Analyses of EEG oscillatory activities during slow and fast repetitive movements using holo-hilbert spectral analysis

Neural oscillatory activities existing in multiple frequency bands usually represent different levels of neurophysiological meanings, from micro-scale to macro-scale organizations. In this paper, we adopted Holo-Hilbert spectral analysis (HHSA) to study the amplitude-modulated (AM) and frequency-modulated (FM) components in sensorimotor Mu rhythm induced by slow- A nd fast-rate repetitive movements. The HHSA-based approach is a two-layer empirical mode decomposition architecture, which firstly decomposes the EEG signal into a series of frequency-modulated intrinsic mode functions (IMFs) and then decomposes each frequency-modulated IMF into a set of amplitude-modulated IMFs. With the HHSA, the FM and AM components were incorporated with their instantaneous power to achieve full-informational spectral analysis. We observed that the instantaneous power induced by slow-rate movements was significantly higher than that induced by fast-rate movements (p < 0.01, Wilcoxon signed rank test). The alpha-band AM frequencies induced by slow-rate movements were higher than those induced by fast-rate movements, while no statistical difference was found in beta-band AM frequencies. In addition, to study the functional coupling between the primary sensorimotor area and other brain regions, spectral coherence was applied and statistical difference was found in frontal area in slow-rate versus fast-rate movements. The discrepancy between slow- A nd fast-rate movements might be due to the change of motor functional modes from a default mode network to automatic timing with the increase of movement rates. The use of HHSA for oscillatory activity analysis can be an efficient tool to provide informative interaction among different frequency bands.