ArticleNature communications2024
Neurocomputational mechanisms involved in adaptation to fluctuating intentions of others.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Oxytocin modulates the neurocomputational mechanisms engaged in learning rank relationships in social networks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Learning to adaptively cooperate through social interactions during childhood and adolescence.NPJ science of learning · 2026Article
- A neural signature of adaptive mentalization.Nature neuroscience · 2026Article
- Intention-Outcome Trade-Off in Moral Character Learning.Annals of the New York Academy of Sciences · 2026Article
- Covert neural and autonomic signatures of shared perception.Social cognitive and affective neuroscience · 2026Article
- Contribution of amygdala to dynamic model arbitration under uncertainty.Nature communications · 2025Article
- Autism-associatedProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Continuous dynamics of cooperation and competition in social decision-making.Communications psychology · 2025Article
- An Information-Theoretic Framework for Understanding Learning and Choice Under Uncertainty.Entropy (Basel, Switzerland) · 2025Article
- Heterogeneity in strategy use during arbitration between experiential and observational learning.Nature communications · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Humans frequently interact with agents whose intentions can fluctuate between competition and cooperation over time. It is unclear how the brain adapts to fluctuating intentions of others when the nature of the interactions (to cooperate or compete) is not explicitly and truthfully signaled. Here, we use model-based fMRI and a task in which participants thought they were playing with another player. In fact, they played with an algorithm that alternated without signaling between cooperative and competitive strategies. We show that a neurocomputational mechanism with arbitration between competitive and cooperative experts outperforms other learning models in predicting choice behavior. At the brain level, the fMRI results show that the ventral striatum and ventromedial prefrontal cortex track the difference of reliability between these experts. When attributing competitive intentions, we find increased coupling between these regions and a network that distinguishes prediction errors related to competition and cooperation. These findings provide a neurocomputational account of how the brain arbitrates dynamically between cooperative and competitive intentions when making adaptive social decisions.
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