Data and analysis code for Schmälzle, R., O'Donnell, M.B., Garcia, J.O., Cascio, C.N., Bayer, J., Bassett, D.S., Vettel, J. & Falk, E.B. (2017). Brain connectivity dynamics during social interaction reflect social network structure. Proceedings of the National Academy of Sciences. 
- The notebook to reproduce the analysis of the main effect of exclusion
- The notebook to reproduce the analysis of the association between social network density and brain connectivity
- The notebook for running the meta-analysis in Neurosynth
- Extracted data matrices for the a-priori-networks
- Extracted data matrices for the Power-264-node parcellation
- Datasheet with the social network density metrics
- Folder with the result maps for the meta-analysis
- Python
Anaconda should provide you with most of what you need.
The following packages are used and we feel very indebted to their creators:
- Project Jupyter
- nilearn e.g.
pip install nilearn - seaborn
- numpy
- scipy
- matplotlib
- pandas
- bctpy
- mne
- neurosynth
Note: if you run into errors indicating you miss a package, either enter "pip install package" in a terminal or - if in the notebook - insert a cell and write "!pip install package"
2017 | Ralf Schmaelzle | Matthew Brook O'Donnell