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Neural signals predict information sharing across cultures.

Authors :
Hang-Yee Chan
Scholz, Christin
Cosme, Danielle
Martin, Rebecca E.
Benitez, Christian
Resnick, Anthony
Carreras-Tartak, José
Cooper, Nicole
Paul, Alexandra M.
Falk, Emily B.
Source :
Proceedings of the National Academy of Sciences of the United States of America; 10/31/2023, Vol. 120 Issue 44, p1-3, 6p
Publication Year :
2023

Abstract

Information sharing influences which messages spread and shape beliefs, behavior, and culture. In a preregistered neuroimaging study conducted in the United States and the Netherlands, we demonstrate replicability, predictive validity, and generalizability of a brain-based prediction model of information sharing. Replicating findings in Scholz et al., Proc. Natl. Acad. Sci. U.S.A. 114, 2881-2886 (2017), self-, social-, and value-related neural signals in a group of individuals tracked the population sharing of US news articles. Preregistered brain-based prediction models trained on Scholz et al. (2017) data proved generalizable to the new data, explaining more variance in population sharing than self-report ratings alone. Neural signals (versus self-reports) more reliably predicted sharing cross-culturally, suggesting that they capture more universal psychological mechanisms underlying sharing behavior. These findings highlight key neurocognitive foundations of sharing, suggest potential target mechanisms for interventions to increase message effectiveness, and advance brain-as-predictor research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00278424
Volume :
120
Issue :
44
Database :
Complementary Index
Journal :
Proceedings of the National Academy of Sciences of the United States of America
Publication Type :
Academic Journal
Accession number :
173420713
Full Text :
https://doi.org/10.1073/pnas.2313175120