whether the trial is correct or incorrect. Note that this is a cartoon schematic and we do not mean to imply any parametric form for these “Type 2” signal detection theoretic distributions. Indeed, as shown by Galvin et al. (2003), these distributions are unlikely to be Gaussian.