Robust estimation of average twitch contraction forces of populations of motor units in humans

Abstract

The characteristics of motor unit force twitch profiles provide important information for the understanding of the muscle force generation. The twitch force is commonly estimated with the spike-triggered averaging technique, which, despite the many limitations, has been important for clarifying central issues in force generation. In this study, we propose a new technique for the estimation of the average twitch profile of populations of motor units with uniform contractile properties. The method encompasses a model-based deconvolution of the force signal using the identified discharge times of a population of motor units. The proposed technique was validated using simulations and tested on signals recorded during voluntary activation. The results of the simulations showed that the proposed method provides accurate estimates (relative error <25%) of the main parameters of the average twitch force when the number of identified motor units is between 5% and 15% of the total number of active motor units. It is discussed that current detection and decomposition methods of multi-channel surface EMG signals allow decoding this relative sample of the active motor unit pool. However, even when this condition is not met, our results show that the estimates provided by the new method are anyway always superior to those obtained by the spike triggered average approach, especially for high motor unit synchronization levels and when a relatively small number of triggers is available. In conclusion, we present a new method that overcome the main limitations of the spike-triggered average for the study of contractile properties of individual motor units. The method provides a new reliable tool for the investigation of the determinants of muscle force.

Spike-triggered averaging provides inaccurate estimates of motor unit twitch properties under optimal conditions

“…This reflects that in STA, the force produced by other motor units represents a noise term, and that magnitude of this noise increases with the number of motor units. Finally, the results indicated that the error in the estimated twitch half relaxation time was always substantially higher compared to the other twitch parameters (>30%; Figure 6), as previously reported (Negro and Orizio, 2017). Importantly, it should be noted that these results reflect conditions without motor unit synchronization, which, if present to a sufficient degree, further corrupts the twitch estimates by STA (Kutch et al, 2007;Taylor et al, 2002).…”

“…A few alternative methods based on system identification techniques have been previously proposed to overcome the limitations of the traditional STA technique in human (Andreassen and Bar-On, 1983;Kutch et al, 2010;Lim et al, 1995;Orizio et al, 2016) and in animal recordings (Drzymała-Celichowska et al, 2016). Recently, an advanced method have been proposed and it has demonstrated the ability to accurately estimate the averaged twitch parameters of a relatively small population of motor units (Negro and Orizio, 2017). The method is based on a model-based deconvolution of the recorded force signal using the identified discharge times of a relatively small (tens) population of motor units.…”

Robust and accurate decoding of motoneuron behaviour and prediction of the resulting force output

“…) and the spike triggered averaging methods to estimate twitch characteristics (Kutch et al . ; Negro & Orizio, ) will also be highly advantageous. Overall, it will be important to apply these approaches in multiple muscles in the future, with the eventual goal of understanding the relationships between synaptic organization, motoneuron properties, and the diversity of the musculoskeletal system in both normal and pathological states.…”

“…In animals, the development of extracellular array recordings of populations of spinal interneurons (AuYong et al 2011) can further deepen the insights for cellular mechanisms. For human studies, statistical approaches for human firing data to estimate the durations of AHPs ) and the spike triggered averaging methods to estimate twitch characteristics (Kutch et al 2010;Negro & Orizio, 2017) will also be highly advantageous. Overall, it will be important to apply these approaches in multiple muscles in the future, with the eventual goal of understanding the relationships between synaptic organization, motoneuron properties, and the diversity of the musculoskeletal system in both normal and pathological states.…”

Tremor in Parkinson’s Disease May Arise from Interactions of Central Rhythms with Spinal Reflex Loop Oscillations

“…1A). This latter time interval is much longer than the former, i.e., approximately 100 ms in muscles of normal human hand [38], such as to allow for tremor-generating synchronization of motor neuron discharges at around 9 Hz.…”