Computational substrates of norms and their violations during social exchange
Open accessAbstract
Social norms in humans constrain individual behaviors to establish shared expectations within a social group. Previous work has probed social norm violations and the feelings that such violations engender; however, a computational rendering of the underlying neural and emotional responses has been lacking. We probed norm violations using a two-party, repeated fairness game (ultimatum game) where proposers offer a split of a monetary resource to a responder who either accepts or rejects the offer. Using a norm-training paradigm where subject groups are preadapted to either high or low offers, we demonstrate that unpredictable shifts in expected offers creates a difference in rejection rates exhibited by the two responder groups for otherwise identical offers. We constructed an ideal observer model that identified neural correlates of norm prediction errors in the ventral striatum and anterior insula, regions that also showed strong responses to variance-prediction errors generated by the same model. Subjective feelings about offers correlated with these norm prediction errors, and the two signals displayed overlapping, but not identical, neural correlates in striatum, insula, and medial orbitofrontal cortex. These results provide evidence for the hypothesis that responses in anterior insula can encode information about social norm violations that correlate with changes in overt behavior (changes in rejection rates). Together, these results demonstrate that the brain regions involved in reward prediction and risk prediction are also recruited in signaling social norm violations.
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Xiang and colleagues showed that subjects used Bayesian rules to update expected feelings given economic outcomes, and that feeling prediction errors (when measured using variance) scaled parametrically with AIC activation.
“Xiang and colleagues showed that subjects used Bayesian rules to update expected feelings given economic outcomes, and that feeling prediction errors (when measured using variance) scaled parametrically with AIC activation [37].”
From Interoceptive inference, emotion, and the embodied self (2013) · cites this paper as [37]
The Materials and Methods section (‘Feeling Bayesian observer’; page unavailable) describes a Bayesian model that updates expected feelings using subjects’ emoticon ratings, rather than directly using economic outcomes. The Results section (‘Feeling prediction errors’; page unavailable) reports that bilateral anterior insula activity correlated with feeling variance prediction errors. The citation supports the neural finding, but ‘showed that subjects used Bayesian rules’ overstates what the modeled update establishes. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSubjects use Bayesian rules to update their feelings, and feeling variance in prediction errors scales parametrically with AIC activation.
“In line with the conceptual framework proposed by Singer and colleagues (2009), a recent empirical study shows that subjects use Bayesian rules to update their feelings and that (feeling) variance in prediction errors scale parametrically with AIC activation (Xiang et al., 2013).”
From Anterior insular cortex and emotional awareness (2013) · cites this paper as Xiang et al., 2013
Ventral striatum and medial prefrontal cortex responses to ultimatum game offers correlate with the difference between social expectations and actual outcomes, even when expectations of fairness are altered by repeated experiences.
“Consistent with the human ventral striatum association with RPE, ventral striatum and medial prefrontal cortex responses to ultimatum game offers correlate with the difference between social expectations and actual outcomes, even when expectations of fairness are altered by repeated experiences 94.”
From The social brain and reward: Social information processing in the human striatum (2014) · cites this paper as [94]
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- Authors
- Xiang, T., Lohrenz, T., & Montague, P. R.
- Affiliations
- Baylor College of Medicine (US)
- Virginia Tech (US)
- Wellcome Centre for Human Neuroimaging (GB)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2013-01-16
- Volume
- 33
- Issue
- 3
- Pages
- 1099-1108
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC3631781
- OpenAlex
- W2071963478
- Cited by
- 197
- References
- 46
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 17 · 2023: 13 · 2022: 13 · 2021: 17 · 2020: 15 · 2019: 15 · 2018: 20 · 2017: 20 · 2016: 12 · 2015: 17 · 2014: 8 · 2013: 8
- FWCI
- 8.23
- 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)
- Europe PMC (PubMed Central) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- VTechWorks (Virginia Tech) (submittedVersion)
- Funders
- Wellcome Trust (091593, 091188)
- National Institute of Mental Health (R01MH085496)
- National Institute on Drug Abuse (R01-DA11723, R01DA011723)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- social norms, norm violation, ultimatum game, fairness, ventral striatum, anterior insula, medial orbitofrontal cortex, ideal observer, rejection behavior, reward prediction, risk prediction
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Emotions, Female, Humans, Image Processing, Computer-Assisted, Interpersonal Relations, Male, Middle Aged, Social Behavior
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