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Subjective confidence reflects representation of Bayesian probability in cortex
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Abstract
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 functional magnetic resonance imaging. Using a generative model-based decoding technique, 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.
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“They found that reported confidence was negatively correlated with such a readout of uncertainty, even when the stimulus was held fixed.”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Geurts et al. 2022
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“Finally, in the study by Geurts et al. (2022) described above, the decoder's readout of sensory uncertainty in early visual areas was correlated with univariate fMRI signals in prefrontal cortex, consistent with domain-specific uncertainty estimates informing globally available estimates of propositional confidence.”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Geurts et al. 2022
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Metadata
- Authors
- Geurts, L. S., Cooke, J. R. H., van Bergen, R. S., & Jehee, J. F. M.
- Affiliations
- Radboud University Nijmegen (NL)
- Corresponding author
- Jehee, Janneke F. M.
- Venue
- Nature Human Behaviour
- Published
- 2022-01-20
- Volume
- 6
- Issue
- 2
- Pages
- 294-305
- ISSN
- 2397-3374 (ISSN-L)
- PMC
- PMC7612428
- OpenAlex
- W4220816838
- Cited by
- 104
- References
- 77
- Citations by year
- 2026: 15 · 2025: 31 · 2024: 25 · 2023: 20 · 2022: 9
- FWCI
- 10.96
- Type
- journal article
- Language
- en
- Update notices
- correction (2022-03-09)
- Open access
- bronze
- doi.org
- Locations
- Nature Human Behaviour (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- subjective confidence, Bayesian probability, neural population activity, visual cortex, insula, anterior cingulate cortex, prefrontal cortex, confidence model, decision-making
- MeSH terms
- Bayes Theorem, Cerebral Cortex, Humans, Probability, Visual Cortex, Visual Perception
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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