The neural representation of unexpected uncertainty during value-based decision making
Open accessAbstract
Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled us to separately examine each form of uncertainty examined. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty, and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Deviations from expected uncertainty should increase learning rates.
“Here, deviations from expected uncertainty (“unexpected uncertainty”) should increase learning rates.8,12,13,15–18”
From Serotonin neurons modulate learning rate through uncertainty (2022) · cites this paper as [16]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913 · see citing works
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388 · see citing works
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122 · see citing works
Aston-Jones, G., & Cohen, J. D. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135709 · Cited by 4,472 · see citing works
Classical conditioning II: Current research and theory.
Black, A. H., & Prokasy, W. F. (1972) · Appleton-Century-Crofts eBooks · Cited by 4,449 · see citing works
Pearce, J. M., & Hall, G. (1980) · Psychological Review · doi:10.1037/0033-295x.87.6.532 · Cited by 3,023 · see citing works
Image matching as a diffusion process: an analogy with maxwell’s demons
Thirion, J.-P. (1998) · Medical Image Analysis · doi:10.1016/s1361-8415(98)80022-4 · Cited by 2,445 · see citing works
Cortical substrates for exploratory decisions in humans
Daw, N. D., O'Doherty, J. P., Dayan, P., Seymour, B., & Dolan, R. J. (2006) · Nature · doi:10.1038/nature04766 · Cited by 2,224 · see citing works
Self-citationDissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning
O'Doherty, J., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004) · Science · doi:10.1126/science.1094285 · Cited by 2,088 · see citing works
Self-citationA framework for mesencephalic dopamine systems based on predictive Hebbian learning
Montague, P., Dayan, P., & Sejnowski, T. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-05-01936.1996 · Cited by 2,066 · see citing works
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 · see citing works
Uncertainty, Neuromodulation, and Attention
Yu, A. J., & Dayan, P. (2005) · Neuron · doi:10.1016/j.neuron.2005.04.026 · Cited by 1,774 · see citing works
Neural systems responding to degrees of uncertainty in human decision-making
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005) · Science · doi:10.1126/science.1115327 · Cited by 1,411 · see citing works
Moore, R. Y., & Bloom, F. E. (1979) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.02.030179.000553 · Cited by 1,378 · see citing works
Tracking the Hemodynamic Responses to Reward and Punishment in the Striatum
Delgado, M. R., Nystrom, L. E., Fissell, C., Noll, D. C., & Fiez, J. A. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.6.3072 · Cited by 1,116 · see citing works
Functional connectivity of human striatum: a resting state FMRI study
Di Martino, A., Scheres, A., Margulies, D. S., Kelly, A. M. C., Uddin, L. Q., Shehzad, Z., Biswal, B., Walters, J. R., Castellanos, F. X., & Milham, M. P. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn041 · Cited by 1,090 · see citing works
Corbetta, M. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.3.831 · Cited by 995 · see citing works
Role of locus coeruleus in attention and behavioral flexibility
Aston-Jones, G., Rajkowski, J., & Cohen, J. (1999) · Biological Psychiatry · doi:10.1016/s0006-3223(99)00140-7 · Cited by 900 · see citing works
Orbitofrontal Cortex Encodes Willingness to Pay in Everyday Economic Transactions
Plassmann, H., O'Doherty, J., & Rangel, A. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.2131-07.2007 · Cited by 855 · see citing works
Self-citationOptimized EPI for fMRI studies of the orbitofrontal cortex
Deichmann, R., Gottfried, J. A., Hutton, C., & Turner, R. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00073-9 · Cited by 821 · see citing works
Network reset: a simplified overarching theory of locus coeruleus noradrenaline function
Bouret, S., & Sara, S. J. (2005) · Trends in Neurosciences · doi:10.1016/j.tins.2005.09.002 · Cited by 806 · see citing works
Human insula activation reflects risk prediction errors as well as risk
Preuschoff, K., Quartz, S. R., & Bossaerts, P. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4286-07.2008 · Cited by 784 · see citing works
Self-citationDissociable Neural Responses in Human Reward Systems
Elliott, R., Friston, K. J., & Dolan, R. J. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-16-06159.2000 · Cited by 740 · see citing works
Rational regulation of learning dynamics by pupil-linked arousal systems
Nassar, M. R., Rumsey, K. M., Wilson, R. C., Parikh, K., Heasly, B., & Gold, J. I. (2012) · Nature Neuroscience · doi:10.1038/nn.3130 · Cited by 722 · see citing works
Neural Signatures of Economic Preferences for Risk and Ambiguity
Huettel, S. A., Stowe, C. J., Gordon, E. M., Warner, B. T., & Platt, M. L. (2006) · Neuron · doi:10.1016/j.neuron.2006.01.024 · Cited by 713 · see citing works
Locus coeruleus neurons in monkey are selectively activated by attended cues in a vigilance task
Aston-Jones, G., Rajkowski, J., Kubiak, P., & Alexinsky, T. (1994) · The Journal of Neuroscience · doi:10.1523/jneurosci.14-07-04467.1994 · Cited by 637 · see citing works
Nassar, M. R., Wilson, R. C., Heasly, B. S., & Gold, J. I. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.0822-10.2010 · Cited by 564 · see citing works
Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making
Collins, A., & Koechlin, E. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001293 · Cited by 558 · cited 2× · see citing works
“A recent experimental study of behavioral adaptation in humans (Collins and Koechlin, 2012) suggests that after a contextual change, humans retrieve from their memory similar contexts experienced in the past and select the behavioral strategy that they previously learned to be optimal in that context.”
BackgroundPupil dilation signals surprise: evidence for noradrenaline’s role in decision making
Preuschoff, K. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00115 · Cited by 538 · see citing works
Determining the neural substrates of goal-directed learning in the human brain
Valentin, V. V., Dickinson, A., & O'Doherty, J. P. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.0564-07.2007 · Cited by 529 · see citing works
Self-citationHampton, A. N., Bossaerts, P., & O’Doherty, J. P. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1010-06.2006 · Cited by 498 · see citing works
Self-citationCarter, C. S., Mintun, M., & Cohen, J. D. (1995) · NeuroImage · doi:10.1006/nimg.1995.1034 · Cited by 474 · see citing works
Huettel, S. A., Song, A. W., & McCarthy, G. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.5070-04.2005 · Cited by 457 · see citing works
Frank, M. J., Doll, B. B., Oas-Terpstra, J., & Moreno, F. (2009) · Nature Neuroscience · doi:10.1038/nn.2342 · Cited by 452 · see citing works
Neural correlates of value, risk, and risk aversion contributing to decision making under risk
Christopoulos, G. I., Tobler, P. N., Bossaerts, P., Dolan, R. J., & Schultz, W. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2614-09.2009 · Cited by 451 · see citing works
Self-citationBouret, S., & Sara, S. J. (2004) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2004.03526.x · Cited by 371 · see citing works
4 T-fMRI Study of Nonspatial Shifting of Selective Attention: Cerebellar and Parietal Contributions
Le, T. H., Pardo, J. V., & Hu, X. P. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.3.1535 · Cited by 361 · see citing works
Arnsten, A. F. T., & Goldman-Rakic, P. S. (1984) · Brain Research · doi:10.1016/0006-8993(84)90351-2 · Cited by 333 · see citing works
The role of the striatum in aversive learning and aversive prediction errors
Delgado, M. R., Li, J., Schiller, D., & Phelps, E. A. (2008) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2008.0161 · Cited by 328 · see citing works
Potent excitatory influence of prefrontal cortex activity on noradrenergic locus coeruleus neurons
Jodoj, E., Chiang, C., & Aston-Jones, G. (1998) · Neuroscience · doi:10.1016/s0306-4522(97)00372-2 · Cited by 321 · see citing works
In vivo mapping of the human locus coeruleus
Keren, N. I., Lozar, C., Harris, K. C., Morgan, P. S., & Eckert, M. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.012 · Cited by 309 · see citing works
Rostrolateral Prefrontal Cortex and Individual Differences in Uncertainty-Driven Exploration
Badre, D., Doll, B. B., Long, N. M., & Frank, M. J. (2012) · Neuron · doi:10.1016/j.neuron.2011.12.025 · Cited by 309 · see citing works
Visualization of Group Inference Data in Functional Neuroimaging
Gläscher, J. P. (2009) · Neuroinformatics · doi:10.1007/s12021-008-9042-x · Cited by 306 · see citing works
Haruno, M., Kuroda, T., Doya, K., Toyama, K., Kimura, M., Samejima, K., Imamizu, H., & Kawato, M. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.3417-03.2004 · Cited by 300 · see citing works
Rutishauser, U., Mamelak, A. N., & Schuman, E. M. (2006) · Neuron · doi:10.1016/j.neuron.2006.02.015 · Cited by 296 · see citing works
Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation
Cavanagh, J. F., y Figueroa, C. M. L. F., Cohen, M. X., & Frank, M. J. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr332 · Cited by 294 · see citing works
The Role of Human Orbitofrontal Cortex in Value Comparison for Incommensurable Objects
FitzGerald, T. H. B., Seymour, B., & Dolan, R. J. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.0717-09.2009 · Cited by 279 · see citing works
Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings
Payzan-LeNestour, E., & Bossaerts, P. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001048 · Cited by 267 · see citing works
Self-citationHahn, B., Ross, T. J., & Stein, E. A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.04.177 · Cited by 255 · see citing works
Yassa, M. A., & Stark, C. E. L. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.016 · Cited by 252 · see citing works
Aston‐Jones, G., Rajkowski, J., & Kubiak, P. (1997) · Neuroscience · doi:10.1016/s0306-4522(97)00060-2 · Cited by 227 · see citing works
McGaughy, J., Ross, R. S., & Eichenbaum, H. (2008) · Neuroscience · doi:10.1016/j.neuroscience.2008.01.064 · Cited by 226 · see citing works
Predicting events of varying probability: uncertainty investigated by fMRI
Volz, K. G., Schubotz, R. I., & von Cramon, D. Y. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00122-8 · Cited by 214 · see citing works
Activation of the noradrenergic system facilitates an attentional shift in the rat
Devauges, V., & Sara, S. J. (1990) · Behavioural Brain Research · doi:10.1016/0166-4328(90)90118-x · Cited by 202 · see citing works
Resolution of Uncertainty in Prefrontal Cortex
Yoshida, W., & Ishii, S. (2006) · Neuron · doi:10.1016/j.neuron.2006.05.006 · Cited by 196 · see citing works
Exploring the Nature of “Trader Intuition”
Bruguier, A., Quartz, S. R., & Bossaerts, P. L. (2010) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01591.x · Cited by 131 · see citing works
Self-citationDifferent Varieties of Uncertainty in Human Decision-Making
Bland, A. R., & Schaefer, A. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00085 · Cited by 126 · see citing works
The Known Unknowns: Neural Representation of Second-Order Uncertainty, and Ambiguity
Bach, D. R., Hulme, O. J., Penny, W. D., & Dolan, R. J. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1452-10.2011 · Cited by 106 · see citing works
Neural correlates of risk prediction error during reinforcement learning in humans
d'Acremont, M., Lu, Z.-L., Li, X., Van der Linden, M., & Bechara, A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.096 · Cited by 94 · see citing works
Prévost, C., McCabe, J. A., Jessup, R. K., Bossaerts, P. L., & O’Doherty, J. P. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07686.x · Cited by 56 · see citing works
Self-citationPayzan-LeNestour, É., & Bossaerts, P. L. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00150 · Cited by 54 · see citing works
Self-citationDiffeomorphic Demons Using ITK's Finite Difference Solver Hierarchy
Vercauteren, T. K., Pennec, X., Perchant, A., et al. (2008) · The Insight Journal · doi:10.54294/ux2obj · Cited by 49 · see citing works
Neural correlates of resolving uncertainty in driver's decision making
Callan, A. M., Osu, R., Yamagishi, Y., Callan, D. E., & Inoue, N. (2008) · Human Brain Mapping · doi:10.1002/hbm.20710 · Cited by 35 · see citing works
Experience-dependent changes in human brain activation during contingency learning
Schlund, M. W., & Ortu, D. (2009) · Neuroscience · doi:10.1016/j.neuroscience.2009.10.014 · Cited by 31 · see citing works
Change is in the eye of the beholder
Yu, A. J. (2012) · Nature Neuroscience · doi:10.1038/nn.3150 · Cited by 24 · see citing works
Learning and Generalization under Ambiguity: An fMRI Study
Chumbley, J. R., Flandin, G., Bach, D. R., Jean Daunizeau, A., Fehr, E., Dolan, R. J., & Friston, K. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002346 · Cited by 20 · see citing works
Brain Structures Involved in Visual Search in the Presence and Absence of Color Singletons
Talsma, D., Coe, B. C., Munoz, D. P., & Theeuwes, J. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21223 · Cited by 15 · see citing works
Glover (2000) · doi:10.1002/1522-2594(200007)44:1
Flagged first, then by citations
Cited by
Sorted by citations
Precise minds in uncertain worlds: Predictive coding in autism.
Van de Cruys, S., Evers, K., Van der Hallen, R., Van Eylen, L., Boets, B., de-Wit, L., & Wagemans, J. (2014) · Psychological Review · doi:10.1037/a0037665 · Cited by 885 · see citing works
Pupil diameter covaries with BOLD activity in human locus coeruleus
Murphy, P. R., O'Connell, R. G., O'Sullivan, M., Robertson, I. H., & Balsters, J. H. (2014) · Human Brain Mapping · doi:10.1002/hbm.22466 · Cited by 819 · see citing works
Anxious individuals have difficulty learning the causal statistics of aversive environments
Browning, M., Behrens, T. E., Jocham, G., O'Reilly, J. X., & Bishop, S. J. (2015) · Nature Neuroscience · doi:10.1038/nn.3961 · Cited by 476 · see citing works
Learning, reward, and decision making
O'Doherty, J. P., Cockburn, J., & Pauli, W. M. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-010416-044216 · Cited by 475 · see citing works
Self-citationHierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning
Iglesias, S., Mathys, C., Brodersen, K. H., Kasper, L., Piccirelli, M., den Ouden, H. E. M., & Stephan, K. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.09.009 · Cited by 342 · see citing works
Computations of uncertainty mediate acute stress responses in humans
de Berker, A. O., Rutledge, R. B., Mathys, C., Marshall, L., Cross, G. F., Dolan, R. J., & Bestmann, S. (2016) · Nature Communications · doi:10.1038/ncomms10996 · Cited by 330 · see citing works
Attention and associative learning in humans: An integrative review.
Le Pelley, M. E., Mitchell, C. J., Beesley, T., George, D. N., & Wills, A. J. (2016) · Psychological Bulletin · doi:10.1037/bul0000064 · Cited by 329 · see citing works
Functionally dissociable influences on learning rate in a dynamic environment
McGuire, J. T., Nassar, M. R., Gold, J. I., & Kable, J. W. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.013 · Cited by 299 · see citing works
Adaptive learning under expected and unexpected uncertainty
Soltani, A., & Izquierdo, A. (2019) · Nature reviews. Neuroscience · doi:10.1038/s41583-019-0180-y · Cited by 286 · see citing works
Computational approaches to psychiatry
Stephan, K. E., & Mathys, C. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.12.007 · Cited by 260 · see citing works
Reinforcement learning in depression: a review of computational research
Chen, C., Takahashi, T., Nakagawa, S., Inoue, T., & Kusumi, I. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.05.005 · Cited by 233 · see citing works
Translational perspectives for computational neuroimaging
Stephan, K. E., Iglesias, S., Heinzle, J., & Diaconescu, A. O. (2015) · Neuron · doi:10.1016/j.neuron.2015.07.008 · Cited by 169 · see citing works
Serotonin neurons modulate learning rate through uncertainty
Grossman, C. D., Bari, B. A., & Cohen, J. Y. (2022) · Current Biology · doi:10.1016/j.cub.2021.12.006 · Cited by 164 · see citing works
Pharmacological Fingerprints of Contextual Uncertainty
Marshall, L., Mathys, C., Ruge, D., de Berker, A. O., Dayan, P., Stephan, K. E., & Bestmann, S. (2016) · PLOS Biology · doi:10.1371/journal.pbio.1002575 · Cited by 158 · see citing works
Brain networks for confidence weighting and hierarchical inference during probabilistic learning
Meyniel, F., & Dehaene, S. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1615773114 · Cited by 138 · see citing works
Catecholaminergic Regulation of Learning Rate in a Dynamic Environment
Jepma, M., Murphy, P. R., Nassar, M. R., Rangel-Gomez, M., Meeter, M., & Nieuwenhuis, S. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005171 · Cited by 91 · see citing works
Real-world stress resilience is associated with the responsivity of the locus coeruleus
Grueschow, M., Stenz, N., Thörn, H., Ehlert, U., Breckwoldt, J., Brodmann Maeder, M., Exadaktylos, A. K., Bingisser, R., Ruff, C. C., & Kleim, B. (2021) · Nature Communications · doi:10.1038/s41467-021-22509-1 · Cited by 116 · see citing works
Enhanced deviant responses in patterned relative to random sound sequences
Southwell, R., & Chait, M. (2018) · Cortex · doi:10.1016/j.cortex.2018.08.032 · Cited by 80 · see citing works
Diederen, K. M. J., Spencer, T., Vestergaard, M. D., Fletcher, P. C., & Schultz, W. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.019 · Cited by 102 · see citing works
Levy, I., & Schiller, D. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.11.007 · Cited by 95 · see citing works
Scaling prediction errors to reward variability benefits error-driven learning in humans
Diederen, K. M. J., & Schultz, W. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00483.2015 · Cited by 69 · see citing works
Anterior insula reflects surprise in value-based decision-making and perception
Loued-Khenissi, L., Pfeuffer, A., Einhäuser, W., & Preuschoff, K. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116549 · Cited by 66 · see citing works
The neural correlates of hierarchical predictions for perceptual decisions
Weilnhammer, V. A., Stuke, H., Sterzer, P., & Schmack, K. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.2901-17.2018 · Cited by 57 · see citing works
Studying the neural representations of uncertainty
Walker, E. Y., Pohl, S., Denison, R. N., Barack, D. L., Lee, J., Block, N., Ma, W. J., & Meyniel, F. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01444-y · Cited by 56 · see citing works
Noradrenergic and Cholinergic Modulation of Belief Updating
Jepma, M., Brown, S. B. R. E., Murphy, P. R., Koelewijn, S. C., de Vries, B., van den Maagdenberg, A. M., & Nieuwenhuis, S. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01317 · Cited by 39 · see citing works
Neural correlates of hierarchical predictive processes in autistic adults
Sapey-Triomphe, L.-A., Pattyn, L., Weilnhammer, V., Sterzer, P., & Wagemans, J. (2023) · Nature Communications · doi:10.1038/s41467-023-38580-9 · Cited by 35 · see citing works
- Authors
- Payzan-LeNestour, E., Dunne, S., Bossaerts, P., & O’Doherty, J. P.
- Affiliations
- California Institute of Technology (US)
- Corresponding author
- Dunne, Simon
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 79
- Issue
- 1
- Pages
- 191-201
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4885745
- OpenAlex
- W2147971214
- Cited by
- 257
- References
- 68
- Citations by year
- 2026: 16 · 2025: 33 · 2024: 20 · 2023: 20 · 2022: 14 · 2021: 18 · 2020: 30 · 2019: 20 · 2018: 18 · 2017: 14 · 2016: 26 · 2015: 12 · 2014: 11 · 2013: 5
- FWCI
- 9.87
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- Science Foundation Ireland (08/IN.1/B1844)
- National Institute of Mental Health (P50MH094258)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- estimation uncertainty, risk, value-based decision making, locus coeruleus, noradrenergic system, learning rate, cortical regions, learning speed
- MeSH terms
- Adult, Bayes Theorem, Brain, Brain Mapping, Decision Making, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Social Values, Uncertainty, Functional Neuroimaging
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 ›
Are you an author, or do you see a problem with this page? Request a review