Estimating reflex responses in large populations of motor units by decomposition of the high‐density surface electromyogram

Abstract

Key points: Reflex responses of single motor units have been used for the study of spinal circuitries but the methods employed are invasive and limited to the assessment of a relatively small number of motor units. We propose a new approach to investigate reflexes on individual motor units based on high‐density surface electromyography (HDsEMG) decomposition. The decomposition of HDsEMG has been previously validated in voluntary isometric contractions but never during reflex activities. The use of HDsEMG decomposition for reflex studies at the individual motor unit level, during constant force contractions, with excitatory and inhibitory stimuli, was validated here by the comparison of results with concurrently recorded intramuscular EMG signals. The validation results showed that HDsEMG decomposition allows an accurate quantification of reflex responses for a large number of individual motor units non‐invasively, for both excitatory and inhibitory stimuli. We propose and validate a non‐invasive method that enables accurate detection of the discharge times of a relatively large number of motor units during excitatory and inhibitory reflex stimulations. High‐density surface electromyography (HDsEMG) and intramuscular EMG (iEMG) were recorded from the tibialis anterior muscle during ankle dorsiflexions performed at 5%, 10% and 20% of the maximum voluntary contraction (MVC) force, in nine healthy subjects. The tibial nerve (inhibitory reflex) and the peroneal nerve (excitatory reflex) were stimulated with constant current stimuli. In total, 416 motor units were identified from the automatic decomposition of the HDsEMG. The iEMG was decomposed using a state‐of‐the‐art decomposition tool and provided 84 motor units (average of two recording sites). The reflex responses of the detected motor units were analysed using the peri‐stimulus time histogram (PSTH) and the peri‐stimulus frequencygram (PSF). The reflex responses of the common motor units identified concurrently from the HDsEMG and the iEMG signals showed an average disagreement (the difference between number of observed spikes in each bin relative to the mean) of 8.2 ± 2.2% (5% MVC), 6.8 ± 1.0% (10% MVC) and 7.5 ± 2.2% (20% MVC), for reflex inhibition, and 6.5 ± 4.1%, 12.0 ± 1.8% and 13.9 ± 2.4%, for reflex excitation. There was no significant difference between the characteristics of the reflex responses, such as latency, amplitude and duration, for the motor units identified by both techniques. Finally, reflex responses could be identified at higher force (4 of the 9 subjects performed contraction up to 50% MVC) using HDsEMG but not iEMG, because of the difficulty in decomposing the iEMG at high forces. In conclusion, single motor unit reflex responses can be estimated accurately and non‐invasively in relatively large populations of motor units using HDsEMG. This non‐invasive approach may enable a more thorough investigation of the synaptic input distribution on active motor units at various force levels.