We investigated the associations between grooved pegboard times, force steadiness (coefficient of variation for force) and variability in an estimate of the common synaptic input to motor neurons innervating the wrist extensor muscles during steady contractions performed by young and older adults. The discharge times of motor units were derived from recordings obtained with high-density surface electrodes when participants performed steady isometric contractions at 10% and 20% of maximal voluntary contraction force. The steady contractions were performed with a pinch grip and wrist extension, both independently (single action) and concurrently (double action). The variance in common synaptic input to motor neurons was estimated with a state-space model of the latent common input dynamics. There was a statistically significant association between the coefficient of variation for force during the steady contractions and the estimated variance in common synaptic input in young (r = 0.31) and older (r = 0.39) adults, although not between either the mean or the coefficient of variation for interspike interval of single motor units with the coefficient of variation for force. Moreover, the estimated variance in common synaptic input during the double-action task with the wrist extensors at the 20% target was significantly associated with grooved pegboard time (r = 0.47) for older adults but not young adults. These findings indicate that longer pegboard times of older adults were associated with worse force steadiness and greater fluctuations in the estimated common synaptic input to motor neurons during steady contractions.

The aims of the current study were to explore the pattern of the force-velocity (F-V) relationship of leg muscles, evaluate the reliability and concurrent validity of the obtained parameters, and explore the load associated changes in the muscle work and power output. Subjects performed maximum vertical countermovement jumps with a vest ranging 0-40% of their body mass. The ground reaction force and leg joint kinematics and kinetics were recorded. The data revealed a strong and approximately linear F-V relationship (individual correlation coefficients ranged from 0.78-0.93). The relationship slopes, F- and V-intercepts, and the calculated power were moderately to highly reliable (0.67 < ICC < 0.91), while the concurrent validity F- and V-intercepts, and power with respect to the directly measured values, was (on average) moderate. Despite that a load increase was associated with a decrease in both the countermovement depth and absolute power, the absolute work done increased, as well as the relative contribution of the knee work. The obtained findings generally suggest that the loaded vertical jumps could not only be developed into a routine method for testing the capacities of leg muscles, but also reveal the mechanisms of adaptation of multijoint movements to different loading conditions.

No abstract

The variance in walking endurance and walking speed was associated with force control of the lower leg muscles during submaximal isometric contractions in individuals with multiple sclerosis (MS). In contrast, the fast walking speed of a sex- and age-matched control group was associated with the strength of lower leg muscles. These findings indicate that moderate declines in the walking performance of persons with MS are more associated with impairments in force control rather than decreases in muscle strength.

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal transmission. This is the first application of a deterministic state-space model to represent the discharge characteristics of motor units during voluntary contractions.