Central nervous system modulates muscle force by controlling the number of active functional units of a muscle, so called motor units (MUs) and their firing rates. Every motor unit is innervated by a motor neuron that transmits the neural commands from the central nervous system. In many different healthy and pathological conditions, the neuromuscular junctions remain stable, thus, the activity of individual motor units reflects the neural codes sent down the motor neurons. Skeletal muscles spatially spread and amplify these neural codes, supporting their acqusition with needle and surface electrodes mounted at the skin above the investigated muscle. Recorded electrical activity of skeletal muscles is called electromyogram (EMG).

EMG is a highly interferential signal but can be decomposed by computer-aided techniques into contributions of individual motor units. This methodology provides a unique insight into the neural codes governing the human movements and has been under intense investigation in the fields of neurophysiology, neurology, rehabilitation, prosthetics, ergonomics and advanced human-machine interfaces. Information on the activity of motor units has also contributed to better understanding of pathologies such as stroke and pathological tremor and basic neurophysiologic research of reflexes and human aging, among the others.

Compound muscle action potential (CMAP) is sum of motor unit action potentials (MUAPs) in the muscle, elicited by electrical or mechanical stimulation of nerves and muscles or by transcranial magnetic (TMS) or electric stimulation (TES) of motor cortex. In the latter case, CMAP is also called motor evoked potential (MEP).

CMAP analysis is routinely applied in clinical and neurophysiologic studies to non-invasively assess the functional status of a human motor system in vivo, to evaluate motor tract integrity and quantify responses of neuromuscular circuits to training, rehabilitation and degeneration due to various neuromuscular disorders, to study corticospinal excitability, to assess motor nerve conduction properties, fatigue and biomechanical responses in skeletal muscles.

In supramaximal stimulation, the CMAP comprises MUAPs of all the motor units in the investigated muscle. Individual detected MUAPs are filtered by volume conductor of a subcutaneous tissue that is interposed between the motor unit and the recording electrodes. Therefore, MUAP and CMAP shapes reflect muscle architecture and geometry, distribution of motor units within the muscle tissue, volume conductor properties and properties of signal acquisition system.

The CMAP’s onset latency from the stimulus artefact indicates the conduction time of the fastest muscle fibers. Namely, although stimulated simultaneously, motor neurons and the corresponding muscle fibers conduct stimuli at different conduction velocities. Changes of conduction velocities and MUAP shapes due to muscle fatigue differ substantially across different muscle fiber types, causing substantial temporal changes in CMAP shapes. By understanding this temporal MUAP dispersions and by decomposing the CMAP to contributions of slow and fast muscle fibers, we would be able to quantify the proportions of different fiber types in different muscles in completely non-invasive way. This information would be of paramount importance for understanding muscle aging, for improved guiding of rehabilitation and training of athletes, as well as for an early detection and objective monitoring of numerous neuromuscular disorders, such as muscle atrophies, that selectively affect specific type of muscle fibers. Similarly, the decomposition of CMAP to contributions of individual motor units could be used as a non-invasive indicator of the number of motor axons innervating the muscle, providing very important biomarker for non-invasive muscle assessment and objective long-term tracking of neuropathies.

In submaximal stimulations, elicited CMAPs are highly variable. This inconsistency of CMAP shapes is mainly due to incomplete muscle stimulation or contributions of neighbouring muscles (i.e. muscle crosstalk), especially in areas with high spatial density of muscles like in the forearm. The problem of submaximal CMAP variability has not yet been systematically addressed, mainly due to the lack of CMAP decomposition techniques. For example, when an electrical excitation, caused by distal supramaximal stimulus propagates in antidromic direction it causes recurrent discharge (so-called F wave) in about 2–5% of the entire motor neuron pool. Moreover, the motor neurons that are involved in F wave generation presumably differ from the motor neurons recruited in low to moderate voluntary contraction levels. Similarly, the order of motor unit recruitment in submaximal nerve and muscle stimulations, generating M waves, differ from the one in voluntary contractions. However, this depends on many factors, such as axon’s diameter and relative location of a neuron with respect to the stimulation electrodes and has not yet been exactly experimentally quantified. These results show that reliable methods to directly quantify the activity of individual motor neurons from non-invasive in vivo recordings of evoked potentials are required but lacking.

In the project, we aim to develop new computer-aided and fully automated techniques for EMG-based CMAP decomposition to contributions of different motor unit types (type I, II) and to individual MUAPs. In particular, we will design and implement new methodologies for:

  • Analysis of conduction velocity distribution in supramaximal and submaximal CMAPs;
  • Quantification of muscle crosstalk contamination in CMAP, especially in areas with several nearby muscles;
  • Decomposition of supramaximal and submaximal CMAPs into contributions of slow and fast motor units
  • Decomposition of supramaximal and submaximal CMAPs into individual MUAPs;
  • Identification of motor unit firing patterns in CMAPs;
  • Comparison of individual motor unit behaviour in stimulated and voluntary contractions.
Figure 1: Identification of MU firing patterns by Covnvolution Kernel Compensation (CKC) method: D) high-density EMG channel with recorded CMAPs in wrist extensor muscles evoked by transcranial magnetic stimulation (TMS). For clarity reasons only one out of 64 recorded high-density EMG channels is depicted; C) Decomposition of recorded high-density EMG signals into contributions of individual MUs. Each vertical bar represents a MU firing; A) Latency between the stimulus and MU firing for a representative MU. B) Stimulation artefact and CMAP in three adjacent high-density EMG channels (blue) and the sum of identified MUAPs (red).