Summary

The human brain processes noisy information to help make adaptive choices under uncertainty. Accompanying these decisions about incoming evidence is a sense of confidence: a feeling about whether a decision is correct. Confidence typically covaries with the accuracy of decisions, in that higher confidence is associated with higher decisional accuracy. In the laboratory, decision confidence is typically measured by asking participants to make judgments about stimuli or information (type 1 judgments) and then to rate their confidence on a rating scale or by engaging in wagering (type 2 judgments). The correspondence between confidence and accuracy can be quantified in a number of ways, some based on probability theory and signal detection theory. But decision confidence does not always reflect only the probability that a decision is correct; confidence can also reflect many other factors, including other estimates of noise, evidence magnitude, nearby decisions, decision time, and motor movements. Confidence is thought to be computed by a number of brain regions, most notably areas in the prefrontal cortex. And, once computed, confidence can be used to drive other behaviors, such as learning rates or social interaction.