In this report we will explain our analysis of EEG (electroencephalograms) data retrieved from PhysioNet Motor Movement/Imagery Dataset (https://physionet.org/content/eegmmidb/1.0.0/). In particular, we focused on the results of a one-minute long experiment at resting state, both with open and closed eyes from the same subject ("S059"). We used this information to create a connectivity graph for brain's areas and analyzed it to study its structures, motifs and communities. To perform our analysis we used several python libraries such as mne, networkx, connectivity, community and cdlib. Overall we can say that we worked with small-world graphs of density equal to 20%; we also found that the number of motifs and anti motifs found in the brain is going to depend on the target region, and that we can highlight at least 3 functional communities in the networks, depeding on the detection method.
This project was made by Alfano Caterina (1746299), Cappelli Dario (1711562), Nana Teukam Yves Gaetan (1741352)