Social and monetary reward learning engage overlapping neural substrates
Open accessAbstract
Learning to make choices that yield rewarding outcomes requires the computation of three distinct signals: stimulus values that are used to guide choices at the time of decision making, experienced utility signals that are used to evaluate the outcomes of those decisions and prediction errors that are used to update the values assigned to stimuli during reward learning. Here we investigated whether monetary and social rewards involve overlapping neural substrates during these computations. Subjects engaged in two probabilistic reward learning tasks that were identical except that rewards were either social (pictures of smiling or angry people) or monetary (gaining or losing money). We found substantial overlap between the two types of rewards for all components of the learning process: a common area of ventromedial prefrontal cortex (vmPFC) correlated with stimulus value at the time of choice and another common area of vmPFC correlated with reward magnitude and common areas in the striatum correlated with prediction errors. Taken together, the findings support the hypothesis that shared anatomical substrates are involved in the computation of both monetary and social rewards.
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The observation of social stimuli in general (e.g., smiling faces) increases activity in medial prefrontal cortex and striatum in cases where the social stimuli have a high value.
“The observation of social stimuli in general (e.g., smiling faces) increases activity in medial prefrontal cortex 33, 34 and striatum in cases where the social stimuli have a high value (e.g., participants will exert effort or pay to view an attractive face) 35–38.”
From The social brain and reward: Social information processing in the human striatum (2014) · cites this paper as [38]
The pattern of striatal activity while learning from social information resembles the reward prediction error learning signal exhibited in the striatum while learning from monetary or food rewards.
“This pattern of striatal activity while learning from social information resembles the reward prediction error learning signal exhibited in the striatum while learning from monetary or food rewards 38, 66, 67.”
From The social brain and reward: Social information processing in the human striatum (2014) · cites this paper as [38]
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- Authors
- Lin, A., Adolphs, R., & Rangel, A.
- Affiliations
- California Institute of Technology (US)
- Venue
- Social Cognitive and Affective Neuroscience
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03-22
- Volume
- 7
- Issue
- 3
- Pages
- 274-281
- ISSN
- 1749-5016 (ISSN-L)
- 1749-5024
- PMC
- PMC3304477
- OpenAlex
- W2157381246
- Cited by
- 351
- References
- 70
- Citations by year
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- FWCI
- 13.30
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Social Cognitive and Affective Neuroscience (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- National Science Foundation
- Gordon and Betty Moore Foundation
- National Institute on Aging (R21AG038866)
- National Institute of Mental Health
- 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
- reward learning, social reward, monetary rewards, stimulus value, prediction error, ventromedial prefrontal cortex, striatum, probabilistic choice, reward magnitude, neural correlates, decision-making
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Choice Behavior, Female, Humans, Image Processing, Computer-Assisted, Learning, Magnetic Resonance Imaging, Oxygen, Photic Stimulation, Reward, Social Behavior, Statistics as Topic, Time Factors, Young Adult
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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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