Computational roles for dopamine in behavioural control

Montague, P. Read; Hyman, Steven E.; Cohen, Jonathan D.

doi:10.1038/nature03015

Cited by 966Neurotransmitter Receptor Influence on BehaviorNeural and Behavioral Psychology StudiesReinforcement Learning in Robotics

Computational roles for dopamine in behavioural control

Montague, P. Read, Hyman, Steven E., Cohen, Jonathan D.·2004·Nature

DOI 10.1038/nature03015

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Abstract

Neuromodulators such as dopamine have a central role in cognitive disorders. In the past decade, biological findings on dopamine function have been infused with concepts taken from computational theories of reinforcement learning. These more abstract approaches have now been applied to describe the biological algorithms at play in our brains when we form value judgements and make choices. The application of such quantitative models has opened up new fields, ripe for attack by young synthesizers and theoreticians.

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The findings are consistent with different functions associated with distinct regions of the striatum: afferent projections to dorsal striatum are crucial for learning correct actions to maximize reward, whereas projections to ventral striatum including nucleus accumbens have a key function in reward prediction and pavlovian learning.
“These findings are consistent with the different functions associated with distinct regions of the striatum: afferent projections to dorsal striatum are thought to be crucial for learning correct actions so as to maximize reward, whereas projections to ventral striatum, including nucleus accumbens, have a key function in reward prediction and pavlovian learning18-20,23,24.”
From Empathic neural responses are modulated by the perceived fairness of others (2006) · cites this paper as [24]

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Authors: Montague, P. R., Hyman, S. E., & Cohen, J. D.
Affiliations: Baylor College of Medicine (US)
Harvard University (US)
University of Pittsburgh (US)
ORCID: Montague, P. Read
Hyman, Steven E.
Cohen, Jonathan D.
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2004-10
Volume: 431
Issue: 7010
Pages: 760-767
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature03015
OpenAlex: W2165368112
Semantic Scholar: 16cd7a24d117f61da645fba1b4cc31839dff2805
Cited by: 966
References: 77
Citations by year: 2026: 6 · 2025: 13 · 2024: 19 · 2023: 36 · 2022: 21 · 2021: 26 · 2020: 32 · 2019: 31 · 2018: 39 · 2017: 40 · 2016: 42 · 2015: 49 · 2014: 51 · 2013: 56 · 2012: 82
FWCI: 4.14
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)
UCL Discovery (University College London) (submittedVersion)
Topics: Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
Keywords: dopamine, neuromodulation, reinforcement learning, computational model, value judgments, decision-making, behavioral control, cognitive disorders
MeSH terms: Animals, Choice Behavior, Cognition, Dopamine, Humans, Learning, Models, Neurological, Schizophrenia, Substance-Related Disorders

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Computational roles for dopamine in behavioural control

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