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Cited by 167

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Neural evidence that three dimensions organize mental state representation: Rationality, social impact, and valence

Open access
Tamir, Diana I., Thornton, Mark A., Contreras, Juan Manuel, Mitchell, Jason P.·2016·Proceedings of the National Academy of Sciences

Abstract

Significance: This study uses advanced functional neuroimaging analyses to test both existing and novel psychological theories about how we understand others’ minds. Analyses show that three dimensions—rationality, social impact, and valence—account for almost half of the variation in the neural representation of mental states, the most comprehensive theory to date regarding our ability to think about others’ minds. These findings both inform long-standing debates within social psychology about theory of mind and generate testable predictions about how our neural hardware supports our ability to mentalize.

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Crossref · 10.1073/pnas.1511905112

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Metadata

Authors
Tamir, D. I., Thornton, M. A., Contreras, J. M., & Mitchell, J. P.
Venue
Proceedings of the National Academy of Sciences
Published
2015-11-30
Volume
113
Issue
1
Pages
194-199
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2187736915
Cited by
167
References
12
FWCI
19.29
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Neural evidence that three dimensions organize mental state representation: Rationality, social impact, and valence. https://app.cochat.ai/papers/10.1073/pnas.1511905112
The paper
Tamir, D. I., Thornton, M. A., Contreras, J. M., & Mitchell, J. P. (2016). Neural evidence that three dimensions organize mental state representation: Rationality, social impact, and valence. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1511905112

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.