![Graphical Abstract][1] *Figure from NeuroImage manuscript doi.org/10.1016/j.neuroimage.2020.116527 (CC-BY-NC-ND)* --- In this study, we used electroencephalography (EEG) to capture brain responses of young adults while viewing real-life video messages about risky alcohol use. The health messages varied in perceived effectiveness ("Strong"/"Weak"). - We found that strong, more effective messages prompted enhanced inter-subject correlation (ISC) of EEG data. - Differential EEG-ISC effects were observed during free viewing and a perceived message effectiveness rating task. - In a second stream of analyses, EEG-ISC is used to model fMRI signal captured in a second audience (Imhof et al., 2017) viewing the same messages. Contact: Martin.Imhof@uni-konstanz.de --- The file repository contains data to reproduce results and figures from the manuscript. Contents: - EEG-ISC data from correlated components analysis - Average EEG-ISC during strong & weak alcohol prevention videos (Fig. 2b) - Average EEG-ISC resolved for a free viewing task and a perceived effectiveness rating task (Fig. 2c) - 4 non-thresholded result maps of an EEG-ISC informed fMRI-GLM analysis in which BOLD signal tracked with the ISC from correlated EEG components (*t*-values). Please note that the maps shown in Fig. 3 and Fig. 4a of the manuscript are thresholded using FWE correction, *p* < 0.05, Threshold: +/- 6.08, Talairach space. - 2 result maps visualizing fMRI-ISC results taken from Imhof et al. (2017) overlaid onto the same anatomical voxel space (*r*-values, Talairach space). Please note that the maps shown in Fig. 4b are FDR corrected with *q* = 10^-4 and a threshold for *r*'s > 0.1. --- More information and related work can be found here: https://gpbp.uni-konstanz.de/people-page/martin-imhof https://doi.org/10.1016/j.neuroimage.2020.116527 https://doi.org/10.1093/scan/nsx044 https://nomcomm.github.io/ --- Imhof, M. A., Schmälzle, R., Renner, B., & Schupp, H. T. (in press) Strong health messages increase audience brain coupling. *NeuroImage*. doi: 10.1016/j.neuroimage.2020.116527 [1]: https://files.osf.io/v1/resources/9mc8b/providers/osfstorage/5e297befc19c5d0031ee1343?mode=render