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A cellular mechanism of reward-related learning
Abstract
Positive reinforcement helps to control the acquisition of learned behaviours. Here we report a cellular mechanism in the brain that may underlie the behavioural effects of positive reinforcement. We used intracranial self-stimulation (ICSS) as a model of reinforcement learning, in which each rat learns to press a lever that applies reinforcing electrical stimulation to its own substantia nigra. The outputs from neurons of the substantia nigra terminate on neurons in the striatum in close proximity to inputs from the cerebral cortex on the same striatal neurons. We measured the effect of substantia nigra stimulation on these inputs from the cortex to striatal neurons and also on how quickly the rats learned to press the lever. We found that stimulation of the substantia nigra (with the optimal parameters for lever-pressing behaviour) induced potentiation of synapses between the cortex and the striatum, which required activation of dopamine receptors. The degree of potentiation within ten minutes of the ICSS trains was correlated with the time taken by the rats to learn ICSS behaviour. We propose that stimulation of the substantia nigra when the lever is pressed induces a similar potentiation of cortical inputs to the striatum, positively reinforcing the learning of the behaviour by the rats.
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“Gaming increases the release of striatal dopamine [47], [48], promoting long-term potentiation of neural connections within the striatum [49], which is suggested to improve motivation and one’s ability to learn [50] (e.g., during EF training).”
In the citing paper
“First, as noted, the phasic firing of dopamine neurons has been suggested as reporting the temporal difference prediction error for reward (Montague et al., 1996; Schultz et al., 1997) that underpins model-free evaluation and control via its influence over activity and plasticity (Reynolds et al., 2001; Frank, 2005).”
From Goals and Habits in the Brain (2013) · cites this paper as Reynolds et al., 2001
Citations
Cites
The rat brain in stereotaxic coordinates
Palkovits, M. (1983) · Neuropeptides · doi:10.1016/0143-4179(83)90049-5 · Cited by 28,959
The Rat Brain in Stereotaxic Coordinates
Paxinos, G., & Watson, C. (1983) · Elsevier eBooks · doi:10.1016/c2009-0-63235-9 · Cited by 28,585
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.09.030186.002041 · Cited by 8,527
Olds, J., & Milner, P. (1954) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0058775 · Cited by 3,176
A framework for mesencephalic dopamine systems based on predictive Hebbian learning
Montague, P., Dayan, P., & Sejnowski, T. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-05-01936.1996 · Cited by 2,066
Swanson, L. W. (1982) · Brain Research Bulletin · doi:10.1016/0361-9230(82)90145-9 · Cited by 1,718
Multiple reward signals in the brain
Schultz, W. (2000) · Nature Reviews Neuroscience · doi:10.1038/35044563 · Cited by 1,303
Smith, A. D., & Bolam, J. P. (1990) · Trends in Neurosciences · doi:10.1016/0166-2236(90)90106-k · Cited by 1,040
Preferential activation of midbrain dopamine neurons by appetitive rather than aversive stimuli
Mirenowicz, J., & Schultz, W. (1996) · Nature · doi:10.1038/379449a0 · Cited by 829
The origins of two-state spontaneous membrane potential fluctuations of neostriatal spiny neurons
Wilson, C. J., & Kawaguchi, Y. (1996) · Journal of Neuroscience · doi:10.1523/jneurosci.16-07-02397.1996 · Cited by 798
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Goerendt, I. K. (2003) · Brain · doi:10.1093/brain/awg035 · Cited by 100
Guthrie, M., Leblois, A., Garenne, A., & Boraud, T. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00026.2013 · Cited by 106
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O’Neill, M. J., & Brown, V. J. (2007) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2007.03.003 · Cited by 99
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McNaughton, N., & Gray, J. A. (2024) · doi:10.1093/oso/9780198843313.001.0001 · Cited by 99
Cardinal, R. N., & Cheung, T. H. C. (2005) · BMC Neuroscience · doi:10.1186/1471-2202-6-9 · Cited by 98
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Murray, J. M., & Escola, G. S. (2017) · eLife · doi:10.7554/elife.26084 · Cited by 102
Sammut, S., Dec, A. M., Mitchell, D., Linardakis, J., Ortigüela, M., & West, A. R. (2005) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300826 · Cited by 96
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Thiele, S. L., Chen, B., Lo, C., Gertler, T. S., Warre, R., Surmeier, D. J., Brotchie, J. M., & Nash, J. E. (2014) · Neurobiology of Disease · doi:10.1016/j.nbd.2014.08.006 · Cited by 86
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Byrne, J. H., LaBar, K. S., LeDoux, J. E., Schafe, G. E., & Thompson, R. F. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-397179-1.00020-8 · Cited by 74
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Cheng, R., Hakak, O. L., & Meck, W. H. (2007) · Psychopharmacology · doi:10.1007/s00213-007-0783-2 · Cited by 70
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Tan, H., Zavala, B., Pogosyan, A. H., Ashkan, K., Zrinzo, L. U., Foltynie, T., Limousin, P. D., & Brown, P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3414-14.2014 · Cited by 68
Schroll, H., Vitay, J., & Hamker, F. H. (2011) · Neural Networks · doi:10.1016/j.neunet.2011.10.008 · Cited by 70
Yamanaka, K., Hori, Y., Minamimoto, T., Yamada, H., Matsumoto, N., Enomoto, K., Aosaki, T., Graybiel, A. M., & Kimura, M. (2017) · Journal of Neural Transmission · doi:10.1007/s00702-017-1713-z · Cited by 69
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Rusu, S. I., & Pennartz, C. M. A. (2019) · Hippocampus · doi:10.1002/hipo.23167 · Cited by 63
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Horvitz, J. C. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2008.12.014 · Cited by 58
Jaramillo, S., Borges, K., & Zador, A. M. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4888-13.2014 · Cited by 58
Metadata
- Authors
- Reynolds, J. N. J., Hyland, B. I., & Wickens, J. R.
- Affiliations
- University of Otago (NZ)
- Corresponding author
- Wickens, Jeffery R.
- Venue
- Nature
- Published
- 2001-09
- Volume
- 413
- Issue
- 6851
- Pages
- 67-70
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2055523610
- Cited by
- 879
- References
- 33
- Citations by year
- 2026: 20 · 2025: 36 · 2024: 54 · 2023: 42 · 2022: 36 · 2021: 28 · 2020: 32 · 2019: 35 · 2018: 28 · 2017: 26 · 2016: 33 · 2015: 44 · 2014: 42 · 2013: 35 · 2012: 32
- FWCI
- 8.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Institut National de la Santé et de la Recherche Médicale
- Saint Petersburg State University
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- reward learning, positive reinforcement, intracranial self-stimulation, substantia nigra, striatum, synaptic potentiation, dopamine receptors, learning acquisition
- MeSH terms
- Animals, Brain, Cerebral Cortex, Corpus Striatum, Dopamine, Learning, Male, Models, Neurological, Neural Pathways, Neurons, Reinforcement, Psychology, Reward, Self Stimulation, Substantia Nigra, Synapses, Rats, Wistar, Rats
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 ›
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