Evaluating Data-Driven Methods to Capture Anxious Arousal with Movie fMRI

Recent years have seen an expansion in the use of naturalistic stimuli in neuroscience. Movie-watching designs offer a unique platform for studying mental processes and psychiatric illness, including anxiety. Common techniques for analyzing this data are feature-based modeling, functional connectivity, and intersubject correlation. While these continue to provide insight, their limitations warrant exploration of additional measures. In this preregistered analysis of open data, we explored the sensitivity of two other techniques for capturing anxious arousal in movie fMRI: fractional amplitude of low frequency fluctuations (fALFF) and a whole-brain inverse ‘fMRI Arousal Index’ (iFAI). We tested whether these measures differed between anxiogenic and control movie clips. We did not observe significantly altered fALFF in hypothesized regions encompassing subcortical, salience, and default mode areas. On the other hand, iFAI was significantly greater during the anxiogenic clip, correlated with ongoing fluctuations in state anxiety, and appeared partially driven by midcingulate activity. iFAI may therefore hold promise as a complementary data-driven technique for studying anxious arousal.