The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
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
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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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