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

<p>This repository contains a dataset supporting results in the manuscript: Ermolova, M., Metsomaa, J., Belardinelli, P., Zrenner, C., &amp; Ziemann, U. (2024). Blindly separated spontaneous network-level oscillations predict corticospinal excitability. <em>Journal of Neural Engineering</em>, <em>21</em>(3), 036041.</p> <p>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. &nbsp;</p> <p>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.&nbsp;</p> <p>1. EEG data from 1.5 sec. before each TMS pulse (<em><strong>eeg</strong></em>). The data was preprocessed: bad trials and channels removed, signals detrended, ICA components corresponding to oculographic artefacts removed.&nbsp;</p> <p>2. EEG channel locations on the scalp (<em><strong>chanlocs</strong></em>) and indices of channels removed during preprocessing (<em><strong>removedChannels</strong></em>).&nbsp;</p> <p>3. Peak-to-peak amplitudes of Motor Evoked Potentials for each trial (<em><strong>mepSize</strong></em>) and excitability labels for each trial based on the amplitude of the corresponding MEP (<em><strong>labels</strong></em>). Labels correspond to high (1) vs low (0) MEP amplitude.</p>