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Neuroscientific investigations into communication phenomena using functional magnetic resonance imaging (fMRI) are becoming increasingly popular in communication science. Recent publications in our discipline provided an introduction and tutorial on using and understanding fMRI in communication research, but were largely silent regarding the statistical-analytical aspects of fMRI, which makes it difficult for communication researchers to keep pace with and understand the dizzying array of new statistical techniques for analyzing fMRI data. This article closes this gap: We contextualize, explain, and critique, in fairly non-technical language, several innovative statistical techniques for fMRI data, describing how each analysis works, what types of communication questions it addresses, and what to look out for when the analysis is applied to empirical data. Accordingly, this article serves as a jumping off point for researchers looking to employ these techniques in addressing new research questions in their own labs, while helping prevent mistakes or controversial analytical decisions.
Benjamin Turner, Wee Kim Wee School of Communication and Information, Nanyang Technological University
Richard Huskey, The Ohio State University
Rene Weber, U of California - Santa Barbara