AbstractThe nervous system has a tremendous ability to modify motoneuron excitability according to task demands through neuromodulatory synaptic input to motoneurons. Neuromodulatory inputs adjust the response of the motoneuron to excitatory and inhibitory ionotropic input and can facilitate the induction of persistent inward currents (PICs). PICs amplify and prolong the motoneuron response to synaptic inputs, and PIC impairment may play a major role in motor deficits observed in pathological conditions. Noninvasive estimation of the magnitude of neuromodulatory input and persistent inward currents in human motoneurons is achieved through a paired motor unit analysis (ΔF) that quantifies hysteresis in the firing rates at motor unit recruitment and derecruitment. While the ΔF technique is commonly used for estimating motoneuron excitability, computational parameters used for the technique vary across studies. In the present study, we assessed the sensitivity of the ΔF technique to several criteria commonly used in selecting motor unit pairs for analysis, as well as to methods used for smoothing the instantaneous motor unit firing rates. Using HD-sEMG and motor unit decomposition we obtained 5,409 motor unit pairs from the triceps brachii of ten healthy individuals during submaximal triangle contractions. The mean (SD) ΔF was 4.9 (1.08) pps, consistent with previous work using intramuscular recordings. There was an exponential plateau relationship between ΔF and the recruitment time difference between the motor unit pairs, with the plateau occurring at approximately 1 s. There was an exponential decay relationship between ΔF and the derecruitment time difference between the motor unit pairs, with the decay stabilizing at approximately 1.5 s. We found that reducing or removing the minimum threshold for the correlation of the rate-rate slope for the two units did not affect ΔF values or variance. Additionally, we found that removing motor unit pairs in which the control unit was saturated had no significant effect on ΔF. Smoothing filter selection had no substantial effect on ΔF values and ΔF variance; however, the length and type of smoothing filter affected the minimum recruitment and derecruitment time differences. Our results facilitate interpretation of findings from studies that implement the ΔF approach but use different computational parameters.
Impact of parameter selection on estimates of motoneuron excitability using paired motor unit analysis