Maria Ermolova

The paper develops a method to predict TMS-evoked responses using pre-stimulus EEG features and finds that alpha, beta, and gamma oscillations correlate with TEP and MEP amplitudes.

This study investigates how the phase of the ongoing micro-rhythm in motor cortices affects long-term changes in interhemispheric inhibition using cortico-cortical paired associative stimulation.

This study develops a machine learning framework to predict motor excitability states using EEG features, achieving 72% mean accuracy in healthy participants.