Neural signals predict information sharing across cultures.

Area of Science:

• Neuroscience
• Social Psychology
• Communication Studies

Background:

• Information sharing significantly impacts societal beliefs, behaviors, and culture.
• Previous research established a brain-based prediction model for information sharing behavior.

Purpose of the Study:

• To demonstrate the replicability, predictive validity, and generalizability of a brain-based prediction model for information sharing.
• To compare the predictive power of neural signals versus self-report ratings in understanding information sharing.
• To investigate the cross-cultural applicability of brain-based models in predicting information sharing.

Main Methods:

• A preregistered neuroimaging study was conducted in the United States and the Netherlands.
• Neural signals related to self-, social-, and value-based processing were recorded.
• Brain-based prediction models were trained on existing data and tested on new datasets.

Main Results:

• Replicated previous findings showing neural signals track population sharing of news articles.
• Brain-based prediction models generalized to new data, explaining more variance in sharing than self-reports alone.
• Neural signals more reliably predicted sharing cross-culturally compared to self-report measures.

Conclusions:

• Neural signals provide a robust and generalizable basis for predicting information sharing behavior.
• Brain-based prediction models offer insights into universal psychological mechanisms underlying information dissemination.
• Findings support the advancement of brain-as-predictor research and suggest targets for enhancing message effectiveness.