Empirical Mode Decomposition (EMD) – Based Spatiotemporal Approach for Single-Trial Extraction of Post-Movement MEG Beta Synchronization

Abstract

Due to the non-phaselocked nature and variability from trial to trial, the extraction of event-related oscillatory neuromagnetic activities from single-trial measurement is challenging. The present study proposes a method based on empirical mode decomposition (EMD) and uses a template-based correlation approach to extract Rolandic beta rhythm from magnetoencephalographic (MEG) during right finger lifting movements. The longitudinal gradiometer of the sensor unit which presented most prominent SEF was selected as channel of interest (CI) on which each single-trial recording was decomposed by EMD into a set of intrinsic mode functions (IMFs). Correlation coefficients were calculated between each IMF and data recorded in other MEG channels. These correlation values can be viewed as the spatial weights of the IMF over all MEG channels, which can then be arranged as a spatial map. One spatial template with a focal spatial distribution over left sensorimotor area was used to facilitate a sernsorimotor-related IMF selection process, by matching the spatial map of each IMF with the spatial template. Only those IMFs survived high correlation values with the spatial template were chosen as sensorimotor-related IMFs, which were then subjected to a following data reconstruction process. Results demonstrated that amplitudes and phases with high SNR were retained in the extracted oscillatory activities. The preservation of spatial-temporal features in oscillatory activities allows various methods of source estimation can be applied to study the intricate brain dynamics of motor control mechanisms. The present study enables the possibility of investigating cortical pathophysiology of movement disorder on a trial-by-trial basis which also permits an effective alternative for participants or patients who can not endure lengthy procedures or are incapable of sustaining long experiments.