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Samuel Gershman - Publications

Affiliations: 
Harvard Medical School, Boston, MA, United States 
Area:
Computational cognitive neuroscience of learning and memory
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44 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Qü AJ, Tai LH, Hall CD, Tu EM, Eckstein MK, Mishchanchuk K, Lin WC, Chase JB, MacAskill AF, Collins AGE, Gershman SJ, Wilbrecht L. Nucleus accumbens dopamine release reflects Bayesian inference during instrumental learning. Biorxiv : the Preprint Server For Biology. PMID 38014354 DOI: 10.1101/2023.11.10.566306  0.384
2023 Hennig JA, Romero Pinto SA, Yamaguchi T, Linderman SW, Uchida N, Gershman SJ. Emergence of belief-like representations through reinforcement learning. Plos Computational Biology. 19: e1011067. PMID 37695776 DOI: 10.1371/journal.pcbi.1011067  0.668
2023 Geerts JP, Gershman SJ, Burgess N, Stachenfeld KL. A probabilistic successor representation for context-dependent learning. Psychological Review. PMID 37166847 DOI: 10.1037/rev0000414  0.376
2023 Hennig JA, Romero Pinto SA, Yamaguchi T, Linderman SW, Uchida N, Gershman SJ. Emergence of belief-like representations through reinforcement learning. Biorxiv : the Preprint Server For Biology. PMID 37066383 DOI: 10.1101/2023.04.04.535512  0.668
2022 Bill J, Gershman SJ, Drugowitsch J. Visual motion perception as online hierarchical inference. Nature Communications. 13: 7403. PMID 36456546 DOI: 10.1038/s41467-022-34805-5  0.756
2022 Pouncy T, Gershman SJ. Inductive biases in theory-based reinforcement learning. Cognitive Psychology. 138: 101509. PMID 36152355 DOI: 10.1016/j.cogpsych.2022.101509  0.315
2022 Mikhael JG, Kim HR, Uchida N, Gershman SJ. The role of state uncertainty in the dynamics of dopamine. Current Biology : Cb. PMID 35114098 DOI: 10.1016/j.cub.2022.01.025  0.673
2021 Mikhael JG, Gershman SJ. Impulsivity and risk-seeking as Bayesian inference under dopaminergic control. Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology. PMID 34376813 DOI: 10.1038/s41386-021-01125-z  0.317
2021 Dorfman HM, Tomov M, Cheung B, Clarke D, Gershman SJ, Hughes BL. Causal inference gates corticostriatal learning. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 34244363 DOI: 10.1523/JNEUROSCI.2796-20.2021  0.365
2021 Mikhael JG, Lai L, Gershman SJ. Rational inattention and tonic dopamine. Plos Computational Biology. 17: e1008659. PMID 33760806 DOI: 10.1371/journal.pcbi.1008659  0.363
2021 Yang S, Bill J, Drugowitsch J, Gershman SJ. Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports. 11: 3714. PMID 33580096 DOI: 10.1038/s41598-021-82175-7  0.755
2021 Tomov MS, Schulz E, Gershman SJ. Multi-task reinforcement learning in humans. Nature Human Behaviour. PMID 33510391 DOI: 10.1038/s41562-020-01035-y  0.318
2020 Kim HR, Malik AN, Mikhael JG, Bech P, Tsutsui-Kimura I, Sun F, Zhang Y, Li Y, Watabe-Uchida M, Gershman SJ, Uchida N. A Unified Framework for Dopamine Signals across Timescales. Cell. PMID 33248024 DOI: 10.1016/j.cell.2020.11.013  0.637
2020 Bill J, Pailian H, Gershman SJ, Drugowitsch J. Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences of the United States of America. 117: 24581-24589. PMID 32938799 DOI: 10.1073/Pnas.2008961117  0.754
2020 Schulz E, Franklin NT, Gershman SJ. Finding structure in multi-armed bandits. Cognitive Psychology. 119: 101261. PMID 32059133 DOI: 10.1016/J.Cogpsych.2019.101261  0.36
2019 Dorfman HM, Gershman SJ. Controllability governs the balance between Pavlovian and instrumental action selection. Nature Communications. 10: 5826. PMID 31862876 DOI: 10.1038/S41467-019-13737-7  0.305
2019 Stalnaker T, Howard JD, Takahashi YK, Gershman SJ, Kahnt T, Schoenbaum G. Dopamine neuron ensembles signal the content of sensory prediction errors. Elife. 8. PMID 31674910 DOI: 10.7554/Elife.49315  0.324
2019 Gershman SJ, Uchida N. Believing in dopamine. Nature Reviews. Neuroscience. PMID 31570826 DOI: 10.1038/s41583-019-0220-7  0.667
2019 Mikhael JG, Gershman SJ. Adapting the Flow of Time with Dopamine. Journal of Neurophysiology. PMID 30864882 DOI: 10.1152/jn.00817.2018  0.338
2019 Bill J, Pailian H, Gershman SJ, Drugowitsch J. Hierarchical motion structure is employed by humans during visual perception Journal of Vision. 19: 282. DOI: 10.1167/19.10.282  0.737
2018 Schulz E, Gershman SJ. The algorithmic architecture of exploration in the human brain. Current Opinion in Neurobiology. 55: 7-14. PMID 30529148 DOI: 10.1016/J.Conb.2018.11.003  0.308
2018 Gardner MPH, Schoenbaum G, Gershman SJ. Rethinking dopamine as generalized prediction error. Proceedings. Biological Sciences. 285. PMID 30464063 DOI: 10.1098/rspb.2018.1645  0.326
2018 Petter EA, Gershman SJ, Meck WH. Integrating Models of Interval Timing and Reinforcement Learning. Trends in Cognitive Sciences. 22: 911-922. PMID 30266150 DOI: 10.1016/j.tics.2018.08.004  0.313
2018 Gershman SJ. The successor representation: its computational logic and neural substrates. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 30006364 DOI: 10.1523/JNEUROSCI.0151-18.2018  0.334
2018 Tomov MS, Dorfman HM, Gershman SJ. Neural Computations Underlying Causal Structure Learning. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 29959234 DOI: 10.1523/Jneurosci.3336-17.2018  0.364
2018 Babayan BM, Uchida N, Gershman SJ. Belief state representation in the dopamine system. Nature Communications. 9: 1891. PMID 29760401 DOI: 10.1038/S41467-018-04397-0  0.725
2018 Starkweather CK, Gershman SJ, Uchida N. The Medial Prefrontal Cortex Shapes Dopamine Reward Prediction Errors under State Uncertainty. Neuron. PMID 29656872 DOI: 10.1016/J.Neuron.2018.03.036  0.659
2017 Momennejad I, Russek EM, Cheong JH, Botvinick MM, Daw ND, Gershman SJ. The successor representation in human reinforcement learning. Nature Human Behaviour. 1: 680-692. PMID 31024137 DOI: 10.1038/S41562-017-0180-8  0.318
2017 Gershman SJ. Dopamine, Inference, and Uncertainty. Neural Computation. 1-16. PMID 28957023 DOI: 10.1162/neco_a_01023  0.378
2017 Russek EM, Momennejad I, Botvinick MM, Gershman SJ, Daw ND. Predictive representations can link model-based reinforcement learning to model-free mechanisms. Plos Computational Biology. 13: e1005768. PMID 28945743 DOI: 10.1371/Journal.Pcbi.1005768  0.327
2017 Gershman SJ, Zhou J, Kommers C. Imaginative Reinforcement Learning: Computational Principles and Neural Mechanisms. Journal of Cognitive Neuroscience. 1-11. PMID 28707569 DOI: 10.1162/jocn_a_01170  0.335
2017 Starkweather CK, Babayan BM, Uchida N, Gershman SJ. Dopamine reward prediction errors reflect hidden-state inference across time. Nature Neuroscience. PMID 28263301 DOI: 10.1038/Nn.4520  0.73
2016 Lake BM, Ullman TD, Tenenbaum JB, Gershman SJ. Building Machines That Learn and Think Like People. The Behavioral and Brain Sciences. 1-101. PMID 27881212 DOI: 10.1017/S0140525X16001837  0.307
2016 Pereira F, Gershman S, Ritter S, Botvinick M. A comparative evaluation of off-the-shelf distributed semantic representations for modelling behavioural data. Cognitive Neuropsychology. 33: 175-90. PMID 27686110 DOI: 10.1080/02643294.2016.1176907  0.319
2016 Tervo DG, Tenenbaum JB, Gershman SJ. Toward the neural implementation of structure learning. Current Opinion in Neurobiology. 37: 99-105. PMID 26874471 DOI: 10.1016/j.conb.2016.01.014  0.315
2015 Niv Y, Daniel R, Geana A, Gershman SJ, Leong YC, Radulescu A, Wilson RC. Reinforcement learning in multidimensional environments relies on attention mechanisms. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 8145-57. PMID 26019331 DOI: 10.1523/Jneurosci.2978-14.2015  0.336
2015 Gershman SJ, Tenenbaum JB, Jäkel F. Discovering hierarchical motion structure. Vision Research. PMID 25818905 DOI: 10.1016/j.visres.2015.03.004  0.353
2015 Gershman SJ, Niv Y. Novelty and Inductive Generalization in Human Reinforcement Learning. Topics in Cognitive Science. PMID 25808176 DOI: 10.1111/tops.12138  0.339
2015 Gershman SJ, Norman KA, Niv Y. Discovering latent causes in reinforcement learning Current Opinion in Behavioral Sciences. 5: 43-50. DOI: 10.1016/j.cobeha.2015.07.007  0.319
2014 Gershman SJ. Dopamine ramps are a consequence of reward prediction errors. Neural Computation. 26: 467-71. PMID 24320851 DOI: 10.1162/NECO_a_00559  0.36
2012 Gershman SJ, Moore CD, Todd MT, Norman KA, Sederberg PB. The successor representation and temporal context. Neural Computation. 24: 1553-68. PMID 22364500 DOI: 10.1162/Neco_A_00282  0.307
2011 Daw ND, Gershman SJ, Seymour B, Dayan P, Dolan RJ. Model-based influences on humans' choices and striatal prediction errors. Neuron. 69: 1204-15. PMID 21435563 DOI: 10.1016/J.Neuron.2011.02.027  0.308
2010 Gershman SJ, Niv Y. Learning latent structure: carving nature at its joints. Current Opinion in Neurobiology. 20: 251-6. PMID 20227271 DOI: 10.1016/j.conb.2010.02.008  0.339
2009 Gershman SJ, Pesaran B, Daw ND. Human reinforcement learning subdivides structured action spaces by learning effector-specific values. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 29: 13524-31. PMID 19864565 DOI: 10.1523/JNEUROSCI.2469-09.2009  0.37
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