Reward prediction error
Open accessAbstract
In this quick guide, Wolfram Schultz provides an introduction of reward prediction error, exploring the signal of dopamine neurons and describing its potential role in reward accumulation, decision-making and everyday life.
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Reward prediction errors are caused by differences between expected and received rewards and can be positive or negative depending on whether the reward exceeds or fails to meet expectations.
“Reward prediction errors are caused by differences between expected and received rewards and can be positive or negative, depending on whether the reward exceeds or fails to meet expectations, respectively (Schultz, 2017).”
From Are prediction error modifications domain specific in autism but domain general in ADHD? (2025) · cites this paper as Schultz, 2017
Dopaminergic neurons in the ventral tegmental area fire in response to unpredicted reward and in anticipation of impending reward.
“dopaminergic neurons in the VTA fire in response to unpredicted reward and in anticipation of impending reward [20]”
From The molecular and cellular mechanisms of depression: a focus on reward circuitry (2019) · cites this paper as [20]
Cites
Introduction to Reinforcement Learning
Sutton, R. S., & Barto, A. G. (1998) · The MIT Press eBooks · Cited by 6,855 · see citing works
What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?
Berridge, K. C., & Robinson, T. E. (1998) · Brain Research Reviews · doi:10.1016/s0165-0173(98)00019-8 · Cited by 4,127 · see citing works
Olds, J., & Milner, P. (1954) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0058775 · Cited by 3,176 · see citing works
Getting formal with dopamine and reward
Schultz, W. (2002) · Neuron · doi:10.1016/s0896-6273(02)00967-4 · Cited by 2,574 · see citing works
Self-citationA Note on the Pure Theory of Consumer's Behaviour
Samuelson, P. A. (1938) · Economica · doi:10.2307/2548836 · Cited by 2,342 · see citing works
Barto, A. (1998) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)38315-5 · Cited by 2,172 · see citing works
Learning and Expectations in Macroeconomics
Evans, G. W., & Honkapohja, S. (2001) · Princeton University Press eBooks · doi:10.1515/9781400824267 · Cited by 2,139 · see citing works
Dissociable 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
Erev, I., & Roth, A. E. (1998) · American Economic Review · Cited by 1,794 · see citing works
Temporal difference models and reward-related learning in the human brain
O'Doherty, J. P., Dayan, P., Friston, K., Critchley, H., & Dolan, R. J. (2003) · Neuron · doi:10.1016/s0896-6273(03)00169-7 · Cited by 1,522 · see citing works
Midbrain dopamine neurons encode a quantitative reward prediction error signal
Bayer, H. M., & Glimcher, P. W. (2005) · Neuron · doi:10.1016/j.neuron.2005.05.020 · Cited by 1,304 · see citing works
Schultz, W., Apicella, P., & Ljungberg, T. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-03-00900.1993 · Cited by 1,291 · see citing works
Self-citationDopamine reward prediction-error signalling: A two-component response
Schultz, W. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2015.26 · Cited by 1,036 · see citing works
Self-citationComputational roles for dopamine in behavioural control
Montague, P. R., Hyman, S. E., & Cohen, J. D. (2004) · Nature · doi:10.1038/nature03015 · Cited by 966 · see citing works
Grace, A. A., & Bunney, B. S. (1983) · Neuroscience · doi:10.1016/0306-4522(83)90135-5 · Cited by 937 · see citing works
The short-latency dopamine signal: a role in discovering novel actions?
Redgrave, P., & Gurney, K. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn2022 · Cited by 762 · see citing works
Topological methods in cardinal utility theory
Debreu, G., Debreu, G., & Hildenbrand, W. (2008) · Mathematical Economics · doi:10.1017/ccol052123736x.010 · Cited by 627 · see citing works
A mathematical model for simple learning.
Bush, R. R., & Mosteller, F. C. (1951) · Psychological Review · doi:10.1037/h0054388 · Cited by 590 · see citing works
Importance of unpredictability for reward responses in primate dopamine neurons
Mirenowicz, J., & Schultz, W. (1994) · Journal of Neurophysiology · doi:10.1152/jn.1994.72.2.1024 · Cited by 544 · see citing works
Self-citationAddiction as a Computational Process Gone Awry
Redish, A. D. (2004) · Science · doi:10.1126/science.1102384 · Cited by 534 · see citing works
(1997) · The MIT Press eBooks · doi:10.7551/mitpress/3917.003.0017 · Cited by 497 · see citing works
Decisions uncertainty. and the brain: The science of neuroeconomics
(2003) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(03)90161-1 · Cited by 425 · see citing works
Individual Learning in Normal Form Games: Some Laboratory Results
Cheung, Y., & Friedman, D. (1997) · Games and Economic Behavior · doi:10.1006/game.1997.0544 · Cited by 361 · see citing works
An fMRI study of reward-related probability learning
Delgado, M. R., Miller, M. M., Inati, S., & Phelps, E. A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.10.002 · Cited by 337 · see citing works
Additive Representations of Preferences: A New Foundation of Decision Analysis
Wakker, P. P. (1988) · Medical Entomology and Zoology · Cited by 336 · see citing works
Human striatal response to salient nonrewarding stimuli
Zink, C. F., Pagnoni, G., Martin, M. E., Dhamala, M., & Berns, G. S. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-22-08092.2003 · Cited by 312 · 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
Corbett, D., & Wise, R. A. (1980) · Brain Research · doi:10.1016/0006-8993(80)90666-6 · Cited by 264 · see citing works
Dopamine Neuron-Specific Optogenetic Stimulation in Rhesus Macaques
Stauffer, W. R., Lak, A., Yang, A., Borel, M., Paulsen, O., Boyden, E. S., & Schultz, W. (2016) · Cell · doi:10.1016/j.cell.2016.08.024 · Cited by 256 · see citing works
Self-citationWhen Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect
Charness, G. B., & Levin, D. (2005) · American Economic Review · doi:10.1257/0002828054825583 · Cited by 245 · see citing works
Statistics of Midbrain Dopamine Neuron Spike Trains in the Awake Primate
Bayer, H. M., Lau, B., & Glimcher, P. W. (2007) · Journal of Neurophysiology · doi:10.1152/jn.01140.2006 · Cited by 184 · see citing works
End behavior in sequences of finite prisoner's dilemma supergames
Selten, R., & Stoecker, R. (1983) · Cited by 169 · see citing works
Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element
Barto, A. G., & Sutton, R. S. (1982) · Behavioural Brain Research · doi:10.1016/0166-4328(82)90001-8 · Cited by 106 · see citing works
Elements of a Theory of Inexact Measurement
Adams, E. W. (1965) · Philosophy of Science · doi:10.1086/288044 · Cited by 103 · see citing works
Predicting How People Play Games: A Simple Dynamic Model of Choice
Sarin, R., & Vahid, F. (2001) · Games and Economic Behavior · doi:10.1006/game.1999.0783 · Cited by 97 · see citing works
Experience-Weighted Attraction Learning in Games: A Unifying ApproachPreprint
Camerer, C., & Ho, T. (1997) · RePEc: Research Papers in Economics · Cited by 67 · see citing works
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Rolls, E. T., Cheng, W., & Feng, J. (2020) · Brain Communications · doi:10.1093/braincomms/fcaa196 · Cited by 474 · see citing works
“Liking” and “wanting” in eating and food reward: Brain mechanisms and clinical implications
Morales, I., & Berridge, K. C. (2020) · Physiology & Behavior · doi:10.1016/j.physbeh.2020.113152 · Cited by 346 · see citing works
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Solié, C., Girard, B., Righetti, B., Tapparel, M., & Bellone, C. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00972-9 · Cited by 186 · see citing works
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Are prediction error modifications domain specific in autism but domain general in ADHD?
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“Reward prediction errors are caused by differences between expected and received rewards and can be positive or negative, depending on whether the reward exceeds or fails to meet expectations, respectively ( Schultz, 2017).”
- Authors
- Schultz, W.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Schultz, Wolfram
- ORCID
- Schultz, Wolfram
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2017-05
- Volume
- 27
- Issue
- 10
- Pages
- R369-R371
- ISSN
- 0960-9822 (ISSN-L)
- OpenAlex
- W2618739337
- Cited by
- 177
- References
- 36
- Citations by year
- 2026: 18 · 2025: 33 · 2024: 16 · 2023: 27 · 2022: 17 · 2021: 20 · 2020: 19 · 2019: 13 · 2018: 11 · 2017: 2
- FWCI
- 6.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Biology (publishedVersion)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- reward prediction error, dopaminergic neurons, decision-making, reinforcement learning, basal ganglia, basal forebrain
- MeSH terms
- Decision Making, Dopamine, Humans, Mental Processes, Reward, Dopaminergic Neurons
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