Motor Unit Identification in the M Waves Recorded by High-Density Electromyogram

Abstract

We describe and test the methodology supporting the identification of individual motor unit (MU) firings in the motor response (M wave) to percutaneous nerve stimulation recorded by surface high-density electromyography (HD-EMG) on synthetic and experimental data. Methods: A set of simulated voluntary contractions followed by 100 simulated M waves with a normal distribution (MU mean firing latency: 10 ms, Standard Deviation -SDLAT 0.1-1.3 ms) constituted the synthetic signals. In experimental condition, at least 52 progressively increasing M waves were elicited in the soleus muscle of 12 males, at rest (REST), and at 10% (C10) and 20% (C20) of maximal voluntary contraction (MVC). The MU decomposition filters were identified from 15-20 s long isometric plantar flexions performed at 10-70% of MVC and, afterwards, applied to M waves. Results: Synthetic signal analysis demonstrated high accuracy of MU identification in M waves (precision ≥ 85%). In experimental conditions 42.6 ± 11.2 MUs per participant were identified from voluntary contractions. When the MU filters were applied to the M wave

Decoding firings of a large population of human motor units from high‐density surface electromyogram in response to transcranial magnetic stimulation

“…Promising results have been shown previously whereby MU firings could be identified in induced reflexes (Kalc et al, 2022a;Yavuz et al, 2015), and a limited number of MU firings were identified in response to maximal percutaneous nerve stimulation (i.e. M wave; Kalc et al, 2022b). However, responses to TMS represent their own challenges, namely the greater complexity of the multi-volley compared to single-volley responses such as H-reflexes and M-waves (Bawa & Lemon, 1993;Brouwer & Ashby, 1990.…”

“…To assess the feasibility of the methodology we first simulated synthetic HDsEMG signals for which the ground truth about MU firings was known. We previously showed in simulations that the approach of estimating MU filters from the decomposition of voluntary submaximal contractions and applying them to evoked responses allows accurate identification of MU firings at a fixed proportion of motor pool recruitment, even in cases of supraphysiological synchronisation of firings (Kalc et al., 2022a , 2022b ). Here, we simulated MEPs corresponding to a wide range of the proportion of motor pool activation (10–100%) and demonstrated high precision and accuracy of MU identification (>90%).…”

“…In this study, we aimed to ascertain the validity and accuracy of identifying firings of a large population of individual MUs that constitute an evoked motor response to single pulse TMS. We utilised the principles of the convolution kernel composition (CKC) method of HDsEMG decomposition that we recently developed for identification of MU firings underpinning the H‐reflex (Kalc et al., 2022a ) and M‐wave (Kalc et al., 2022b ); here we adapted and applied this methodology to more complex evoked responses to TMS. We relied on MU filters, a unique property of HDsEMG decomposition (Francic & Holobar, 2021 ), obtained from a range of voluntary contractions to estimate firing instances of many MUs during MEPs.…”