This project is a quick attempt to replicate the results of the following article : Alves, C. L., Cury, R. G., Roster, K., Pineda, A. M., Rodrigues, F. A., Thielemann, C., & Ciba, M. (2022). Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLOS ONE, 17(12), e0277257. https://doi.org/10.1371/journal.pone.0277257

Basically, I took the Pearson connectivity matrix from the original EEG data in order to train a support vector machine (SVM) algorithm to classify correctly if the EEG signals were under the effects of ayahuasca or not.