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1_social_network_basics.ipynb
2a_epi_preprocessing.ipynb
2b_combine_preprocessed_runs.ipynb
2c_extract_roi_average_time_series.ipynb
3_combine_social_network_and_fmri_data.ipynb
README.md Cleaning up typos + adding more info for Eshin to use at Sao Paulo Su… Aug 21, 2018

README.md

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).

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