Neural Coding of Uncertainty and Probability

Prospect Theory: An Analysis of Decision under Risk

Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524

Prospect theory: An analysis of decision under risk

Kahneman, D. J., & Tversky, A. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511609220.014 · Cited by 32,720

Advances in Neural Information Processing Systems 25

Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653

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Signal detection theory and psychophysics

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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

Noise in the nervous system

Faisal, A. A., Selen, L. P. J., & Wolpert, D. M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2258 · Cited by 2,883

A framework for studying the neurobiology of value-based decision making

Rangel, A., Camerer, C., & Montague, P. R. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2357 · Cited by 2,184

Discrete coding of reward probability and uncertainty by dopamine neurons

Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003) · Science · doi:10.1126/science.1077349 · Cited by 2,085

Learning the value of information in an uncertain world

Behrens, T. E. J., Woolrich, M. W., Walton, M. E., & Rushworth, M. F. S. (2007) · Nature Neuroscience · doi:10.1038/nn1954 · Cited by 2,053

The Neurobiology of Confidence: From Beliefs to NeuronsPreprint

Ott, T., Masset, P., & Kepecs, Á. (2018) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2018.83.038794 · Cited by 17

Re-thinking the fixed-criterion model of perceptual decision-makingPreprint

Lee, J. L., Denison, R. N., & Ma, W. J. (2021) · doi:10.31234/osf.io/ys8mb · Cited by 18

Uncertainty-based inference of a common cause for body ownershipPreprint

Chancel, M., Ehrsson, H. H., & Ma, W. J. (2021) · doi:10.31219/osf.io/yh2z7 · Cited by 19

How the brain controls decision making in a multisensory world

Fetsch, C. R., & Noppeney, U. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2022.0332 · Cited by 17

Models of Vestibular Semi-Circular Canal Afferent Neuron Firing Activity.

Paulin, M., & Hoffman, L. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00087.2019 · Cited by 18

Expressions for Bayesian confidence of drift diffusion observers in fluctuating stimuli tasks

Calder-Travis, J., Bogacz, R., & Yeung, N. (2023) · Journal of Mathematical Psychology · doi:10.1101/2020.02.25.965384 · Cited by 19

Circular inference in bistable perception

Leptourgos, P., Notredame, C.-É., Eck, M., Jardri, R., & Denève, S. (2020) · Journal of Vision · doi:10.1167/jov.20.4.12 · Cited by 24

Investigating the representation of uncertainty in neuronal circuits

Dehaene, G., Coen-Cagli, R., & Pouget, A. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008138 · Cited by 18

Standard Tone Stability as a Manipulation of Precision in the Oddball Paradigm: Modulation of Prediction Error Responses to Fixed-Probability Deviants

SanMiguel, I., Costa‐Faidella, J., Lugo, Z., Vilella, E., & Escera, C. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.734200 · Cited by 16

Correlates of Perceptual Orientation Biases in Human Primary Visual Cortex

Patten, M. L. W., Mannion, D. J., & Clifford, C. W. G. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3511-16.2017 · Cited by 18

Understanding multivariate brain activity: Evaluating the effect of voxelwise noise correlations on population codes in functional magnetic resonance imaging

Zhang, R., Wei, X.-X., & Kay, K. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008153 · Cited by 17

What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception

Tanrıkulu, Ö. D., Четвериков, А. А., Hansmann-Roth, S., & Kristjansson, A. K. (2021) · Cognition · doi:10.1016/j.cognition.2021.104903 · Cited by 16

Validating model-based Bayesian integration using prior–cost metamers

Sohn, H., & Jazayeri, M. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2021531118 · Cited by 18

Neural basis of concurrent deliberation toward a choice and confidence judgment

Vivar-Lazo, M., & Fetsch, C. R. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02116-9 · Cited by 22

Perceived variability reflects the reliability of individual items

Jeong, J., & Chong, S. C. (2021) · Vision Research · doi:10.1016/j.visres.2021.02.008 · Cited by 15

A normative model of peripersonal space encoding as performing impact prediction

Straka, Z., Noel, J., & Hoffmann, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010464 · Cited by 14

Human confidence judgments reflect reliability-based hierarchical integration of contextual information

Schustek, P., Hyafil, A., & Moreno‐Bote, R. (2019) · Nature Communications · doi:10.1038/s41467-019-13472-z · Cited by 13

The role of sensory uncertainty in simple contour integration

Zhou, Y., Acerbi, L., & Ma, W. J. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006308 · Cited by 14

Gated recurrence enables simple and accurate sequence prediction in stochastic, changing, and structured environments

Foucault, C., & Meyniel, F. (2021) · eLife · doi:10.7554/elife.71801 · Cited by 16

Towards a cross-level understanding of Bayesian inference in the brain

Lin, C., & Garrido, M. I. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104649 · Cited by 18

Optimal multisensory integration leads to optimal time estimation

Murai, Y., & Yotsumoto, Y. (2018) · Scientific Reports · doi:10.1038/s41598-018-31468-5 · Cited by 14

Bayesian confidence in optimal decisionsPreprint

Calder-Travis, J. M., Charles, L., Bogacz, R., & Yeung, N. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/j8sxz · Cited by 14

Divisively normalized neuronal processing of uncertain visual feedback for visuomotor learning

Makino, Y., Hayashi, T., & Nozaki, D. (2023) · Communications Biology · doi:10.1038/s42003-023-05578-4 · Cited by 18

Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning

Bennett, D., Sasmita, K., Maloney, R. T., Murawski, C., & Bode, S. (2019) · Psychophysiology · doi:10.1111/psyp.13431 · Cited by 14

Sampling-based causal inference in cue combination and its neural implementation

Yu, Z., Chen, F., Dong, J., & Dai, Q. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.10.045 · Cited by 12

Confidence Modulates the Conformity Behavior of the Investors and Neural Responses of Social Influence in Crowdfunding

Zheng, J., Hu, L., Li, L., Shen, Q., & Wang, L. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.766908 · Cited by 13

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Egger, S. W., & Jazayeri, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-30722-0 · Cited by 13

Belief states and categorical-choice biases determine reward-based learning under perceptual uncertaintyPreprint

Bruckner, R., Heekeren, H. R., & Ostwald, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.18.303495 · Cited by 12

Neural mechanisms of resource allocation in working memory

Li, H.-H., Sprague, T. C., Yoo, A. H., Ma, W. J., & Curtis, C. E. (2025) · Science Advances · doi:10.1126/sciadv.adr8015 · Cited by 12

Modality independent or modality specific? Common computations underlie confidence judgements in visual and auditory decisions

West, R. K., Harrison, W. J., Matthews, N. L., Mattingley, J. B., & Sewell, D. K. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011245 · Cited by 12

A dynamic neural field model of continuous input integration

Wojtak, W., Coombes, S., Avitabile, D., Bicho, E. G., & Erlhagen, W. (2021) · Biological Cybernetics · doi:10.1007/s00422-021-00893-7 · Cited by 11

Illusions, Delusions, and Your Backwards Bayesian Brain: A Biased Visual Perspective

Born, R. T., & Bencomo, G. (2020) · Brain Behavior and Evolution · doi:10.1159/000514859 · Cited by 12

Learning nonnative speech sounds changes local encoding in the adult human cortex

Yi, H., Chandrasekaran, B., Nourski, K. V., Rhone, A. E., Schuerman, W. L., Howard, M. A., Chang, E. F., & Leonard, M. K. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2101777118 · Cited by 13

Audiovisual simultaneity windows reflect temporal sensory uncertainty

Cary, E., Lahdesmaki, I., & Badde, S. (2024) · Psychonomic Bulletin & Review · doi:10.3758/s13423-024-02478-4 · Cited by 14

Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation

Zheng, Y., Jia, S., Yu, Z., Huang, T., Liu, J. K., & Tian, Y. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.03.003 · Cited by 10

The case against full probability distributions in perceptual decision makingPreprint

Rahnev, D. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/108944 · Cited by 12

Perception is rich and probabilistic

Jabar, S. B., & Fougnie, D. L. (2022) · Scientific Reports · doi:10.1038/s41598-022-17458-8 · Cited by 8

Listening to the Data: Computational Approaches to Addiction and Learning

Wilkinson, C. S., Luján, M. Á., Hales, C. A., Costa, K. M., Fiore, V. G., Knackstedt, L. A., & Hedy Kober, A. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1415-23.2023 · Cited by 13

Motivation: A Valuation Systems Perspective

Uusberg, A., Suri, G., Dweck, C. S., & Gross, J. J. (2019) · Nebraska Symposium on Motivation/The Nebraska symposium on motivation · doi:10.1007/978-3-030-27473-3_6 · Cited by 10

An insula‐driven network computes decision uncertainty and promotes abstinence in chronic cocaine users

Yu, J., Fiore, V. G., Briggs, R. W., Braud, J., Rubia, K., Adinoff, B. H., & Gu, X. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14917 · Cited by 12

A characterization of the neural representation of confidence during probabilistic learning

Bounmy, T., Eger, E., & Meyniel, F. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2022.119849 · Cited by 16

Introspective inference counteracts perceptual distortion

Mihali, A., Broeker, M. D., Ragalmuto, F. D. M., & Horga, G. (2023) · Nature Communications · doi:10.1038/s41467-023-42813-2 · Cited by 9

Metacognition in the audiovisual McGurk illusion: perceptual and causal confidence

Meijer, D., & Noppeney, U. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2022.0348 · Cited by 10

The influence of polymodality of reflection on personality self-organization

Sizikova, T. E. (2019) · Science for Education Today · doi:10.15293/2658-6762.1901.04 · Cited by 9

Task-induced neural covariability as a signature of approximate Bayesian learning and inferencePreprint

Lange, R. D., & Haefner, R. M. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/081661 · Cited by 9

Normative decision rules in changing environments

Barendregt, N. W., Gold, J. I., Josić́, K., & Kilpatrick, Z. P. (2022) · eLife · doi:10.7554/elife.79824 · Cited by 8

An FPGA implementation of Bayesian inference with spiking neural networks

Li, H., Wan, B., Fang, Y. G., Li, Q., Liu, J. K., & An, L. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1291051 · Cited by 10

Unification of MAP Estimation and Marginal Inference in Recurrent Neural Networks

Yu, Z., Chen, F., & Deng, F. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2805813 · Cited by 7

Information seeking mechanism of neural populations in the lateral prefrontal cortex

Nakamura, K., & Komatsu, M. (2018) · Brain Research · doi:10.1016/j.brainres.2018.11.029 · Cited by 7

Sampling-Tree Model: Efficient Implementation of Distributed Bayesian Inference in Neural Networks

Yu, Z., Chen, F., & Liu, J. K. (2019) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2019.2927808 · Cited by 8

Systematic and Bibliometric Review of Neuroeconomics and Neurofinance Research: Current Status, Thematic Trends, and Future Directions

Bayramoğlu, G., & Öztürk, O. (2024) · Journal of Economic Surveys · doi:10.1111/joes.12676 · Cited by 8

Metacognitive judgments during visuomotor learning reflect the integration of error history

Hewitson, C. L., Al-Fawakhiri, N., Forrence, A. D., & McDougle, S. D. (2023) · Journal of Neurophysiology · doi:10.1152/jn.00022.2023 · Cited by 7

Using the perceptual past to predict the perceptual future influences the perceived present – A novel ERP paradigm

Joos, E., Giersch, A., Bhatia, K., Heinrich, S. P., van Elst, L. T., & Kornmeier, J. (2020) · PLoS ONE · doi:10.1371/journal.pone.0237663 · Cited by 9

Sensory Island Task (SIT): A New Behavioral Paradigm to Study Sensory Perception and Neural Processing in Freely Moving Animals

Ferreiro, D. N., Amaro, D., Schmidtke, D., Sobolev, A., Gundi, P., Belliveau, L., Sirota, A., Grothe, B., & Pecka, M. (2020) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2020.576154 · Cited by 7

Interpreting Dynamical Systems as Bayesian Reasoners

Virgo, N., Biehl, M., & McGregor, S. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-93736-2_52 · Cited by 7

Sure enough: efficient Bayesian learning and choice

Foley, B. R., & Marjoram, P. (2017) · Animal Cognition · doi:10.1007/s10071-017-1107-5 · Cited by 8

A change of mind: Globus pallidus activity and effective connectivity during changes in choice selections

Fiore, V. G., Guertler, A. V., Yu, J., C.Tatineni, C., & Gu, X. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15142 · Cited by 7

Arbitrary Conditional Distributions with EnergyPreprint

Strauss, R. R., & Oliva, J. B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.04426 · Cited by 7

Expressions for Bayesian confidence of drift diffusion observers in dynamic stimuli tasksPreprint

Calder-Travis, J. M., Bogacz, R., & Yeung, N. (2020) · doi:10.17605/osf.io/tk3vp · Cited by 8

The energy metabolic footprint of predictive processing in the human brainPreprint

Hechler, A., de Lange, F. P., & Riedl, V. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.08.570804 · Cited by 8

Learning to integrate parts for whole through correlated neural variability

Zhu, Z., Qi, Y., Lu, W., & Feng, J. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012401 · Cited by 7

Population activity statistics dissect subthreshold and spiking variability in V1

Bányai, M., Koman, Z., & Orbán, G. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00931.2016 · Cited by 6

An observer model of tilt perception, sensitivity and confidence

Arnold, D. H., Saurels, B. W., Anderson, N. L., & Johnston, A. (2021) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2021.1276 · Cited by 6

Theoretical Models of Health Behavior

McDowell, I. (2023) · Springer eBooks · doi:10.1007/978-3-031-28986-6_6 · Cited by 7

Neural correlates of valence-dependent belief and value updating during uncertainty reduction: An fNIRS study

Peng, X.-R., Bundil, I., Schulreich, S., & Li, S. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120327 · Cited by 7

Modeling confidence in causal judgments.

O’Neill, K. J., Henne, P., Pearson, J., & Brigard, F. D. (2024) · Journal of Experimental Psychology General · doi:10.1037/xge0001615 · Cited by 6

Attractor dynamics of working memory explain a concurrent evolution of stimulus-specific and decision-consistent biases in visual estimation

Gu, H., Lee, J., Kim, S., Lim, J., Lee, H.-J., Lee, H., Choe, M. J., Yoo, D.-G., Ryu, J. H., Lim, S., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.07.003 · Cited by 7

The virtual loss function in the summary perception of motion and its limited adjustability

Teng, T., Li, S., & Zhang, H. (2021) · Journal of Vision · doi:10.1167/jov.21.5.2 · Cited by 7

Late Bayesian inference in sensorimotor behaviorPreprint

Remington, E. D., & Jazayeri, M. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/130062 · Cited by 6

An uncertainty-based model of the effects of fixation on choicePreprint

Li, Z., & Ma, W. J. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/ajmwx · Cited by 5

Are we really Bayesian? Probabilistic inference shows sub-optimal knowledge transfer

Lin, C., Do, T. T., Unsworth, L., & Garrido, M. I. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011769 · Cited by 6

Representation of a perceptual bias in the prefrontal cortex

Serrano-Fernández, L., Beirán, M., Romo, R., & Parga, N. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2312831121 · Cited by 5

The neural basis for uncertainty processing in hierarchical decision making

Wang, M. B., Lynch, N., & Halassa, M. M. (2025) · Nature Communications · doi:10.1038/s41467-025-63994-y · Cited by 9

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

Neville, V., Mendl, M., Paul, E. S., Seriès, P., & Dayan, P. (2023) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-023-01137-w · Cited by 5

Instance-based generalization for human judgments about uncertainty

Schustek, P., & Moreno‐Bote, R. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006205 · Cited by 9

The role of familiarity in signaller–receiver interactions

Ma, W. J., & Higham, J. P. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0568 · Cited by 4

Neural variability in the default mode network compresses with increasing belief precision during Bayesian inference

Skowron, A., Kosciessa, J. Q., Lorenz, R. C., Hertwig, R., van den Bos, W., & Garrett, D. D. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf219 · Cited by 4

Computational elements of natural vision

Rothkopf, C. A., & Hayhoe, M. (2025) · Journal of Vision · doi:10.1167/jov.25.12.4 · Cited by 4

The representational instability in the generalization of fear learning

Yu, K., Vanpaemel, W., Tuerlinckx, F., & Zaman, J. (2024) · npj Science of Learning · doi:10.1038/s41539-024-00287-x · Cited by 4

Priors for natural image statistics inform confidence in perceptual decisions

West, R. K., A-Izzeddin, E. J., Sewell, D. K., & Harrison, W. J. (2025) · Consciousness and Cognition · doi:10.1016/j.concog.2025.103818 · Cited by 4

Representing Probability in Perception and Experience

Lee, G., & Orlandi, N. (2022) · Review of Philosophy and Psychology · doi:10.1007/s13164-022-00647-9 · Cited by 4

Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations

Genewein, T., & Braun, D. A. (2016) · Biological Cybernetics · doi:10.1007/s00422-016-0684-8 · Cited by 4

The role of sensory uncertainty in simple contour integrationPreprint

Zhou, Y., Acerbi, L., & Ma, W. J. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/350082 · Cited by 3

Neural variability compresses with increasing belief precision during Bayesian inferencePreprint

Skowron, A., Kosciessa, J. Q., Lorenz, R. C., Hertwig, R., van den Bos, W., & Garrett, D. D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.11.575180 · Cited by 4

Antifragile control systems in neuronal processing: a sensorimotor perspective

Axenie, C. (2025) · Biological Cybernetics · doi:10.1007/s00422-025-01003-7 · Cited by 4

Bayesian prior uncertainty and surprisal elicit distinct neural patterns during sound localization in dynamic environments

Bayram, B., Meijer, D., Barumerli, R., Spierings, M. J., Baumgartner, R., & Pomper, U. (2025) · Scientific Reports · doi:10.1038/s41598-025-90269-9 · Cited by 3

Adaptive reward representations integrate expected uncertainty signals in orbitofrontal cortex

Zhang, Q., & Zhou, J. (2025) · Science Advances · doi:10.1126/sciadv.adv9590 · Cited by 3

Humans optimally integrate cutaneous and proprioceptive cues in haptic size perception

Allen, K. S., & Goldreich, D. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1653390 · Cited by 2

Evidence for Spinozan “Unbelieving” in the Right Inferior Prefrontal Cortex

Bernhard, R. M., Frankland, S., Plunkett, D., Sievers, B., & Greene, J. D. (2023) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01964 · Cited by 5

Humans use underestimates of auditory spatial and temporal uncertainty for perceptual inference

Hong, F., Xu, J., Landy, M. S., & Badde, S. (2025) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2024.2880 · Cited by 4

Beyond von Neumann: Brain-computer structural metaphor

Otoom, M. (2016) · International Conference on Electrical, Electronics, Computer Engineering and their Applications (EECEA) · doi:10.1109/eecea.2016.7470764 · Cited by 3

A Radically New Theory of How the Brain Represents and Computes with Probabilities

Rinkus, G. J. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53966-4_34 · Cited by 3

How the known reference weakens the visual oblique effect: a Bayesian account of cognitive improvement by cue influence

Ye, R., & Liu, X. (2020) · Scientific Reports · doi:10.1038/s41598-020-76911-8 · Cited by 4

Stochastic satisficing account of confidence in uncertain value-based decisionsPreprint

Hertz, U., Bahrami, B., & Keramati, M. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/107532 · Cited by 3

Using the past to estimate sensory uncertaintyPreprint

Beierholm, U., Rohe, T., Ferrari, A., Stegle, O., & Noppeney, U. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/589275 · Cited by 3

Using a betting game to reveal the rich nature of visual working memoriesPreprint

Jabar, S. B., Sreenivasan, K. K., Lentzou, S., Kanabar, A., Brady, T. F., & Fougnie, D. L. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.28.357442 · Cited by 3

Similar network compositions, but distinct neural dynamics underlying belief updating in environments with and without explicit outcomes

Fiore, V. G., & Gu, X. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118821 · Cited by 2

Probabilistic and rich individual working memories revealed by a betting game

Jabar, S. B., Sreenivasan, K. K., Lentzou, S., Kanabar, A., Brady, T. F., & Fougnie, D. L. (2023) · Scientific Reports · doi:10.1038/s41598-023-48242-x · Cited by 5

From uncertainty and entropy to coherence and consciousness

Beshkar, M. (2025) · Brain‐X · doi:10.1002/brx2.70027 · Cited by 2

Linking neuroimaging signals to behavioral responses in single cases: C hallenges and opportunities

Sander, T. H., & Zhou, B. (2016) · PsyCh Journal · doi:10.1002/pchj.143 · Cited by 2

The Bayesian brain: The role of uncertainty in neural coding and computation

Knill, D. C., & Pouget, A. (2004) · Trends in Neurosciences · doi:10.1016/j.tins.2004.10.007 · Cited by 2,588

Knowing how much you don't know: a neural organization of uncertainty estimates

Bach, D. R., & Dolan, R. J. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3289 · Cited by 339

Decision-Making Under Uncertainty

Bach, D. (2016) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-642-35923-1_6

Sensory uncertainty decoded from visual cortex predicts behavior

van Bergen, R. S., Ma, W. J., Pratte, M. S., & Jehee, J. F. M. (2015) · Nature Neuroscience · doi:10.1038/nn.4150 · Cited by 235

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