Paola Contessa

Motor unit control and force fluctuation during fatigue

During isometric contractions, the fluctuation of the force output of muscles increases as the muscle fatigues, and the contraction is sustained to exhaustion. We analyzed motor unit firing data from the vastus lateralis muscle to investigate which motor unit control parameters were associated with the increased force fluctuation. Subjects performed a sequence of isometric constant-force contractions sustained at 20% maximal force, each spaced by a 6-s rest period. The contractions were performed until the mean value of the force output could not be maintained at the desired level. Intramuscular EMG signals were detected with a quadrifilar fine-wire sensor. The EMG signals were decomposed to identify all of the firings of several motor units by using an artificial intelligence-based set of algorithms. We were able to follow the behavior of the same motor units as the endurance time progressed. The force output of the muscle was filtered to remove contributions from the tracking task. The coefficient of variation of the force was found to increase with endurance time (P < 0.001, R(2) = 0.51). We calculated the coefficient of variation of the firing rates, the synchronization of pairs of motor unit firings, the cross-correlation value of the firing rates of pairs of motor units, the cross-correlation of the firing rates of motor units and the force, and the number of motor units recruited during the contractions. Of these parameters, only the cross-correlation of the firing rates (P < 0.01, R(2) = 0.10) and the number of recruited motor units (P = 0.042, R(2) = 0.22) increased significantly with endurance time for grouped subjects. A significant increase (P < 0.001, R(2) = 0.16) in the cross-correlation of the firing rates and force was also observed. It is suggested that the increase in the cross-correlation of the firing rates is likely due to a decrease in the sensitivity of the proprioceptive feedback from the spindles.

The compensatory interaction between motor unit firing behavior and muscle force during fatigue

Throughout the literature, different observations of motor unit firing behavior during muscle fatigue have been reported and explained with varieties of conjectures. The disagreement amongst previous studies has resulted, in part, from the limited number of available motor units and from the misleading practice of grouping motor unit data across different subjects, contractions, and force levels. To establish a more clear understanding of motor unit control during fatigue, we investigated the firing behavior of motor units from the vastus lateralis muscle of individual subjects during a fatigue protocol of repeated voluntary constant force isometric contractions. Surface electromyographic decomposition technology provided the firings of 1,890 motor unit firing trains. These data revealed that to sustain the contraction force as the muscle fatigued, the following occurred: 1) motor unit firing rates increased; 2) new motor units were recruited; and 3) motor unit recruitment thresholds decreased. Although the degree of these adaptations was subject specific, the behavior was consistent in all subjects. When we compared our empirical observations with those obtained from simulation, we found that the fatigue-induced changes in motor unit firing behavior can be explained by increasing excitation to the motoneuron pool that compensates for the fatigue-induced decrease in muscle force twitch reported in empirical studies. Yet, the fundamental motor unit control scheme remains invariant throughout the development of fatigue. These findings indicate that the central nervous system regulates motor unit firing behavior by adjusting the operating point of the excitation to the motoneuron pool to sustain the contraction force as the muscle fatigues.

Is the notion of central fatigue based on a solid foundation

Exercise-induced muscle fatigue has been shown to be the consequence of peripheral factors that impair muscle fiber contractile mechanisms. Central factors arising within the central nervous system have also been hypothesized to induce muscle fatigue, but no direct empirical evidence that is causally associated to reduction of muscle force-generating capability has yet been reported. We developed a simulation model to investigate whether peripheral factors of muscle fatigue are sufficient to explain the muscle force behavior observed during empirical studies of fatiguing voluntary contractions, which is commonly attributed to central factors. Peripheral factors of muscle fatigue were included in the model as a time-dependent decrease in the amplitude of the motor unit force twitches. Our simulation study indicated that the force behavior commonly attributed to central fatigue could be explained solely by peripheral factors during simulated fatiguing submaximal voluntary contractions. It also revealed important flaws regarding the use of the interpolated twitch response from electrical stimulation of the muscle as a means for assessing central fatigue. Our analysis does not directly refute the concept of central fatigue. However, it raises important concerns about the manner in which it is measured and about the interpretation of the commonly accepted causes of central fatigue and questions the very need for the existence of central fatigue.

Transposed firing activation of motor units

Muscles are composed of groups of muscle fibers, called motor units, each innervated by a single motoneuron originating in the spinal cord. During constant or linearly varying voluntary force contractions, motor units are activated in a hierarchical order, with the earlier-recruited motor units having greater firing rates than the later-recruited ones. We found that this normal pattern of firing activation can be altered during oscillatory contractions where the force oscillates at frequencies ≥2 Hz. During these high-frequency oscillations, the activation of the lower-threshold motor units effectively decreases and that of the higher-threshold motor units effectively increases. This transposition of firing activation provides means to activate higher-threshold motor units preferentially. Our results demonstrate that the hierarchical regulation of motor unit activation can be manipulated to activate specific motoneuron populations preferentially. This finding can be exploited to develop new forms of physical therapies and exercise programs that enhance muscle performance or that target the preferential atrophy of high-threshold motor units as a result of aging or motor disorders such as stroke and amyotrophic lateral sclerosis.

Motor unit drive: A neural interface for real-time upper limb prosthetic control

OBJECTIVE Modern prosthetic limbs have made strident gains in recent years, incorporating terminal electromechanical devices that are capable of mimicking the human hand. However, access to these advanced control capabilities has been prevented by fundamental limitations of amplitude-based myoelectric neural interfaces, which have remained virtually unchanged for over four decades. Consequently, nearly 23% of adults and 32% of children with major traumatic or congenital upper-limb loss abandon regular use of their myoelectric prosthesis. To address this healthcare need, we have developed a noninvasive neural interface technology that maps natural motor unit increments of neural control and force into biomechanically informed signals for improved prosthetic control. APPROACH Our technology, referred to as motor unit drive (MU Drive), utilizes real-time machine learning algorithms for directly measuring motor unit firings from surface electromyographic signals recorded from residual muscles of an amputated or congenitally missing limb. The extracted firings are transformed into biomechanically informed signals based on the force generating properties of individual motor units to provide a control source that represents the intended movement. MAIN RESULTS We evaluated the characteristics of the MU Drive control signals and compared them to conventional amplitude-based myoelectric signals in healthy subjects as well as subjects with congenital or traumatic trans-radial limb-loss. Our analysis established a vital proof-of-concept: MU Drive provides a more responsive real-time signal with improved smoothness and more faithful replication of intended limb movement that overcomes the trade-off between performance and latency inherent to amplitude-based myoelectric methods. SIGNIFICANCE MU Drive is the first neural interface for prosthetic control that provides noninvasive real-time access to the natural motor control mechanisms of the human nervous system. This new neural interface holds promise for improving prosthetic function by achieving advanced control that better reflects the user intent. Beyond the immediate advantages in the field of prosthetics, MU Drive provides an innovative alternative for advancing the control of exoskeletons, assistive devices, and other robotic rehabilitation applications.