Dataset for the article "Blindly separated spontaneous network-level oscillations predict corticospinal excitability"

This repository contains a dataset supporting results in the manuscript: Ermolova, M., Metsomaa, J., Belardinelli, P., Zrenner, C., & Ziemann, U. (2024). Blindly separated spontaneous network-level oscillations predict corticospinal excitability. Journal of Neural Engineering, 21(3), 036041.

REFTEP dataset: TMS-EEG experiment on awake healthy human subjects. Single-pulse TMS was applied in resting state over primary motor cortex, with simultaneous EEG recording from the scalp and EMG recording from hand muscles.  

The dataset is intended for use by the code published at: https://github.com/mariaermolova/CSPAnalysis. The dataset is structured as follows: each .mat file corresponds to a single subject and contains a matlab structure with the following substructs. 

1. EEG data from 1.5 sec. before each TMS pulse (eeg). The data was preprocessed: bad trials and channels removed, signals detrended, ICA components corresponding to oculographic artefacts removed. 

2. EEG channel locations on the scalp (chanlocs) and indices of channels removed during preprocessing (removedChannels). 

3. Peak-to-peak amplitudes of Motor Evoked Potentials for each trial (mepSize) and excitability labels for each trial based on the amplitude of the corresponding MEP (labels). Labels correspond to high (1) vs low (0) MEP amplitude.