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Subjective confidence reflects representation of Bayesian probability in cortex
Open accessPublished version of a preprint
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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Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250
The Neural Basis of Decision Making
Gold, J. I., & Shadlen, M. N. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113038 · Cited by 3,764
Permutation inference for the general linear model
Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.060 · Cited by 3,563
SUSAN—a new approach to low level image processing
Smith, S. M., & Brady, J. M. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007963824710 · Cited by 3,333
Research works printed but not linked: 4
- Green, D. M. & Swets, J. A. Signal Detection Theory and Psychophysics (Wiley, 1966).
- Kleiner, M., Brainard, D. H. & Pelli, D. G. What’s new in Psychtoolbox-3? Perception 36 (Suppl.), 14 (2007).
- Hedges, L. V. & Olkin, I. Statistical Methods for Meta-analysis (Academic Press, 1985).
- Fieller, E. C. & Pearson, E. S. Tests for rank correlation coefficients: II. Biometrika 48, 29–40 (1961).
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Items 101–104 of 104
Time-resolved decoding of uncertainty about stimulus features from human EEGPreprint
Nestor, J., Tian, K. J., Chapman, A. F., & Denison, R. N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.08.750188
Tsapos, M., Tjøstheim, T. A., Ekström, A. G., & Stephens, A. (2026) · Synthese · doi:10.1007/s11229-026-05786-5
Dynamic Reduction of Neural Uncertainty Shapes Perceptual Decisions in a Bayes-Optimal Manner
Rangelov, D., Bitzer, S., & Mattingley, J. B. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.1026-25.2026
Optimisation UncertaintyPreprint
Bao, T., & Pei, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7619399
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
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