{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:59:09Z","timestamp":1790830749717,"version":"4.1.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T00:00:00Z","timestamp":1572220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T00:00:00Z","timestamp":1572220800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Neurosci"],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1038\/s41593-019-0518-9","type":"journal-article","created":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T13:06:18Z","timestamp":1572267978000},"page":"2066-2077","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":176,"title":["Computational noise in reward-guided learning drives behavioral variability in volatile environments"],"prefix":"10.1038","volume":"22","author":[{"given":"Charles","family":"Findling","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasilisa","family":"Skvortsova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00e9mi","family":"Dromnelle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5768-6646","authenticated-orcid":false,"given":"Stefano","family":"Palminteri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6522-7837","authenticated-orcid":false,"given":"Valentin","family":"Wyart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,10,28]]},"reference":[{"key":"518_CR1","doi-asserted-by":"crossref","unstructured":"Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction (MIT Press, 1998).","DOI":"10.1109\/TNN.1998.712192"},{"key":"518_CR2","unstructured":"Rescorla, R. A. & Wagner, A. R. A theory of Pavlovian conditioning: variations in the effectiveness of reinforcement and nonreinforcement. in Classical Conditioning II (eds Black, A. H.Prokasy, W. F.) 64\u201399 (Appleton-Century-Crofts, 1972)."},{"key":"518_CR3","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1038\/nature04766","volume":"441","author":"ND Daw","year":"2006","unstructured":"Daw, N. D., O\u2019Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876\u2013879 (2006).","journal-title":"Nature"},{"key":"518_CR4","doi-asserted-by":"crossref","first-page":"2074","DOI":"10.1037\/a0038199","volume":"143","author":"RC Wilson","year":"2014","unstructured":"Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A. & Cohen, J. D. Humans use directed and random exploration to solve the explore\u2013exploit dilemma. J. Exp. Psychol. Gen. 143, 2074\u20132081 (2014).","journal-title":"J. Exp. Psychol. Gen."},{"key":"518_CR5","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.cobeha.2016.07.003","volume":"11","author":"V Wyart","year":"2016","unstructured":"Wyart, V. & Koechlin, E. Choice variability and suboptimality in uncertain environments. Curr. Opin. Behav. Sci. 11, 109\u2013115 (2016).","journal-title":"Curr. Opin. Behav. Sci."},{"key":"518_CR6","doi-asserted-by":"crossref","first-page":"1398","DOI":"10.1016\/j.neuron.2016.11.005","volume":"92","author":"J Drugowitsch","year":"2016","unstructured":"Drugowitsch, J., Wyart, V., Devauchelle, A.-D. & Koechlin, E. Computational precision of mental inference as critical source of human choice suboptimality. Neuron 92, 1398\u20131411 (2016).","journal-title":"Neuron"},{"key":"518_CR7","unstructured":"Fechner, G. T. Elements of Psychophysics (Holt, Reinehart & Winston, 1966)."},{"key":"518_CR8","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1038\/nn.2501","volume":"13","author":"MM Churchland","year":"2010","unstructured":"Churchland, M. M. et al. Stimulus onset quenches neural variability: a widespread cortical phenomenon. Nat. Neurosci. 13, 369\u2013378 (2010).","journal-title":"Nat. Neurosci."},{"key":"518_CR9","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1177\/107385840200800207","volume":"8","author":"KO Johnson","year":"2002","unstructured":"Johnson, K. O., Hsiao, S. S. & Yoshioka, T. Neural coding and the basic law of psychophysics. Neuroscientist 8, 111\u2013121 (2002).","journal-title":"Neuroscientist"},{"key":"518_CR10","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.tics.2017.03.011","volume":"21","author":"S Palminteri","year":"2017","unstructured":"Palminteri, S., Wyart, V. & Koechlin, E. The importance of falsification in computational cognitive modeling. Trends Cogn. Sci. 21, 425\u2013433 (2017).","journal-title":"Trends Cogn. Sci."},{"key":"518_CR11","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1016\/j.neuron.2009.05.014","volume":"62","author":"ED Boorman","year":"2009","unstructured":"Boorman, E. D., Behrens, T. E. J., Woolrich, M. W. & Rushworth, M. F. S. How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action. Neuron 62, 733\u2013743 (2009).","journal-title":"Neuron"},{"key":"518_CR12","doi-asserted-by":"crossref","DOI":"10.1038\/ncomms9096","volume":"6","author":"S Palminteri","year":"2015","unstructured":"Palminteri, S., Khamassi, M., Joffily, M. & Coricelli, G. Contextual modulation of value signals in reward and punishment learning. Nat. Commun. 6, 8096 (2015).","journal-title":"Nat. Commun."},{"key":"518_CR13","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1901\/jeab.2005.110-04","volume":"84","author":"B Lau","year":"2005","unstructured":"Lau, B. & Glimcher, P. W. Dynamic response-by-response models of matching behavior in rhesus monkeys. J. Exp. Anal. Behav. 84, 555\u2013579 (2005).","journal-title":"J. Exp. Anal. Behav."},{"key":"518_CR14","doi-asserted-by":"crossref","first-page":"13524","DOI":"10.1523\/JNEUROSCI.2469-09.2009","volume":"29","author":"SJ Gershman","year":"2009","unstructured":"Gershman, S. J., Pesaran, B. & Daw, N. D. Human reinforcement learning subdivides structured action spaces by learning effector-specific values. J. Neurosci. 29, 13524\u201313531 (2009).","journal-title":"J. Neurosci."},{"key":"518_CR15","first-page":"1873","volume":"21","author":"AJ Yu","year":"2009","unstructured":"Yu, A. J. & Cohen, J. D. Sequential effects: superstition or rational behavior? Adv. Neural Inf. Process. Syst. 21, 1873\u20131880 (2009).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"518_CR16","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1098\/rstb.2007.2098","volume":"362","author":"JD Cohen","year":"2007","unstructured":"Cohen, J. D., McClure, S. M. & Yu, A. J. Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 362, 933\u2013942 (2007).","journal-title":"Philos. Trans. R. Soc. Lond. B. Biol. Sci."},{"key":"518_CR17","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1038\/nn2077","volume":"11","author":"K Doya","year":"2008","unstructured":"Doya, K. Modulators of decision making. Nat. Neurosci. 11, 410\u2013416 (2008).","journal-title":"Nat. Neurosci."},{"key":"518_CR18","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.neuron.2013.07.007","volume":"79","author":"A Shenhav","year":"2013","unstructured":"Shenhav, A., Botvinick, M. M. & Cohen, J. D. The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron 79, 217\u2013240 (2013).","journal-title":"Neuron"},{"key":"518_CR19","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1126\/science.1252254","volume":"344","author":"M Donoso","year":"2014","unstructured":"Donoso, M., Collins, A. G. E. & Koechlin, E. Foundations of human reasoning in the prefrontal cortex. Science 344, 1481\u20131486 (2014).","journal-title":"Science"},{"key":"518_CR20","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1146\/annurev.neuro.28.061604.135709","volume":"28","author":"G Aston-Jones","year":"2005","unstructured":"Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403\u2013450 (2005).","journal-title":"Annu. Rev. Neurosci."},{"key":"518_CR21","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1126\/science.283.5401.549","volume":"283","author":"M Usher","year":"1999","unstructured":"Usher, M., Cohen, J. D., Servan-Schreiber, D., Rajkowski, J. & Aston-Jones, G. The role of locus coeruleus in the regulation of cognitive performance. Science 283, 549\u2013554 (1999).","journal-title":"Science"},{"key":"518_CR22","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1038\/nn.3428","volume":"16","author":"E Eldar","year":"2013","unstructured":"Eldar, E., Cohen, J. D. & Niv, Y. The effects of neural gain on attention and learning. Nat. Neurosci. 16, 1146\u20131153 (2013).","journal-title":"Nat. Neurosci."},{"key":"518_CR23","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1162\/jocn.2010.21548","volume":"23","author":"M Jepma","year":"2011","unstructured":"Jepma, M. & Nieuwenhuis, S. Pupil diameter predicts changes in the exploration-exploitation trade-off: evidence for the adaptive gain theory. J. Cogn. Neurosci. 23, 1587\u20131596 (2011).","journal-title":"J. Cogn. Neurosci"},{"key":"518_CR24","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.neuron.2015.11.028","volume":"89","author":"S Joshi","year":"2015","unstructured":"Joshi, S., Li, Y., Kalwani, R. M. & Gold, J. I. Relationships between pupil diameter and neuronal activity in the locus coeruleus, colliculi, and cingulate cortex. Neuron 89, 221\u2013234 (2015).","journal-title":"Neuron"},{"key":"518_CR25","doi-asserted-by":"crossref","first-page":"e1004567","DOI":"10.1371\/journal.pcbi.1004567","volume":"11","author":"SJ Gershman","year":"2015","unstructured":"Gershman, S. J. A unifying probabilistic view of associative learning. PLoS Comput. Biol. 11, e1004567 (2015).","journal-title":"PLoS Comput. Biol."},{"key":"518_CR26","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.neuron.2012.03.016","volume":"74","author":"JM Beck","year":"2012","unstructured":"Beck, J. M., Ma, W. J., Pitkow, X., Latham, P. E. & Pouget, A. Not noisy, just wrong: the role of suboptimal inference in behavioral variability. Neuron 74, 30\u201339 (2012).","journal-title":"Neuron"},{"key":"518_CR27","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1038\/nn1724","volume":"9","author":"SW Kennerley","year":"2006","unstructured":"Kennerley, S. W., Walton, M. E., Behrens, T. E. J., Buckley, M. J. & Rushworth, M. F. S. Optimal decision making and the anterior cingulate cortex. Nat. Neurosci. 9, 940\u2013947 (2006).","journal-title":"Nat. Neurosci."},{"key":"518_CR28","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.cell.2014.08.037","volume":"159","author":"DGR Tervo","year":"2014","unstructured":"Tervo, D. G. R. et al. Behavioral variability through stochastic choice and its gating by anterior cingulate cortex. Cell 159, 21\u201332 (2014).","journal-title":"Cell"},{"key":"518_CR29","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.neuron.2017.03.044","volume":"94","author":"S Farashahi","year":"2017","unstructured":"Farashahi, S. et al. Metaplasticity as a neural substrate for adaptive learning and choice under uncertainty. Neuron 94, 401\u2013414.e6 (2017).","journal-title":"Neuron"},{"key":"518_CR30","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-017-02169-w","volume":"8","author":"D Meder","year":"2017","unstructured":"Meder, D. et al. Simultaneous representation of a spectrum of dynamically changing value estimates during decision making. Nat. Commun. 8, 1942 (2017).","journal-title":"Nat. Commun."},{"key":"518_CR31","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I. & Salakhutdinov, R. Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929\u20131958 (2014).","journal-title":"J. Mach. Learn. Res."},{"key":"518_CR32","doi-asserted-by":"crossref","unstructured":"Bottou, L. Large-scale machine learning with stochastic gradient descent. in Proceedings of COMPSTAT\u20192010 (eds Lechevallier Y. & Saporta G.) 177\u2013186 (2010).","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"518_CR33","doi-asserted-by":"crossref","first-page":"1214","DOI":"10.1038\/nn1954","volume":"10","author":"TEJ Behrens","year":"2007","unstructured":"Behrens, T. E. J., Woolrich, M. W., Walton, M. E. & Rushworth, M. F. S. Learning the value of information in an uncertain world. Nat. Neurosci. 10, 1214\u20131221 (2007).","journal-title":"Nat. Neurosci."},{"key":"518_CR34","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.neuron.2005.04.026","volume":"46","author":"AJ Yu","year":"2005","unstructured":"Yu, A. J. & Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46, 681\u2013692 (2005).","journal-title":"Neuron"},{"key":"518_CR35","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/0006-8993(84)90351-2","volume":"306","author":"AFT Arnsten","year":"1984","unstructured":"Arnsten, A. F. T. & Goldman-Rakic, P. S. Selective prefrontal cortical projections to the region of the locus coeruleus and raphe nuclei in the rhesus monkey. Brain Res. 306, 9\u201318 (1984).","journal-title":"Brain Res."},{"key":"518_CR36","doi-asserted-by":"crossref","first-page":"e0176034","DOI":"10.1371\/journal.pone.0176034","volume":"12","author":"CM Warren","year":"2017","unstructured":"Warren, C. M. et al. The effect of atomoxetine on random and directed exploration in humans. PLoS One 12, e0176034 (2017).","journal-title":"PLoS One"},{"key":"518_CR37","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.3758\/s13415-017-0531-y","volume":"17","author":"GA Kane","year":"2017","unstructured":"Kane, G. A. et al. Increased locus coeruleus tonic activity causes disengagement from a patch-foraging task. Cogn. Affect. Behav. Neurosci. 17, 1073\u20131083 (2017).","journal-title":"Cogn. Affect. Behav. Neurosci."},{"key":"518_CR38","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1038\/nn.3961","volume":"18","author":"M Browning","year":"2015","unstructured":"Browning, M., Behrens, T. E., Jocham, G., O\u2019Reilly, J. X. & Bishop, S. J. Anxious individuals have difficulty learning the causal statistics of aversive environments. Nat. Neurosci. 18, 590\u2013596 (2015).","journal-title":"Nat. Neurosci."},{"key":"518_CR39","doi-asserted-by":"crossref","unstructured":"Robert, C. & Casella, G. Monte Carlo Statistical Methods (Springer, 2004).","DOI":"10.1007\/978-1-4757-4145-2"},{"key":"518_CR40","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1093\/biomet\/89.3.539","volume":"89","author":"N Chopin","year":"2002","unstructured":"Chopin, N. A sequential particle filter method for static models. Biometrika 89, 539\u2013552 (2002).","journal-title":"Biometrika"},{"key":"518_CR41","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1111\/j.1467-9868.2012.01046.x","volume":"75","author":"N Chopin","year":"2013","unstructured":"Chopin, N., Jacob, P. E. & Papaspiliopoulos, O. SMC2: an efficient algorithm for sequential analysis of state space models. J. R. Stat. Soc. B 75, 397\u2013426 (2013).","journal-title":"J. R. Stat. Soc. B"},{"key":"518_CR42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000045","volume":"6","author":"F Lindsten","year":"2013","unstructured":"Lindsten, F. & Sch\u00f6n, T. B. Backward simulation methods for Monte Carlo statistical inference. Found. Trends Mach. Learn. 6, 1\u2013143 (2013).","journal-title":"Found. Trends Mach. Learn."},{"key":"518_CR43","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1023\/A:1008935410038","volume":"10","author":"A Doucet","year":"2000","unstructured":"Doucet, A., Godsill, S. & Andrieu, C. On sequential Monte Carlo sampling methods for Bayesian filtering. Stat. Comput. 10, 197\u2013208 (2000).","journal-title":"Stat. Comput."},{"key":"518_CR44","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/S1053-8119(03)00073-9","volume":"19","author":"R Deichmann","year":"2003","unstructured":"Deichmann, R., Gottfried, J., Hutton, C. & Turner, R. Optimized EPI for fMRI studies of the orbitofrontal cortex. Neuroimage 19, 430\u2013441 (2003).","journal-title":"Neuroimage"},{"key":"518_CR45","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.neuroimage.2006.07.029","volume":"33","author":"N Weiskopf","year":"2006","unstructured":"Weiskopf, N., Hutton, C., Josephs, O. & Deichmann, R. Optimal EPI parameters for reduction of susceptibility-induced BOLD sensitivity losses: a whole-brain analysis at 3T and 1.5T. Neuroimage 33, 493\u2013504 (2006).","journal-title":"Neuroimage"},{"key":"518_CR46","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","volume":"62","author":"M Jenkinson","year":"2012","unstructured":"Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. Neuroimage 62, 782\u2013790 (2012).","journal-title":"Neuroimage"},{"key":"518_CR47","doi-asserted-by":"crossref","first-page":"225","DOI":"10.3758\/PBR.16.2.225","volume":"16","author":"JN Rouder","year":"2009","unstructured":"Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D. & Iverson, G. Bayesian t tests for accepting and rejecting the null hypothesis. Psychon. Bull. Rev. 16, 225\u2013237 (2009).","journal-title":"Psychon. Bull. Rev."},{"key":"518_CR48","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1016\/j.neuroimage.2009.03.025","volume":"15","author":"KE Stephan","year":"2009","unstructured":"Stephan, K. E., Penny, W. D., Daunizeau, J., Moran, R. J. & Friston, K. J. Bayesian model selection for group studies. NeuroImage 15, 1004\u20131017 (2009).","journal-title":"NeuroImage"}],"container-title":["Nature Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.nature.com\/articles\/s41593-019-0518-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/www.nature.com\/articles\/s41593-019-0518-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/www.nature.com\/articles\/s41593-019-0518-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T18:19:25Z","timestamp":1684606765000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41593-019-0518-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,28]]},"references-count":48,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["518"],"URL":"https:\/\/doi.org\/10.1038\/s41593-019-0518-9","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/439885","asserted-by":"object"}]},"ISSN":["1097-6256","1546-1726"],"issn-type":[{"value":"1097-6256","type":"print"},{"value":"1546-1726","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,28]]},"assertion":[{"value":"11 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 September 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}