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A cellular mechanism of reward-related learning

Reynolds, John N. J., Hyland, Brian I., Wickens, Jeffery R.·2001·Nature

DOI 10.1038/35092560

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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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Olds, J., & Milner, P. (1954) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0058775 · Cited by 3,176
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Authors: Reynolds, J. N. J., Hyland, B. I., & Wickens, J. R.
Affiliations: University of Otago (NZ)
Corresponding author: Wickens, Jeffery R.
ORCID: Reynolds, John N. J.
Hyland, Brian I.
Wickens, Jeffery R.
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2001-09
Volume: 413
Issue: 6851
Pages: 67-70
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/35092560
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

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