ArticleNature communications2025
Neurocomputational basis of learning when choices simultaneously affect both oneself and others.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Psychological and computational evidence that merit is a constructed evaluative process.Science advances · 2026Article
- Hippocampal-cingulate dynamics in the human brain link reinforcement-learning and memory.bioRxiv : the preprint server for biology · 2026Article
- A computational mechanism linking momentary craving and decision-making in alcohol drinkers and cannabis users.Nature. Mental health · 2026Article
- Ventromedial prefrontal cortex lesions disrupt learning to reward others.Brain : a journal of neurology · 2025Article
- Neural responses underlying extraordinary altruists' generosity for socially distant others.PNAS nexus · 2023Article
- Towards a neurocomputational account of social controllability: From models to mental health.Neuroscience and biobehavioral reviews · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many prosocial and antisocial behaviors simultaneously impact both ourselves and others, requiring us to learn from their joint outcomes to guide future choices. However, the neurocomputational processes supporting such social learning remain unclear. Across three pre-registered studies, participants learned how choices affected both themselves and others. Computational modeling tested whether people simulate how other people value their choices or integrate self- and other-relevant information to guide choices. An integrated value framework, rather than simulation, characterizes multi-outcome social learning. People update the expected value of choices using different types of prediction errors related to the target (e.g., self, other) and valence (e.g., positive, negative). This asymmetric value update is represented in brain regions that include ventral striatum, subgenual and pregenual anterior cingulate, insula, and amygdala. These results demonstrate that distinct encoding of self- and other-relevant information guides future social behaviors across mutually beneficial, mutually costly, altruistic, and instrumentally harmful scenarios.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.