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神经信号可预测跨文化的信息共享。

Neural signals predict information sharing across cultures.

机构信息

Department of Marketing, King's Business School, King's College London, London WC2B 4BG, United Kingdom.

Amsterdam School of Communication Research, University of Amsterdam, Amsterdam 1018 WV, The Netherlands.

出版信息

Proc Natl Acad Sci U S A. 2023 Oct 31;120(44):e2313175120. doi: 10.1073/pnas.2313175120. Epub 2023 Oct 23.

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., , 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.

摘要

信息共享会影响信息的传播,并塑造人们的信仰、行为和文化。我们在美国和荷兰进行了一项预先注册的神经影像学研究,证明了一种基于大脑的信息共享预测模型的可重复性、预测有效性和普遍性。本研究复制了 Scholz 等人在 2017 年发表的研究结果,个体的自我、社交和价值相关的神经信号可以追踪到美国新闻文章在人群中的共享情况。基于 Scholz 等人(2017 年)数据预先注册的基于大脑的预测模型可以推广到新数据,比仅使用自我报告评分解释更多的人群共享方差。神经信号(而非自我报告)更可靠地预测了跨文化的共享情况,这表明它们可以捕捉到共享行为背后更普遍的心理机制。这些发现强调了共享的关键神经认知基础,为增加信息有效性的干预措施提供了潜在的目标机制,并推进了大脑预测研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b645/10622920/18779611f504/pnas.2313175120fig01.jpg

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