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D Bennett, SM Silverstein, and Y Niv (2019) – The two cultures of computational psychiatry – JAMA Psychiatry 76(6), pp. 563-564. [pdf]

NW Schuck & Y Niv (2019) – Sequential replay of nonspatial task states in the human hippocampus – Science [full text] [Scientific American] [New Scientist]

SD McDougle, PA Butcher, DE Parvin, F Mushtaq, Y Niv, RB Ivry & JA Taylor (2019) – Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures – Current Biology 29(10), pp.1606-1613 [full text]

A Radulescu, Y Niv & I Ballard (2019) – Holistic Reinforcement Learning: The Role of Structure and Attention – Trends in Cognitive Science [pdf]

MJ Sharpe, HM Batchelor, LE Mueller, CY Chang, EJP Maes, Y Niv & G Schoenbaum (2019) – Dopamine transients delivered in learning contexts do not act as model-free prediction errors – bioRxiv [pdf]

MJ Sharpe, T Stalnaker, NW Schuck, S Killcross, G Schoenbaum & Y Niv (2019) – An Integrated Model of Action Selection: Distinct Modes of Cortical Control of Striatal Decision Making – Annual Review of Psychology 70:53-76. [full text]


GB Hermsdorff, T Pereira & Y Niv (2018) – Quantifying Humans' Priors Over Graphical Representations of Tasks. In: Morales A., Gershenson C., Braha D., Minai A., Bar-Yam Y. (eds) Unifying Themes in Complex Systems IX. ICCS 2018. Springer Proceedings in Complexity. Springer, Cham [pdf]

D Bennett & Y Niv (2018) – Opening Burton's Clock: Psychiatric insights from computational cognitive models – PsyArXiv [pdf]

A Langdon, MJ Sharpe, G Schoenbaum & Y Niv (2018) – Model-based predictions for dopamine – Current Opinion in Neurobiology 49:1-7. [pdf]

E Eldar, V Felso, JD Cohen & Y Niv (2018) – A pupillary index of susceptibility to decision biases – bioRxiv [pdf]


N Rouhani, KA Norman, Y Niv (in press) – Dissociable effects of surprising rewards on learning and memory – Journal of Experimental Psychology: Learning, Memory and Cognition [pdf]

NW Schuck, RC Wilson & Y Niv (2017) – A state representation for reinforcement learning and decision-making in the orbitofrontal cortex – bioRxiv [pdf]

MJ Sharpe, NJ Marchant, LR Whitaker, CT Richie, YJ Zhang, EJ Campbell, PP Koivula, JC Necarsulmer, C Mejias-Aponte, M Morales, J Pickel, JC Smith, Y Niv, Y Shaham, BK Harvey* & G Schoenbaum* (2017) – Lateral hypothalamic GABAergic neurons encode reward predictions that are relayed to the ventral tegmental area to regulate learning – Current Biology 27:2089-2100. [pdf]

A Auchter, L Cormack, Y Niv, F Gonzalez-Lima & M-H Monfils (2017) – Reconsolidation–extinction interactions in fear-memory attenuation: the role of inter-trial interval variability – Frontiers in Behavioral Neuroscience 11:2. [full text]

S DuBrow, N Rouhani, Y Niv & KA Norman (2017) – Does mental context drift or shift? – Current Opinion in Behavioral Sciences 17:141–146. [pdf]

SJ Gershman, M Monfils, KA Norman & Y Niv (2017) – The computational nature of memory modification – eLife 6:e23763. [full text]

MJ Sharpe, CY Chang, MA Liu, HM Batchelor, LE Mueller, JL Jones, Y Niv, G Schoenbaum (2017) – Dopamine transients are sufficient and necessary for acquisition of model-based associations – Nature Neuroscience 20:735-742. [pdf]

JD Cohen, N Daw, B Engelhardt, U Hasson, K Li, Y Niv, KA Norman, J Pillow, PJ Ramadge, NB Turk-Browne & TL Willke (2017) – Computational approaches to fMRI analysis – Nature Neuroscience 20: 304–313. [pdf] [press]

YC Leong*, A Radulescu*, R Daniel, V DeWoskin & Y Niv (2017) – Dynamic interaction between reinforcement learning and attention in multidimensional environments – Neuron 93: 451–463. [pdf] [preview] [press release]


Z Kurth-Nelson, JP O’Doherty, DM Barch, S Denève, D Durstewitz, MJ Frank, JA Gordon, SJ Mathew, Y Niv, K Ressler & H Tost. 2016. Computational Approaches for Studying Mechanisms of Psychiatric Disorders. In: Computational Psychiatry: New Perspectives on Mental Illness, edited by A. D. Redish and J. A. Gordon. Strüngmann Forum Reports, vol. 20, J. Lupp, series editor. Cambridge, MA: MIT Press [pdf]

A Radulescu, R Daniel & Y Niv (2016) – The effects of aging on the interaction between reinforcement learning and attention – Psychology and Aging 31(7):747-757 [pdf]

N Schuck, M Cai, RC Wilson & Y Niv (2016) – Human orbitofrontal cortex represents a cognitive map of state space –Neuron [pdf] [link]

E Eldar, Y Niv & JD Cohen (2016) – Do you see the forest or the trees? Neural gain and integration during perceptual processing – Psychological Science [pdf]

MB Cai, NW Schuck, J Pillow & Y Niv (in press) – A Bayesian method for reducing bias in neural representational similarity analysis – Neural Information Processing Systems [link]

SCY Chan, Y Niv* & KA Norman* (2016) – A probability distribution over latent causes in the orbitofrontal cortex – The Journal of Neuroscience 30(30):7817-7828. [pdf] [Princeton Blog]

D Arkadir, A Radulescu, D Raymond, N Lubarr, SB Bressman, P Mazzoni, & Yael Niv (2016) – DYT1 dystonia increases risk taking in humans– eLife 5:e14155 [full text]

Y Takahashi*, A Langdon*, Y Niv & G Schoenbaum (2016) – Temporal specificity of reward prediction errors signaled by putative dopamine neurons in rat VTA depends on ventral striatum – Neuron 91(1):182-193. [pdf]

Y Niv & A Langdon (2016) – Reinforcement Learning with Marr – Current Opinion in Behavioral Sciences 11:67-73. [pdf]

E Eldar, RB Rutledge, RJ Dolan & Y Niv (2016) – Mood as representation of momentum – Trends in Cognitive Science 20(1):15-24 [pdf] [UCL press release] [Huffington Post]


SJ Gershman, KA Norman & Y Niv (2015) – Discovering latent causes in reinforcement learning – Current Opinion in Behavioral Sciences 5:43-50. [pdf]

JE Dunsmoor, Y Niv, ND Daw & EA Phelps (2015) – Rethinking Extinction – Neuron 88:47-63. [pdf]

Y Niv, A Radulescu, & A Langdon (2015) – A free-choice premium in the basal ganglia– Trends in Cognitive Science 19(1), 4-5. [pdf]

R Daniel, NW Schuck, & Y Niv (2015) – How to divide and conquer the world, one step at a time– PNAS 112(10), 2929-2930. [pdf]

SJ Gershman & Y Niv (2015) – Novelty and inductive generalization in human reinforcement learning – Topics in Cognitive Science 1-25. [pdf]

A Geana & Y Niv (2015) - Causal model comparison shows that human representation learning is not Bayesian - Cold Spring Harbor Symposia on Quantitative Biology, Volume 79: Cognition. [pdf]

Y Niv, R Daniel, A Geana, SJ Gershman, YC Leong, A Radulescu & RC Wilson (2015) - Reinforcement learning in multidimensional environments relies on attention mechanisms - The Journal of Neuroscience. 35(21), 8145-8157.[pdf]

RC Wilson & Y Niv (2015) - Is model fitting necessary for model-based fMRI? - PLoS Computational Biology. 11(6): e1004237. [pdf]

E Eldar & Y Niv (2015) - Interaction between emotional state and learning underlies mood instability - Nature Communications, 6. [pdf]

NW Schuck, R Gaschler,D Wenke, J Heinzle, PA Frensch, JD Haynes & C Reverberi (2015) - Medial prefrontal cortex predicts internally driven strategy shifts - Neuron, 86(1), 331-340. [pdf]


FA Soto, SJ Gershman & Y Niv (2014) - Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization - Psychological Review . 121(3):526-558. [pdf]

RC Wilson, YK Takahashi, G Schoenbaum, Y Niv (2014) - Orbitofrontal Cortex as a Cognitive Map of Task Space - Neuron. 81(2), 267-279. [pdf]

SJ Gershman, A Radulescu, KA Norman & Y Niv (2014) - Statistical computations underlying the dynamics of memory updating - PLoS Computational Biology, 10, e1003939. [pdf]

A Solway, C Diuk, N Cordova, D Yee, AG Barto, Y Niv & MM Botvinick (2014) - Optimal behavioral hierarchy - PLoS Computational Biology 10(8): e1003779. [pdf]


SJ Gershman, CE Jones, KA Norman, M Monfils, Y Niv (2013) - Gradual extinction prevents the return of fear: Implications for the discovery of state - Frontiers in Behavioral Neuroscience, 7:164. [full text] [SfN '13 primer]

SJ Gershman, Y Niv (2013) - Perceptual estimation obeys Occam's razor - Frontiers in Psychology, 4:623. [full text]

A Christakou, SJ Gershman, Y Niv, A Simmons, M Brammer, K Rubia (2013) - Neural and Psychological Maturation of Decision-making in Adolescence and Young Adulthood - Journal of Cognitive Neuroscience, 25:11, 1807-1823. [pdf]

Y Niv (2013) - Dopamine ramps up - Nature, 500, 533-535. [pdf] [news & views for this paper]

G Schoenbaum, TA Stalnaker, Y Niv (2013) - How Did the Chicken Cross the Road? With Her Striatal Cholinergic Interneurons, Of Course - Neuron, 79(1), 3-6. [pdf] [preview for this paper]

E Eldar, JD Cohen, Y Niv (2013) - The effects of neural gain on attention and learning - Nature Neuroscience, 16:1146-1153. [pdf] [preview] [press release]

C Diuk, K Tsai, J Wallis, M Botvinick, Y Niv (2013) - Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia - The Journal of Neuroscience, 33(13), 5797-5805. [pdf]


SJ Gershman, Y Niv (2012) - Exploring a latent cause theory of classical conditioning - Learning & Behavior 40:255-268. [pdf]

RC Wilson, Y Niv (2012) - Inferring relevance in a changing world - Frontiers in Human Neuroscience 5:189. [full text]

Y Niv, J Edlund, P Dayan, JP O'Doherty (2012) - Neural prediction errors reveal a risk-sensitive reinforcement learning process in the human brain - The Journal of Neuroscience 32(2):551-562.


YK Takahashi, MR Roesch, RC Wilson, K Toreson, P O'Donnell, Y Niv, G Schoenbaum (2011) - Expectancy-related changes in firing of dopamine neurons depend on orbitofrontal cortex - Nature Neuroscience 14(12):1590-1597. [pdf]

E Eldar, G Morris, Y Niv (2011) - The effects of motivation on response rate: A hidden semi-Markov model analysis of behavioral dynamics - Journal of Neuroscience Methods 1201:251-261. [pdf]

JJF Ribas-Fernandes, A Solway, C Diuk, JT McGuire, AG Barto, Y Niv & MM Botvinick (2011) - A neural signature of hierarchical reinforcement learning - Neuron 71:370-379. [pdf] [preview]

M McDannald, F Lucantonio, K Burke, Y Niv & G Schoenbaum (2011) - Ventral striatum and orbitofrontal cortex are both required for model-based, but not model-free, reinforcement learning - Journal of Neuroscience 31(7), 2700-2705. [pdf]


SJ Gershman, JD Cohen & Y Niv (2010) - Learning to selectively attend - Proceedings of the 32nd Annual Conference of the Cognitive Science Society. [pdf]

SJ Gershman & Y Niv (2010) - Learning latent structure: Carving nature at its joints - Current Opinion in Neurobiology 20(2), 251-256. [pdf]

SJ Gershman, D Blei & Y Niv (2010) - Context, learning and extinction - Psychological Review 117(1), 197-209. [pdf]


Y Niv (2009) - Reinforcement learning in the brain - The Journal of Mathematical Psychology 53(3), 139-154. [pdf]

MM Botvinick, Y Niv & A Barto (2009) - Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective - Cognition 113, 262-280. [pdf]


MT Todd, Y Niv & JD Cohen (2008) - Learning to use working memory in partially observable environments through dopaminergic reinforcement - NIPS 2008. [pdf]

D Schiller, I Levi, Y Niv, JE LeDoux & EA Phelps (2008) - From fear to safety and back - Reversal of fear in the human brain - The Journal of Neuroscience 28(45), 11517-11525.

P Dayan & Y Niv (2008) - Reinforcement learning and the brain: The Good, The Bad and The Ugly - Current Opinion in Neurobiology 18(2), 185-196. [pdf]

Y Takahashi, G Schoenbaum & Y Niv (2008) - Silencing the critics: Understanding the effects of cocaine sensitization on dorsal and ventral striatum in the context of an Actor/Critic model - Frontiers in Neuroscience 2, 86-99. [pdf]

Y Niv & G Schoenbaum (2008) - Dialogues on prediction errors - Trends in Cognitive Sciences, 12(7), 265-272. [pdf]


Y Niv, ND Daw, D Joel & P Dayan (2007) - Tonic dopamine: Opportunity costs and the control of response vigor - Psychopharmacology, 191(3), 507-520. [pdf]


Y Niv, D Joel & P Dayan (2006) - A normative perspective on motivation - Trends in Cognitive Sciences, 10(8), 375-381. [pdf]

P Dayan, Y Niv, B Seymour & ND Daw (2006) - The misbehavior of value and the discipline of the will - Neural Networks, 19(8), 1153-1160. [pdf]


Y Niv, ND Daw & P Dayan (2005) - How fast to work: Response vigor, motivation and tonic dopamine - In: Y Weiss, B Scholkopf & J Platt, eds., Neural Information Processing Systems, 18, 1019-1026, MIT Press (Outstanding Student Paper Award). [pdf]

ND Daw, Y Niv & P Dayan (2005) - Uncertainty based competition between prefrontal and dorsolateral striatal systems for behavioral control - Nature Neuroscience, 8(12), 1704-1711. [pdf]

Y Niv, MO Duff & P Dayan (2005) - Dopamine, Uncertainty and TD Learning - Behavioral and Brain Functions, 1:6 (4 May 2005), doi:10.1186/1744-9081-1-6. [full text]


Y Niv, D Joel, I Meilijson & E Ruppin (2002) - Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors - Adaptive Behavior, 10(1), 5-24. [pdf]

D Joel, Y Niv & E Ruppin (2002) - Actor-critic models of the basal ganglia: New anatomical and computational perspectives - Neural Networks, 15, 535-547. [pdf]

Niv Lab     //    Department of Psychology    //    Princeton Neuroscience Institute

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