MIND tutorial on social networks and neural response similarities
In this tutorial, we'll first go over some basics of working with and visualizing social network data (1_social_network_basics.ipynb). The first notebook uses the R kernel, but the other notebooks are Python-based. If you don't have jupyter lab set up to be able to use the R kernel, you can follow along in the HTML version or run the commands within R or R Studio.
Then, we'll quickly go over how to extract region-wise inter-subject fMRI response time series (dis)similarities from members of a social network we have characterized (2a_epi_preprocessing.ipynb, 2b_combine_preprocessed_runs.ipynb, 2c_extract_roi_average_time_series.ipynb).
Finally, we'll relate the distance between individuals in the network to region-wise time-series similarities (3_combine_social_network_and_fmri_data.ipynb).