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A computational and neural model of momentary subjective well-being
Open accessAbstract
The subjective well-being or happiness of individuals is an important metric for societies. Although happiness is influenced by life circumstances and population demographics such as wealth, we know little about how the cumulative influence of daily life events are aggregated into subjective feelings. Using computational modeling, we show that emotional reactivity in the form of momentary happiness in response to outcomes of a probabilistic reward task is explained not by current task earnings, but by the combined influence of recent reward expectations and prediction errors arising from those expectations. The robustness of this account was evident in a large-scale replication involving 18,420 participants. Using functional MRI, we show that the very same influences account for task-dependent striatal activity in a manner akin to the influences underpinning changes in happiness.
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“Adolescents’ momentary affective well-being was defined as their current feelings of happiness, a commonly used question to measure well-being21, 22, which has high convergent validity, as evidenced by the strong correlations with the presence of positive affect and absence of negative affect.”
From The effect of social media on well-being differs from adolescent to adolescent (2020) · cites this paper as [21]
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Reference effects on decision-making elicited by previous rewards
Rigoli, F. (2019) · Cognition · doi:10.1016/j.cognition.2019.104034 · Cited by 33
Metadata
- Authors
- Rutledge, R. B., Skandali, N., Dayan, P., & Dolan, R. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Gatsby Computational Neuroscience Unit (GB)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-08-04
- Volume
- 111
- Issue
- 33
- Pages
- 12252-12257
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4143018
- OpenAlex
- W1994312033
- Cited by
- 444
- References
- 57
- Citations by year
- 2026: 36 · 2025: 43 · 2024: 46 · 2023: 54 · 2022: 51 · 2021: 45 · 2020: 32 · 2019: 37 · 2018: 25 · 2017: 18 · 2016: 32 · 2015: 20 · 2014: 3
- FWCI
- 36.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (091593, 078865/Z/05/Z, 095844/Z/11/Z, 098362, 098362/Z/12/Z, 091593/Z/10/Z, 095844, 101252/Z/13/Z)
- Topics
- Social Sciences › Psychology › Social Psychology › Psychological Well-being and Life Satisfaction
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- subjective well-being, emotional reactivity, reward anticipation, prediction error, probabilistic reward task, daily life events, replication
- MeSH terms
- Adult, Emotions, Female, Humans, Magnetic Resonance Imaging, Male, Models, Psychological, Neurons, Probability, Reward, Computational Biology, Young Adult
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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