title: Phasic and tonic coupling between EEG and EMG demonstrated with independent component analysis.
abstract: The authors describe a method for demonstrating the tonic and phasic couplings between suitably time-aligned surface eletromyographs (sEMGs) and the simultaneously recorded EEGs. The method, based on independent component analysis, was applied to data recorded from two normal subjects performing sustained submaximal contractions or continual repetitive movements of the arm. Augmented datasets, consisting of the EEG and either the sEMG from a single muscle (subject 1) or a combination of sEMGs from several muscles (subject 2), were analyzed with independent component analysis to determine the EEG/sEMG coupling. Each derived coupling consisted of a spatial distribution on the scalp and a waveform representing an EEG channel combination coactivating with the sEMG. The combinations of sEMGs, derived by applying independent component analysis to the simultaneous sEMG recordings from several muscles to create sEMG independent components (ICs), were either tonic or phasic with differing periods of activation. The topographic distributions on the scalp of the couplings between the EEG and sEMG ICs were different for each sEMG IC. The spatial distributions of the couplings between tonic sEMG ICs or single-muscle sEMGs and the EEG followed topographic patterns in sensorimotor regions. Phasic couplings were bifrontal, lateral, and bioccipital. Calculation of coherence between the sEMG ICs and calculated EEG combinations agreed well with the frequency spectra of the independent component analysis-derived coupling waveforms. These preliminary results demonstrate that detection of both the tonic and phasic coupling between the sEMG and the EEG is possible when monitoring unpaced proximal arm movement. This may thus be a practical means of exploring the dynamic cortical/muscle relationships in subjects unable to perform fine finger movements, such as patients recovering from stroke.
authors: Department of Medicine (Neurology), Duke University Medical Center, Duke University, Durham, North Carolina 27710, USA.
authors: M J
authors: MJ
authors: McKeown
authors: R
authors: R
authors: Radtke
mesh_terms: D000465:Algorithms; D001132:Arm / Q000502:physiology; D002540:Cerebral Cortex / Q000502:physiology; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D004576:Electromyography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D009010:Monte Carlo Method; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology