The Journal of Physiology - 2023 - karabot - Decoding firings of a large population of human motor units from high‐density.pdf (1.52 MB)
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Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation

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posted on 2023-03-23, 09:44 authored by Jakob SkarabotJakob Skarabot, Claudia Ammann, Tom BalshawTom Balshaw, Matjaz Divjak, Filip Urh, Nina Murks, Guglielmo Foffani, Ales Holobar

We describe a novel application of methodology for high-density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with Convolution Kernel Compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEP. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency, and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEP with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non-invasive HDsEMG recordings.


Slovenian Research Agency (Project J2-1731 and Programme funding P2-0041

Versus Arthritis Foundation Fellowship (reference: 22569)

Comunidad de Madrid fellowship (2017-T2/BMD-5231)

Juan de la Cierva fellowship (IJC2020- 1310 045437-I)

“la Caixa” Foundation (grant LCF/PR/HR20/52400012)

Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación (Spain)

European Regional Development Fund of the European Union (grant PID2021-128623OB-I00)



  • Sport, Exercise and Health Sciences

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The Journal of Physiology




AM (Accepted Manuscript)

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This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as This article is protected by copyright. All rights reserved.

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Dr Jakob Skarabot. Deposit date: 17 March 2023