Simulating progressive motor neuron degeneration and collateral reinnervation in motor neuron diseases using a dynamic muscle model based on human single motor unit recordings

Boudewijn T H M Sleutjes*, Diederik J L Stikvoort García, Pieter A van Doorn, H Stephan Goedee, Leonard H van den Berg

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Downloads (Pure)

Abstract

Objective.To simulate progressive motor neuron loss and collateral reinnervation in motor neuron diseases (MNDs) by developing a dynamic muscle model based on human single motor unit (MU) surface-electromyography (EMG) recordings. Approach.Single MU potentials recorded with high-density surface-EMG from thenar muscles formed the basic building blocks of the model. From the baseline MU pool innervating a muscle, progressive MU loss was simulated by removal of MUs, one-by-one. These removed MUs underwent collateral reinnervation with scenarios varying from 0% to 100%. These scenarios were based on a geometric variable, reflecting the overlap in MU territories using the spatiotemporal profiles of single MUs and a variable reflecting the efficacy of the reinnervation process. For validation, we tailored the model to generate compound muscle action potential (CMAP) scans, which is a promising surface-EMG method for monitoring MND patients. Selected scenarios for reinnervation that matched observed MU enlargements were used to validate the model by comparing markers (including the maximum CMAP and a motor unit number estimate (MUNE)) derived from simulated and recorded CMAP scans in a cohort of 49 MND patients and 22 age-matched healthy controls. Main results.The maximum CMAP at baseline was 8.3 mV (5th-95th percentile: 4.6 mV-11.8 mV). Phase cancellation caused an amplitude drop of 38.9% (5th-95th percentile, 33.0%-45.7%). To match observations, the geometric variable had to be set at 40% and the efficacy variable at 60%-70%. The Δ maximum CMAP between recorded and simulated CMAP scans as a function of fitted MUNE was -0.4 mV (5th-95th percentile = -4.0 - +2.4 mV). Significance.The dynamic muscle model could be used as a platform to train personnel in applying surface-EMG methods prior to their use in clinical care and trials. Moreover, the model may pave the way to compare biomarkers more efficiently, without directly posing unnecessary burden on patients.

Original languageEnglish
Article number056039
JournalJournal of Neural Engineering
Volume20
Issue number5
DOIs
Publication statusPublished - 1 Oct 2023

Keywords

  • biomarker development
  • compound muscle action potential scan
  • dynamic muscle model
  • motor neuron diseases
  • motor unit loss
  • surface-electromyography

Fingerprint

Dive into the research topics of 'Simulating progressive motor neuron degeneration and collateral reinnervation in motor neuron diseases using a dynamic muscle model based on human single motor unit recordings'. Together they form a unique fingerprint.

Cite this