Mikhail Vladimirovich Sinkin

This study compares MEG and EEG in capturing physiological patterns and artifacts, finding MEG provides more spatially focused signals while EEG is more susceptible to high-amplitude artifacts.

This paper decodes speech from minimally invasive EEG electrodes using a compact neural network, achieving 55-70% accuracy with few channels.

The paper introduces FPCM, a novel spike detection method for EEG/MEG data, showing robustness in low SNR conditions and reliable detection of interictal events.