| # | Title | Journal | Year | Citations |
|---|
| 1 | Nonlinear Dimensionality Reduction by Locally Linear Embedding | Science | 2000 | 12,086 |
| 2 | Training Products of Experts by Minimizing Contrastive Divergence | Neural Computation | 2002 | 3,295 |
| 3 | Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control | Nature Neuroscience | 2005 | 2,108 |
| 4 | An Introduction to Variational Methods for Graphical Models | Machine Learning | 1999 | 1,889 |
| 5 | Cortical substrates for exploratory decisions in humans | Nature | 2006 | 1,790 |
| 6 | Neural correlations, population coding and computation | Nature Reviews Neuroscience | 2006 | 1,419 |
| 7 | Model-Based Influences on Humans' Choices and Striatal Prediction Errors | Neuron | 2011 | 1,388 |
| 8 | Temporal Difference Models and Reward-Related Learning in the Human Brain | Neuron | 2003 | 1,311 |
| 9 | The Future of Memory: Remembering, Imagining, and the Brain | Neuron | 2012 | 1,066 |
| 10 | Tonic dopamine: opportunity costs and the control of response vigor | Psychopharmacology | 2007 | 969 |
| 11 | States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning | Neuron | 2010 | 935 |
| 12 | Stimulus onset quenches neural variability: a widespread cortical phenomenon | Nature Neuroscience | 2010 | 907 |
| 13 | Goals and Habits in the Brain | Neuron | 2013 | 799 |
| 14 | Opponent interactions between serotonin and dopamine | Neural Networks | 2002 | 744 |
| 15 | Reward, Motivation, and Reinforcement Learning | Neuron | 2002 | 743 |
| 16 | Perspectives and problems in motor learning | Trends in Cognitive Sciences | 2001 | 667 |
| 17 | Cortical Control of Arm Movements: A Dynamical Systems Perspective | Annual Review of Neuroscience | 2013 | 633 |
| 18 | The hippocampus as a predictive map | Nature Neuroscience | 2017 | 593 |
| 19 | A deep learning framework for neuroscience | Nature Neuroscience | 2019 | 563 |
| 20 | Disorders of compulsivity: a common bias towards learning habits | Molecular Psychiatry | 2015 | 523 |
| 21 | Probabilistic brains: knowns and unknowns | Nature Neuroscience | 2013 | 498 |
| 22 | Information-limiting correlations | Nature Neuroscience | 2014 | 478 |
| 23 | Decision theory, reinforcement learning, and the brain | Cognitive, Affective and Behavioral Neuroscience | 2008 | 427 |
| 24 | Learning and selective attention | Nature Neuroscience | 2000 | 424 |
| 25 | Vector-based navigation using grid-like representations in artificial agents | Nature | 2018 | 414 |
| 26 | Acetylcholine contributes through muscarinic receptors to attentional modulation in V1 | Nature | 2008 | 406 |
| 27 | Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex | Nature | 2010 | 399 |
| 28 | Dopamine: generalization and bonuses | Neural Networks | 2002 | 388 |
| 29 | Prefrontal cortex as a meta-reinforcement learning system | Nature Neuroscience | 2018 | 378 |
| 30 | Learning The Discriminative Power-Invariance Trade-Off | Nature Neuroscience | 2007 | 358 |
| 31 | Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex | Neuron | 2015 | 358 |
| 32 | Direct cortical control of muscle activation in voluntary arm movements: a model | Nature Neuroscience | 2000 | 353 |
| 33 | Spike-triggered neural characterization | Journal of Vision | 2006 | 336 |
| 34 | Rational approximations to rational models: Alternative algorithms for category learning. | Psychological Review | 2010 | 333 |
| 35 | Go and no-go learning in reward and punishment: Interactions between affect and effect | NeuroImage | 2012 | 328 |
| 36 | SMEM Algorithm for Mixture Models | Neural Computation | 2000 | 323 |
| 37 | A computational and neural model of momentary subjective well-being | Proceedings of the National Academy of Sciences of the United States of America | 2014 | 322 |
| 38 | Bonsai Trees in Your Head: How the Pavlovian System Sculpts Goal-Directed Choices by Pruning Decision Trees | PLoS Computational Biology | 2012 | 314 |
| 39 | Causal inference in perception | Trends in Cognitive Sciences | 2010 | 307 |
| 40 | Serotonin in Affective Control | Annual Review of Neuroscience | 2009 | 301 |
| 41 | Maximum likelihood estimation of cascade point-process neural encoding models | Network: Computation in Neural Systems | 2004 | 292 |
| 42 | Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding | PLoS Computational Biology | 2011 | 292 |
| 43 | VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data | PLoS Computational Biology | 2014 | 278 |
| 44 | Variational Learning for Switching State-Space Models | Neural Computation | 2000 | 269 |
| 45 | A distributional code for value in dopamine-based reinforcement learning | Nature | 2020 | 262 |
| 46 | Mapping value based planning and extensively trained choice in the human brain | Nature Neuroscience | 2012 | 259 |
| 47 | Model-based and model-free Pavlovian reward learning: Revaluation, revision, and revelation | Cognitive, Affective and Behavioral Neuroscience | 2014 | 257 |
| 48 | Phasic norepinephrine: A neural interrupt signal for unexpected events | Network: Computation in Neural Systems | 2006 | 249 |
| 49 | Statistical models for neural encoding, decoding, and optimal stimulus design | Progress in Brain Research | 2007 | 236 |
| 50 | Dopamine restores reward prediction errors in old age | Nature Neuroscience | 2013 | 233 |
