RT Journal Article
SR Electronic
T1 Subjective confidence reflects representation of Bayesian probability in cortex
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.04.10.439272
DO 10.1101/2021.04.10.439272
A1 Geurts, Laura S.
A1 Cooke, James R. H.
A1 van Bergen, Ruben S.
A1 Jehee, Janneke F. M.
YR 2021
UL http://biorxiv.org/content/early/2021/04/10/2021.04.10.439272.abstract
AB What gives rise to the human sense of confidence? Here, we tested the Bayesian hypothesis that confidence is based on a probability distribution represented in neural population activity. We implemented several computational models of confidence, and tested their predictions using psychophysics and fMRI. Using a generative model-based fMRI decoding approach, we extracted probability distributions from neural population activity in human visual cortex. We found that subjective confidence tracks the shape of the decoded distribution. That is, when sensory evidence was more precise, as indicated by the decoded distribution, observers reported higher levels of confidence. We furthermore found that neural activity in the insula, anterior cingulate, and prefrontal cortex was linked to both the shape of the decoded distribution and reported confidence, in ways consistent with the Bayesian model. Altogether, our findings support recent statistical theories of confidence and suggest that probabilistic information guides the computation of one’s sense of confidence.Competing Interest StatementThe authors have declared no competing interest.