Identification of common synaptic inputs to motor neurons from the rectified electromyogram

Abstract

Oscillatory common inputs of cortical or peripheral origin can be identified from the motor neuron output with coherence analysis. Linear transmission is possible despite the motor neuron non-linearity because the same input is sent commonly to several neurons. Because of the linear transmission, common input components to motor neurons can be investigated from the surface EMG, for example by EEG-EMG or EMG-EMG coherence. In these studies, there is an open debate on the utility and appropriateness of EMG rectification. The present study addresses this issue using an analytical, simulation and experimental approach. The main novel theoretical contribution that we report is that the spectra of both the rectified and the raw EMG contain input spectral components to motor neurons. However, they differ by the contribution of amplitude cancellation which influences the rectified EMG spectrum when extracting common oscillatory inputs. Therefore, the degree of amplitude cancellation has an impact on the effectiveness of EMG rectification in extracting input spectral peaks. The theoretical predictions were exactly confirmed by realistic simulations of a pool of motor neurons innervating a muscle in a cylindrical volume conductor of EMG generation and by experiments conducted on the first dorsal interosseous and the abductor pollicis brevis muscles of seven healthy subjects during pinching. It was concluded that when the contraction level is relatively low, EMG rectification may be preferable for identifying common inputs to motor neurons, especially when the energy of the action potentials in the low frequency range is low. Nonetheless, different levels of cancellation across conditions influence the relative estimates of the degree of linear transmission of oscillatory inputs to motor neurons when using the rectified EMG.

Figure 1. Effect of cancellation on spectral peaks of raw and rectified EMG

Two simulations are presented in which an input at 20 Hz is sent to 30 (A) and 300 (B) motor neurons. The surface EMG signal is simulated and the level of cancellation corresponds to 37% (A) and 63% (B). The common oscillatory input at 20 Hz is summed with noise (see Methods for the properties and power of the independent noise components). The raw and rectified EMG and their respective amplitude spectra are shown. au: arbitrary units.

Figure 2. The no-cancellation condition corresponds to ideal transmission

Raw, rectified and no-cancellation EMG (see text for the definition of the no-cancellation EMG) signals when activating 300 motor neurons with a common oscillatory input at 30 Hz and additive noise as in Fig. 1. The signals and corresponding spectra are shown. au: arbitrary units.

Figure 3. Transmission of spectral peaks from the neural drive to the muscle to the EMG signal

A signal-to-noise ratio (SNR) measure is defined here as the ratio between the spectral peak corresponding to the oscillatory common input to motor neurons in the raw, rectified and no-cancellation EMG and the same peak in the cumulative motor unit spike train (expressed as %) (see inset). The simulations are as in Fig. 1 but varying the number of active motor units (x-axis). The input frequency is 10 (A), 20 (B) and 30 Hz (C). The second inset represents the relation between the number of active motor units and the level of amplitude cancellation.

Figure 4. Coherence between input and EMG

Coherence values between the raw, rectified and no-cancellation EMG and the composite spike train (A) or the input signal (B), varying the number of active motor units (and thus cancellation level; see inset). The common oscillatory input is in this case set to 20 Hz. The inset represents the relation between the number of active motor units and the level of amplitude cancellation.

Figure 5. Experimental results

A, representative coherence functions between EMG signals recorded from the FDI and APB muscles of one subject. The raw EMG signal has been pre-filtered with a low-pass filter at 800, 200, 80 and 40 Hz, before rectification. The coherence is shown for the pre-filtered, non-rectified signal, and for the pre-filtered and rectified signal. B, group data with peak coherence values obtained from the raw (open circles) and rectified (filled circles) EMG after pre-filtering at varying low-pass cutoff frequencies (x-axis). All values are normalized with respect to the coherence value obtained from the raw EMG without any pre-filtering. The vertical bars indicate SD (the values for SD are negligible for the raw EMG results). *Statistical significant difference between raw and rectified EMG results (P < 0.05).