Literature DB >> 11135280

Cortical activation related to arm-movement combinations.

M J McKeown1.   

Abstract

Recent studies support the long-standing hypothesis that continuous arm movements consist of overlapping, discrete submovements. However, the cortical activation associated with these submovements is unclear. We tested the hypothesis that electroencephalography (EEG) activity would more strongly correspond to the particular combinations of muscle electrical activity, the independent components (ICs) of surface electromyography (EMG), than the surface EMG from individual muscles alone. We examined data recorded from two normal subjects performing sustained submaximal contractions or continual, unpaced repetitive movements of the arm. Independent component analysis (ICA) was used to determine the ICs of the multichannel EMG recordings (EMGICs). ICA was also used to calculate the coupling between the simultaneously recorded EEG and the EMG from a single muscle (Subject 1) or the EMGICs (Subject 2). The EMGICs were either tonic or phasic. The significant couplings between the EEG and the EMGICs were different for each EMGIC. The distribution on the scalp of the coupling between the EEG and tonic EMGICs and those of the single-muscle EMG were similar and followed topographic patterns in sensorimotor regions. Couplings between the EEG and phasic EMGICs were bifrontal, lateral, and bioccipital and were significantly stronger than the coupling between a single muscle's EMG and the EEG (p < 2 x 10(-5)) or another EMG combination derived from principal component analysis. These preliminary results support the notion that electrophysiological cortical activations are more significantly related to the ICs of muscle activations than to the activations of individual muscles alone. Copyright 2000 John Wiley & Sons, Inc. Muscle Nerve Supplement 9:S19-S25, 2000

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Year:  2000        PMID: 11135280     DOI: 10.1002/1097-4598(2000)999:9<::aid-mus5>3.0.co;2-l

Source DB:  PubMed          Journal:  Muscle Nerve Suppl


  1 in total

1.  Identification of hand and finger movements using multi run ICA of surface electromyogram.

Authors:  Ganesh R Naik; Dinesh K Kumar
Journal:  J Med Syst       Date:  2010-07-07       Impact factor: 4.460

  1 in total

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