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Distributed Neural Representation of Expected Value
Open accessAbstract
Anticipated reward magnitude and probability comprise dual components of expected value (EV), a cornerstone of economic and psychological theory. However, the neural mechanisms that compute EV have not been characterized. Using event-related functional magnetic resonance imaging, we examined neural activation as subjects anticipated monetary gains and losses that varied in magnitude and probability. Group analyses indicated that, although the subcortical nucleus accumbens (NAcc) activated proportional to anticipated gain magnitude, the cortical mesial prefrontal cortex (MPFC) additionally activated according to anticipated gain probability. Individual difference analyses indicated that, although NAcc activation correlated with self-reported positive arousal, MPFC activation correlated with probability estimates. These findings suggest that mesolimbic brain regions support the computation of EV in an ascending and distributed manner: whereas subcortical regions represent an affective component, cortical regions also represent a probabilistic component, and, furthermore, may integrate the two.
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“and its activity may predict self-reports of positive affect (Knutson, Taylor, Kaufman, Peterson, & Glover, 2005).”
From Gender Differences in Emotion Regulation: An fMRI Study of Cognitive Reappraisal (2008) · cites this paper as Knutson, Taylor, Kaufman, Peterson, & Glover, 2005
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“With monetary rewards, research shows that ventral striatum activity can signal both anticipated reward magnitude and probability 56, 57.”
From The social brain and reward: Social information processing in the human striatum (2014) · cites this paper as [56]
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“Cued anticipation of monetary gains has been consistently found to recruit the VS, including the NAcc, with greater VS activity for more salient incentives (for example, $1 versus $5; [18]).”
From Social “wanting” dysfunction in autism: neurobiological underpinnings and treatment implications (2012) · cites this paper as [18]
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Incentive-elicited striatal activation in adolescent children of alcoholics
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Self-citationCingulate cortex: Diverging data from humans and monkeys
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Self-citation
Metadata
- Authors
- Knutson, B., Taylor, J., Kaufman, M., Peterson, R., & Glover, G.
- Affiliations
- Stanford University (US)
- Corresponding author
- Knutson, Brian
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2005-05-11
- Volume
- 25
- Issue
- 19
- Pages
- 4806-4812
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6724773
- OpenAlex
- W2163979049
- Cited by
- 955
- References
- 34
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 19 · 2023: 26 · 2022: 30 · 2021: 33 · 2020: 22 · 2019: 39 · 2018: 51 · 2017: 42 · 2016: 55 · 2015: 53 · 2014: 45 · 2013: 81 · 2012: 58
- FWCI
- 27.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Funders
- National Alliance for Research on Schizophrenia and Depression
- National Institute of Mental Health (R03MH066923)
- National Center for Research Resources (RR 09784, P41RR009784)
- 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
- expected value, reward anticipation, reward magnitude, reward probability, nucleus accumbens, mesolimbic system, monetary gains and losses, individual differences, probability estimation
- MeSH terms
- Adult, Brain Mapping, Female, Humans, Image Processing, Computer-Assisted, Functional Laterality, Magnetic Resonance Imaging, Male, Nucleus Accumbens, Oxygen, Photic Stimulation, Probability, Reference Values, Regression Analysis, Reward, Time Factors, Prefrontal Cortex
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