Cited by 597Neurotransmitter Receptor Influence on BehaviorNeural and Behavioral Psychology StudiesNeural dynamics and brain function

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

Dopamine reward prediction error coding

Open access

Schultz, Wolfram·2016·Dialogues in Clinical Neuroscience

DOI 10.31887/dcns.2016.18.1/wschultzPMC PMC4826767

Open this paper in CoChat — free account

Abstract

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.31887/dcns.2016.18.1/wschultz

Cites

37 of 37 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects
Rao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483
Predictive reward signal of dopamine neurons
Schultz, W. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.1 · Cited by 4,564
Increasing risk: I. A definition
Rothschild, M., & Stiglitz, J. (1970) · Journal of Economic Theory · doi:10.1016/0022-0531(70)90038-4 · Cited by 3,760
Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain.
Olds, J., & Milner, P. (1954) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0058775 · Cited by 3,176
Psychosis as a state of aberrant salience: a framework linking biology, phenomenology and pharmacology in schizophrenia
Kapur, S. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.1.13 · Cited by 2,813
Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans
Pessiglione, M., Seymour, B., Flandin, G., Dolan, R. J., & Frith, C. D. (2006) · Nature · doi:10.1038/nature05051 · Cited by 1,584
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
Toward a modern theory of adaptive networks: Expectation and prediction.
Sutton, R. S., & Barto, A. G. (1981) · Psychological Review · doi:10.1037/0033-295x.88.2.135 · Cited by 1,450
Two types of dopamine neuron distinctly convey positive and negative motivational signals
Matsumoto, M., & Hikosaka, O. (2009) · Nature · doi:10.1038/nature08028 · Cited by 1,378

Flagged first, then by citations

Show all 37 references

Research works printed but not linked: 3

Pavlov PI., 1927, Conditioned Reflexes. London, UK: Oxford University Press:
Rescorla RA., 1972, Classical Conditioning II: Current Research and Theory. New York, NY: Appleton Century Crofts:, 64
von Neumann J., 1944, The Theory of Games and Economic Behavior. Princeton, NJ: Princeton University Press:

Sorted by citations

Schizophrenia
Jauhar, S., Johnstone, M., & McKenna, P. J. (2022) · The Lancet · doi:10.1016/s0140-6736(21)01730-x · Cited by 1,116
The entropic brain - revisited
Carhart-Harris, R. L. (2018) · Neuropharmacology · doi:10.1016/j.neuropharm.2018.03.010 · Cited by 522
Neural Circuitry of Reward Prediction Error
Watabe-Uchida, M., Eshel, N., & Uchida, N. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031109 · Cited by 437
Disruption of Reward Processing in Addiction: An Image-Based Meta-analysis of Functional Magnetic Resonance Imaging Studies
Luijten, M., Schellekens, A. F., Kühn, S., Machielse, M. W. J., & Sescousse, G. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.3084 · Cited by 402
Dopamine: The Neuromodulator of Long-Term Synaptic Plasticity, Reward and Movement Control
Speranza, L., di Porzio, U., Viggiano, D., Donato, A. D., & Volpicelli, F. (2021) · Cells · doi:10.3390/cells10040735 · Cited by 472
Emotion, motivation, decision-making, the orbitofrontal cortex, anterior cingulate cortex, and the amygdala
Rolls, E. T. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02644-9 · Cited by 356
Reinforcement learning in artificial and biological systems
Neftci, E. O., & Averbeck, B. B. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0025-4 · Cited by 268
What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation
Klaus, A., Alves da Silva, J., & Costa, R. M. (2019) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031033 · Cited by 284
Clinical evaluation of adhesively placed Cerec endo-crowns after 2 years--preliminary results.
Bindl, A., & MÖRMANN, W. H. (1999) · PubMed · Cited by 279
Amygdala Reward Neurons Form and Store Fear Extinction Memory
Zhang, X., Kim, J., & Tonegawa, S. (2019) · Neuron · doi:10.1016/j.neuron.2019.12.025 · Cited by 280
Circuit Mechanisms of Reward, Anhedonia, and Depression
Höflich, A., Michenthaler, P., Kasper, S., & Lanzenberger, R. (2019) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyy081 · Cited by 253
The Hard Problem of Consciousness and the Free Energy Principle
Solms, M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02714 · Cited by 239
“Panksepp (1998) and Schultz (2016) offer distinctly different accounts of the role played by dopamine. error” cycle that codes ongoing learning from experience (see Schultz, 2016).”
Background
Chronic Stress Induces Activity, Synaptic, and Transcriptional Remodeling of the Lateral Habenula Associated with Deficits in Motivated Behaviors
Cerniauskas, I., Winterer, J., de Jong, J. W., Lukacsovich, D., Yang, H., Khan, F., Peck, J. R., Obayashi, S. K., Lilascharoen, V., Lim, B. K., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.09.005 · Cited by 187
Separate neural representations of prediction error valence and surprise: Evidence from an fMRI meta‐analysis
Fouragnan, E., Retzler, C., & Philiastides, M. G. (2018) · Human Brain Mapping · doi:10.1002/hbm.24047 · Cited by 176
The effects of early life stress on reward processing
Novick, A. M., Levandowski, M. L., Laumann, L. E., Philip, N. S., Price, L. H., & Tyrka, A. R. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.02.002 · Cited by 192
“actual reward outcome, allows for dynamic learning from experience and updates in reward expectations (Gradin et al., 2011; Schultz, 2016).”
Background
Optimizing exposure therapy with an inhibitory retrieval approach and the OptEx Nexus
Craske, M. G., Treanor, M., Zbozinek, T. D., & Vervliet, B. (2022) · Behaviour Research and Therapy · doi:10.1016/j.brat.2022.104069 · Cited by 195
Recent advances in the application of predictive coding and active inference models within clinical neuroscience
Smith, R., Badcock, P., & Friston, K. J. (2021) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13138 · Cited by 174
Modulating the Neuromodulators: Dopamine, Serotonin, and the Endocannabinoid System
Peters, K. Z., Cheer, J. F., & Tonini, R. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.02.001 · Cited by 180
Autism-linked dopamine transporter mutation alters striatal dopamine neurotransmission and dopamine-dependent behaviors
DiCarlo, G. E., Aguilar, J. I., Matthies, H. J. G., Harrison, F. E., Bundschuh, K. E., West, A. M., Hashemi, P., Herborg, F., Rickhag, M., Chen, H., et al. (2019) · Journal of Clinical Investigation · doi:10.1172/jci127411 · Cited by 150
Updates in Motor Learning: Implications for Physical Therapist Practice and Education
Leech, K. A., Roemmich, R. T., Gordon, J., Reisman, D. S., & Cherry‐Allen, K. M. (2021) · Physical Therapy · doi:10.1093/ptj/pzab250 · Cited by 172
Multiple Motor Learning Processes in Humans: Defining Their Neurophysiological Bases
Spampinato, D. A., & Celnik, P. A. (2020) · The Neuroscientist · doi:10.1177/1073858420939552 · Cited by 170
Dopamine and addiction: what have we learned from 40 years of research
Solinas, M., Belujon, P., Fernagut, P., Jaber, M., & Thiriet, N. (2018) · Journal of Neural Transmission · doi:10.1007/s00702-018-1957-2 · Cited by 163
Hungry brains: A meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals
Devoto, F., Zapparoli, L., Bonandrini, R., Berlingeri, M., Ferrulli, A., Luzi, L., Banfi, G., & Paulesu, E. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.07.017 · Cited by 140
Untitled work
(2018) · UCL Discovery (University College London) · Cited by 145
Individual differences in the neuropsychopathology of addiction
George, O., & Koob, G. F. (2017) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2017.19.3/gkoob · Cited by 152
Hedonic Eating and the “Delicious Circle”: From Lipid-Derived Mediators to Brain Dopamine and Back
Coccurello, R., & Maccarrone, M. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00271 · Cited by 143
Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making
Chakroun, K., Mathar, D., Wiehler, A., Ganzer, F., & Peters, J. (2020) · eLife · doi:10.7554/elife.51260 · Cited by 131
Pain induces adaptations in ventral tegmental area dopamine neurons to drive anhedonia-like behavior
Markovic, T., Pedersen, C. E., Massaly, N., Vachez, Y. M., Ruyle, B. C., Murphy, C. A., Abiraman, K., Shin, J. H., Garcia, J. J., Yoon, H. J., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00924-3 · Cited by 129
Reinforcement-learning in fronto-striatal circuits
Averbeck, B. B., & O’Doherty, J. P. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01108-0 · Cited by 132
Memory and Reward-Based Learning: A Value-Directed Remembering Perspective
Knowlton, B. J., & Castel, A. D. (2022) · Annual Review of Psychology · doi:10.1146/annurev-psych-032921-050951 · Cited by 115
Integrative Hedonic and Homeostatic Food Intake Regulation by the Central Nervous System: Insights from Neuroimaging
Campos, A., Port, J. D., & Acosta, A. J. (2022) · Brain Sciences · doi:10.3390/brainsci12040431 · Cited by 126
Amygdala-Midbrain Connections Modulate Appetitive and Aversive Learning
Steinberg, E. E., Gore, F., Heifets, B. D., Taylor, M. D., Norville, Z. C., Beier, K. T., Földy, C., Lerner, T. N., Luo, L., Deisseroth, K. A., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.03.016 · Cited by 120
Complementary neural circuits for divergent effects of oxytocin: social approach versus social anxiety
Steinman, M. Q., Duque-Wilckens, N., & Trainor, B. C. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.10.008 · Cited by 105
Transient and Persistent Representations of Odor Value in Prefrontal Cortex
Wang, P. Y., Boboilă, C., Chin, M., Higashi-Howard, A., Shamash, P., Wu, Z., Stein, N. P., Abbott, L. F., & Axel, R. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.033 · Cited by 109
Dopamine, Prediction Error and Beyond
Diederen, K. M. J., & Fletcher, P. C. (2021) · The Neuroscientist · doi:10.1177/1073858420907591 · Cited by 106
Mapping adolescent reward anticipation, receipt, and prediction error during the monetary incentive delay task
Cao, Z., Bennett, M., Orr, C., Icke, I., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Bromberg, U., Büchel, C., Quinlan, E. B., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24370 · Cited by 109
Learning to lose control: A process-based account of behavioral addiction
Perales, J. C., King, D. L., Navas, J. F., Schimmenti, A., Sescousse, G., Starcevic, V., van Holst, R. J., & Billieux, J. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.12.025 · Cited by 101
Roles of the medial and lateral orbitofrontal cortex in major depression and its treatment
Zhang, B., Rolls, E. T., Wang, X., Xie, C., Cheng, W., & Feng, J. (2024) · Molecular Psychiatry · doi:10.1038/s41380-023-02380-w · Cited by 107
The locus coeruleus broadcasts prediction errors across the cortex to promote sensorimotor plasticity
Jordan, R., & Keller, G. B. (2023) · eLife · doi:10.7554/elife.85111 · Cited by 127
The cerebellum directly modulates the substantia nigra dopaminergic activity
Washburn, S., Oñate, M., Yoshida, J., Vera, J. R., Bhuvanasundaram, R., Khatami, L., Farzan Nadim, A., & Khodakhah, K. (2024) · Nature Neuroscience · doi:10.1038/s41593-023-01560-9 · Cited by 93
Dystonia and dopamine: From phenomenology to pathophysiology
Ribot, B., Aupy, J., Vidailhet, M., Mazère, J., Pisani, A., Bézard, E., Guehl, D., & Burbaud, P. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101678 · Cited by 96
Embodying addiction: A predictive processing account
Miller, M., Kiverstein, J. D., & Rietveld, E. (2019) · Brain and Cognition · doi:10.1016/j.bandc.2019.105495 · Cited by 89
“Stopping for knowledge”: The sense of beauty in the perception-action cycle
Sarasso, P., Neppi-Mòdona, M., Sacco, K., & Ronga, I. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.004 · Cited by 91
Escaping Paternalism
Rizzo, M. J., & Whitman, G. (2019) · Cambridge University Press eBooks · doi:10.1017/9781139061810 · Cited by 132
An insight-related neural reward signal
Oh, Y., Chesebrough, C., Erickson, B. A., Zhang, F., & Kounios, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116757 · Cited by 89
Association of Brain Reward Response With Body Mass Index and Ventral Striatal-Hypothalamic Circuitry Among Young Women With Eating Disorders
Frank, G., Shott, M. E., Stoddard, J., Swindle, S., & Pryor, T. L. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2021.1580 · Cited by 77
A gateway to consumers' minds: Achievements, caveats, and prospects of electroencephalography‐based prediction in neuromarketing
Hakim, A., & Levy, D. J. (2018) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1485 · Cited by 85
Place field assembly distribution encodes preferred locations
Mamad, O., Stumpp, L., McNamara, H. M., Ramakrishnan, C., Deisseroth, K., Reilly, R. B., & Tsanov, M. (2017) · PLoS Biology · doi:10.1371/journal.pbio.2002365 · Cited by 73
Plastic and stimulus-specific coding of salient events in the central amygdala
Yang, T., Yu, K., Zhang, X., Xiao, X., Chen, X., Fu, Y., & Li, B. (2023) · Nature · doi:10.1038/s41586-023-05910-2 · Cited by 73
Primate optogenetics: Progress and prognosis
El-Shamayleh, Y., & Horwitz, G. D. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902284116 · Cited by 78
Feature-specific prediction errors and surprise across macaque fronto-striatal circuits
Oemisch, M., Westendorff, S., Azimi, M., Hassani, S. A., Ardid, S., Tiesinga, P. H. E., & Womelsdorf, T. (2019) · Nature Communications · doi:10.1038/s41467-018-08184-9 · Cited by 72
The empirical status of predictive coding and active inference
Hodson, R., Mehta, M., & Smith, R. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105473 · Cited by 69
Prediction Error Representation in Individuals With Generalized Anxiety Disorder During Passive Avoidance
White, S. F., Geraci, M. F., Lewis, E., Leshin, J. C., Teng, C. Y., Averbeck, B. B., Meffert, H., Monique Ernst, D., Blair, J., Grillon, C., et al. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.15111410 · Cited by 68
Differential mechanisms underlie trace and delay conditioning in Drosophila
Grover, D., Chen, J., Xie, J. L., Li, J., Changeux, J., & Greenspan, R. J. (2022) · Nature · doi:10.1038/s41586-022-04433-6 · Cited by 63
The Reward System and Post-Traumatic Stress Disorder: Does Trauma Affect the Way We Interact With Positive Stimuli?
Seidemann, R., Duek, O. A., Jia, R., Levy, I., & Harpaz‐Rotem, I. (2021) · Chronic Stress · doi:10.1177/2470547021996006 · Cited by 69
Effect of sleep deprivation on emotional working memory
Gerhardsson, A., Åkerstedt, T., Axelsson, J., Fischer, H., Lekander, M., & Schwarz, J. (2018) · Journal of Sleep Research · doi:10.1111/jsr.12744 · Cited by 65
Activation of Nigrostriatal Dopamine Neurons during Fear Extinction Prevents the Renewal of Fear
Bouchet, C. A., Miner, M. A., Loetz, E. C., Rosberg, A. J., Hake, H. S., Farmer, C. E., Ostrovskyy, M., Gray, N. A., & Greenwood, B. N. (2017) · Neuropsychopharmacology · doi:10.1038/npp.2017.235 · Cited by 59
The neuroscience of active learning and direct instruction
Dubinsky, J. M., & Hamid, A. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105737 · Cited by 121
Rethinking delusions: A selective review of delusion research through a computational lens
Ashinoff, B. K., Singletary, N. M., Baker, S. C., & Horga, G. (2021) · Schizophrenia Research · doi:10.1016/j.schres.2021.01.023 · Cited by 61
Neuroimaging reward, craving, learning, and cognitive control in substance use disorders: review and implications for treatment
Tanabe, J., Regner, M. F., Sakai, J. T., Martínez, D., & Gowin, J. L. (2019) · British Journal of Radiology · doi:10.1259/bjr.20180942 · Cited by 58
Dopamine modulates subcortical responses to surprising sounds
Valdés‐Baizabal, C., Carbajal, G. V., Pérez‐González, D., & Malmierca, M. S. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3000744 · Cited by 58
Disruptive Mood Dysregulation Disorder (DMDD): An RDoC perspective
Meyers, E., DeSerisy, M., & Roy, A. K. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.08.007 · Cited by 58
Ghrelin Enhances Food Odor Conditioning in Healthy Humans: An fMRI Study
Han, J. E., Frasnelli, J., Zeighami, Y., Larcher, K. M.-H., Boyle, J., McConnell, T., Malik, S., Jones‐Gotman, M., & Dagher, A. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.11.026 · Cited by 56
Learning Similar Actions by Reinforcement or Sensory-Prediction Errors Rely on Distinct Physiological Mechanisms
Uehara, S., Mawase, F., & Celnik, P. A. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx214 · Cited by 52
Circuits that encode and guide alcohol-associated preference
Scaplen, K. M., Talay, M., Salamon, S., Nuñez, K. M., Waterman, A. G., Gang, S., Song, S. L., Barnea, G., & Kaun, K. R. (2020) · eLife · doi:10.7554/elife.48730 · Cited by 61
Using pharmacological manipulations to study the role of dopamine in human reward functioning: A review of studies in healthy adults
Webber, H. E., Lopez-Gamundi, P., Stamatovich, S. N., de Wit, H., & Wardle, M. C. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.11.004 · Cited by 51
The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again
Safron, A. (2021) · Entropy · doi:10.3390/e23060783 · Cited by 59
Identification of visual cortex cell types and species differences using single-cell RNA sequencing
Wei, J.-R., Hao, Z.-Z., Xu, C., Huang, M., Tang, L., Xu, N., Liu, R., Shen, Y., Teichmann, S. A., Miao, Z., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34590-1 · Cited by 61
Serotonin release measured in the human brain: a PET study with [11C]CIMBI-36 and d-amphetamine challenge
Erritzøe, D., Ashok, A. H., Searle, G. E., Colasanti, A., Turton, S., Lewis, Y. L., Huiban, M., Moz, S., Passchier, J., Saleem, A., et al. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-019-0567-5 · Cited by 54
A neurobiological perspective on social influence: Serotonin and social adaptation
Duerler, P., Vollenweider, F. X., & Preller, K. H. (2022) · Journal of Neurochemistry · doi:10.1111/jnc.15607 · Cited by 52
The Genetically Informed Neurobiology of Addiction (GINA) model
Bogdan, R., Hatoum, A. S., Johnson, E. C., & Arpana Agrawal, A. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00656-8 · Cited by 56
Reward Learning Through the Lens of RDoC: a Review of Theory, Assessment, and Empirical Findings in the Eating Disorders
Schaefer, L. M., & STEINGLASS, J. E. (2021) · Current Psychiatry Reports · doi:10.1007/s11920-020-01213-9 · Cited by 51
Striatal dopamine supports reward expectation and learning: A simultaneous PET/fMRI study
Calabro, F. J., Montez, D. F., Larsen, B., Laymon, C. M., Foran, W., Hallquist, M. N., Price, J. C., & Luna, B. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119831 · Cited by 56
Active inference models do not contradict folk psychology
Smith, R. S., Ramstead, M. J. D., & Kiefer, A. B. (2022) · Synthese · doi:10.1007/s11229-022-03480-w · Cited by 55
Two what, two where, visual cortical streams in humans
Rolls, E. T. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105650 · Cited by 48
Humans with latent toxoplasmosis display altered reward modulation of cognitive control
Stock, A., Dajkic, D., Köhling, H.-L., von Heinegg, E. H., Fiedler, M., & Beste, C. (2017) · Scientific Reports · doi:10.1038/s41598-017-10926-6 · Cited by 46
Can rhythm-mediated reward boost learning, memory, and social connection? Perspectives for future research
Fiveash, A., Ferreri, L., Bouwer, F. L., Kösem, A., Moghimi, S., Ravignani, A., Keller, P. E., & Tillmann, B. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105153 · Cited by 58
Resolving the Delusion Paradox
Petrović, P., & Sterzer, P. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbad084 · Cited by 45
Towards a Better Understanding of Consumer Behavior: Marginal Utility as a Parameter in Neuromarketing Research
Alvino, L., Constantinides, E., & Franco, M. (2018) · International Journal of Marketing Studies · doi:10.5539/ijms.v10n1p90 · Cited by 47
Escaping Paternalism: Rationality, Behavioral Economics, and Public Policy
Rizzo, M. J., & Whitman, G. (2019) · Cited by 42
Dopamine transporter silencing in the rat: systems-level alterations in striato-cerebellar and prefrontal-midbrain circuits
Reinwald, J., Gass, N., Mallien, A. S., Sartorius, A., Becker, R., Sack, M., Falfán-Melgoza, C., von Hohenberg, C. C., Leo, D., Pfeiffer, N., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01471-4 · Cited by 43
Credit Assignment in a Motor Decision Making Task Is Influenced by Agency and Not Sensory Prediction Errors
Parvin, D. E., McDougle, S. D., Taylor, J. A., & Ivry, R. B. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.3601-17.2018 · Cited by 41
A complementary learning systems approach to temporal difference learning
Blakeman, S., & Mareschal, D. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.10.011 · Cited by 41
Neural bases of frustration-aggression theory: A multi-domain meta-analysis of functional neuroimaging studies
Dugre, J. R., & Potvin, S. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.03.005 · Cited by 47
Time of Day Differences in Neural Reward Functioning in Healthy Young Men
Byrne, J. E. M., Hughes, M. E., Rossell, S. L., Johnson, S. L., & Murray, G. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0918-17.2017 · Cited by 42
Neurobehavioral Effects of Restricted and Unpredictable Environmental Enrichment in Rats
Rojas‐Carvajal, M., Sequeira‐Cordero, A., & Brenes, J. C. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00674 · Cited by 42
A predictive coding framework for understanding major depression
Gilbert, J. R., Wusinich, C., & Zarate, C. A. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.787495 · Cited by 38
Inhibitory Plasticity of Mesocorticolimbic Circuits in Addiction and Mental Illness
Ostroumov, A., & Dani, J. A. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.07.014 · Cited by 43
A Focus on Reward Prediction and the Lateral Habenula: Functional Alterations and the Behavioral Outcomes Induced by Drugs of Abuse
Graziane, N., Neumann, P. A., & Dong, Y. (2018) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2018.00012 · Cited by 40
Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal
Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101901 · Cited by 38
Emerging Treatments in Schizophrenia
Correll, C. U., Abi‐Dargham, A., & Howes, O. D. (2022) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.su21024ip1 · Cited by 41
Re-examining the role of ventral tegmental area dopaminergic neurons in motor activity and reinforcement by chemogenetic and optogenetic manipulation in mice
Jing, M., Han, X., Zhao, T.-Y., Wang, Z., Lu, G.-Y., Wu, N., Song, R., & Li, J. (2019) · Metabolic Brain Disease · doi:10.1007/s11011-019-00442-z · Cited by 33
Relief of neuropathic pain by cell-specific manipulation of nucleus accumbens dopamine D1- and D2-receptor-expressing neurons
Sato, D., Narita, M., Hamada, Y., Mori, T., Tanaka, K., Tamura, H., Yamanaka, A., Matsui, R., Watanabe, D., Suda, Y., et al. (2022) · Molecular Brain · doi:10.1186/s13041-021-00896-2 · Cited by 35
DNA Epigenetics in Addiction Susceptibility
Kaplan, G., Xu, H., Abreu, K., & Feng, J. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.806685 · Cited by 34
Ingestion of artificial sweeteners leads to caloric frustration memory in Drosophila
Musso, P., Lampin-Saint-Amaux, A., Tchénio, P., & Préat, T. (2017) · Nature Communications · doi:10.1038/s41467-017-01989-0 · Cited by 40
Cannabinoids, reward processing, and psychosis
Gunasekera, B., Diederen, K. M. J., & Bhattacharyya, S. (2021) · Psychopharmacology · doi:10.1007/s00213-021-05801-2 · Cited by 35
The learning of prospective and retrospective cognitive maps within neural circuits
Namboodiri, V. M. K., & Stuber, G. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.09.034 · Cited by 32
A mechanistic model of ADHD as resulting from dopamine phasic/tonic imbalance during reinforcement learning
Véronneau-Veilleux, F., Robaey, P., Ursino, M., & Nekka, F. (2022) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2022.849323 · Cited by 32
Health, pleasure, and fullness: changing mindset affects brain responses and portion size selection in adults with overweight and obesity
Veit, R., Horstman, L. I., Hege, M. A., Heni, M., Rogers, P. J., Brunstrom, J. M., Fritsche, A., Preissl, H. T., & Kullmann, S. (2019) · International Journal of Obesity · doi:10.1038/s41366-019-0400-6 · Cited by 33
The Efficacy of Cognitive Videogame Training for ADHD and What FDA Clearance Means for Clinicians
Evans, S. W., Beauchaine, T. P., Chronis-Tuscano, A., Becker, S. P., Chacko, A., Gallagher, R., Hartung, C. M., Kofler, M. J., Schultz, B. K., Tamm, L., et al. (2021) · Evidence-Based Practice in Child and Adolescent Mental Health · doi:10.1080/23794925.2020.1859960 · Cited by 32

Authors: Schultz, W.
Affiliations: University of Cambridge (GB)
Corresponding author: Schultz, Wolfram
ORCID: Schultz, Wolfram
Venue: Dialogues in Clinical Neuroscience
Publisher: Informa UK Limited
Published: 2016-03-31
Volume: 18
Issue: 1
Pages: 23-32
ISSN: 1294-8322 (ISSN-L)
1958-5969
DOI: 10.31887/dcns.2016.18.1/wschultz
PMC: PMC4826767
OpenAlex: W2419438565
Cited by: 597
References: 37
Citations by year: 2026: 84 · 2025: 83 · 2024: 77 · 2023: 68 · 2022: 64 · 2021: 53 · 2020: 36 · 2019: 62 · 2018: 45 · 2017: 20 · 2016: 4
FWCI: 24.37
Type: journal article
Language: en
Open access: diamond
doi.org
Licence: cc-by-nc-nd
creativecommons.org/licenses/by-nc-nd/3.0/ (vor)
Locations: Dialogues in Clinical Neuroscience (publishedVersion, cc-by-nc-nd)
Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Funders: Wellcome Trust (093875)
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 › Neural dynamics and brain function
Keywords: dopamine, reward prediction error, midbrain dopaminergic neurons, reward learning, drug addiction, neuroplasticity, striatum, amygdala, frontal cortex
MeSH terms: Animals, Brain, Dopamine, Forecasting, Humans, Learning, Nerve Net, Neuronal Plasticity, Reward

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Dopamine reward prediction error coding

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks