Neural Prediction of Communication-Relevant Outcomes
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EEG
ERP
fNIRS
biological
neuroscience
brain
neuroimaging
prediction
media effects
Biological Psychology
Cognitive Psychology
Communication
Neuroscience and Neurobiology
Social and Behavioral Sciences
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Abstract
Understanding and predicting the mechanisms and consequences of effective communication may be greatly advanced by leveraging knowledge from social and cognitive neuroscience research. We build on prior brain research that mapped mental processes, and show that information gained from neuroimaging can predict variation in communication outcomes over and above that associated with self-report. We further discuss how neural measures can complement physiological and other implicit measures. The brain-as-predictor approach can (1) allow researchers to predict individual and population level outcomes of exposure to communication stimuli with greater accuracy and (2) provide a better understanding of the mental processes underlying behaviors relevant to communication research. In this article, we give a detailed description of the brain-as-predictor approach and provide a guide for scholars interested in employing it in their research. We then discuss how the brain-as-predictor approach can be used to provide theoretical insights in communication research. Given its potential for advancing theory and practice, we argue that the brain-as-predictor approach can serve as a valuable addition to the communication science toolbox and provide a brief checklist for authors, reviewers and editors interested in using the approach.