Neural Economics and the Biological Substrates of Valuation
Open accessAbstract
A recent flurry of neuroimaging and decision-making experiments in humans, when combined with single-unit data from orbitofrontal cortex, suggests major additions to current models of reward processing. We review these data and models and use them to develop a specific computational relationship between the value of a predictor and the future rewards or punishments that it promises. The resulting computational model, the predictor-valuation model (PVM), is shown to anticipate a class of single-unit neural responses in orbitofrontal and striatal neurons. The model also suggests how neural responses in the orbitofrontal-striatal circuit may support the conversion of disparate types of future rewards into a kind of internal currency, that is, a common scale used to compare the valuation of future behavioral acts or stimuli.
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Risk taking is associated with an increase in accumbens activity that is exaggerated in adolescents, relative to both children and adults.
“In contrast, risk taking is associated with an increase in accumbens activity (Kuhnen & Knutson 2005; Matthews et al. 2004; Montague & Berns 2002) that is exaggerated in adolescents, relative to both children and adults (Ernst et al. 2005; Galvan et al. 2006).”
From <i>The Adolescent Brain</i> (2008) · cites this paper as Montague & Berns 2002
A number of studies have shown increases in activity in the nucleus accumbens immediately prior to making risky choices on monetary-risk paradigms.
“A number of studies have shown increases in activity in the nucleus accumbens immediately prior to making risky choices on monetary-risk paradigms (Kuhnen & Knutson 2005; Matthews et al. 2004; Montague & Berns 2002)”
From <i>The Adolescent Brain</i> (2008) · cites this paper as Montague & Berns 2002
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Yarkoni, T., Gray, J. R., Chrastil, E. R., Barch, D. M., Green, L., & Braver, T. S. (2005) · Cognitive Brain Research · doi:10.1016/j.cogbrainres.2005.01.013 · Cited by 59 · see citing works
To be specific: The role of orbitofrontal cortex in signaling reward identity.
Howard, J. D., & Kahnt, T. (2021) · Behavioral Neuroscience · doi:10.1037/bne0000455 · Cited by 57 · see citing works
- Authors
- Montague, P. R., & Berns, G. S.
- Affiliations
- Baylor College of Medicine (US)
- Emory University (US)
- Corresponding author
- Montague, P.Read
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2002-10
- Volume
- 36
- Issue
- 2
- Pages
- 265-284
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2117403214
- Cited by
- 994
- References
- 8
- Citations by year
- 2026: 7 · 2025: 17 · 2024: 66 · 2023: 23 · 2022: 20 · 2021: 21 · 2020: 24 · 2019: 43 · 2018: 36 · 2017: 25 · 2016: 32 · 2015: 35 · 2014: 45 · 2013: 54 · 2012: 66
- FWCI
- 2.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institutes of Health (5r01mh061010-02)
- National Institute of Mental Health (R01 MH61010, R01MH52797, R01MH052797)
- National Institute on Drug Abuse (K08 DA00367, K08DA000367, R01-DA11723, R01DA011723)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- valuation, reward processing, orbitofrontal cortex, striatum, single-unit activity, computational model, prediction error, decision-making
- MeSH terms
- Animals, Brain, Choice Behavior, Forecasting, Humans, Models, Neurological, Neurons, 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.
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