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

Spatially repeatable components from ultrafast ultrasound are associated with motor unit activity in human isometric contractions. J Neural Eng 2023;20:046016. [PMID: 37437598 DOI: 10.1088/1741-2552/ace6fc]

Objective.Ultrafast ultrasound (UUS) imaging has been used to detect intramuscular mechanical dynamics associated with single motor units (MUs). Detecting MUs from ultrasound sequences requires decomposing a velocity field into components, each consisting of an image and a signal. These components can be associated with putative MU activity or spurious movements (noise). The differentiation between putative MUs and noise has been accomplished by comparing the signals with MU firings obtained from needle electromyography (EMG). Here, we examined whether the repeatability of the images over brief time intervals can serve as a criterion for distinguishing putative MUs from noise in low-force isometric contractions.Approach.UUS images and high-density surface EMG (HDsEMG) were recorded simultaneously from 99 MUs in the biceps brachii of five healthy subjects. The MUs identified through HDsEMG decomposition were used as a reference to assess the outcomes of the ultrasound-based components. For each contraction, velocity sequences from the same eight-second ultrasound recording were separated into consecutive two-second epochs and decomposed. To evaluate the repeatability of components' images across epochs, we calculated the Jaccard similarity coefficient (JSC). JSC compares the similarity between two images providing values between 0 and 1. Finally, the association between the components and the MUs from HDsEMG was assessed.Main results.All the MU-matched components had JSC > 0.38, indicating they were repeatable and accounted for about one-third of the HDsEMG-detected MUs (1.8 ± 1.6 matches over 4.9 ± 1.8 MUs). The repeatable components (JSC > 0.38) represented 14% of the total components (6.5 ± 3.3 components). These findings align with our hypothesis that intra-sequence repeatability can differentiate putative MUs from noise and can be used for data reduction.Significance.This study provides the foundation for developing stand-alone methods to identify MU in UUS sequences and towards real-time imaging of MUs. These methods are relevant for studying muscle neuromechanics and designing novel neural interfaces.

Skeletal muscle models composed of motor units: A review

The mathematical muscle models should include several aspects of muscle structure and physiology. First, muscle force is the sum of forces of multiple motor units (MUs), which have different contractile properties and play different roles in generating muscle force. Second, whole muscle activity is an effect of net excitatory inputs to a pool of motoneurons innervating the muscle, which have different excitability, influencing MU recruitment. In this review, we compare various methods for modeling MU twitch and tetanic forces and then discuss muscle models composed of different MU types and number. We first present four different analytical functions used for twitch modeling and show limitations related to the number of twitch describing parameters. We also show that a nonlinear summation of twitches should be considered in modeling tetanic contractions. We then compare different muscle models, most of which are variations of Fuglevand's model, adopting a common drive hypothesis and the size principle. We pay attention to integrating previously developed models into a consensus model based on physiological data from in vivo experiments on the rat medial gastrocnemius muscle and its respective motoneurons. Finally, we discuss the shortcomings of existing models and potential applications for studying MU synchronization, potentiation, and fatigue.

Real-time myoelectric control of wrist/hand motion in Duchenne muscular dystrophy: A case study

Introduction: Duchenne muscular dystrophy (DMD) is a genetic disorder that induces progressive muscular degeneration. Currently, the increase in DMD individuals' life expectancy is not being matched by an increase in quality of life. The functioning of the hand and wrist is central for performing daily activities and for providing a higher degree of independence. Active exoskeletons can assist this functioning but require the accurate decoding of the users' motor intention. These methods have, however, never been systematically analyzed in the context of DMD. Methods: This case study evaluated direct control (DC) and pattern recognition (PR), combined with an admittance model. This enabled customization of myoelectric controllers to one DMD individual and to a control population of ten healthy participants during a target-reaching task in 1- and 2- degrees of freedom (DOF). We quantified real-time myocontrol performance using target reaching times and compared the differences between the healthy individuals and the DMD individual. Results and Discussion: Our findings suggest that despite the muscle tissue degeneration, the myocontrol performance of the DMD individual was comparable to that of the healthy individuals in both DOFs and with both control approaches. It was also evident that PR control performed better for the 2-DOF tasks for both DMD and healthy participants, while DC performed better for the 1-DOF tasks. The insights gained from this study can lead to further developments for the intuitive multi-DOF myoelectric control of active hand exoskeletons for individuals with DMD.

Sex differences in the detection of motor unit action potentials identified using high-density surface electromyography

Sex-related disparities in force production of humans have been widely observed. Previous literature has attributed differences in peripheral traits, such as muscle size, to explain these disparities. However, less is known about potential sex-related differences in central neuromuscular traits and many comparable studies, not exploring sex-related differences, exhibit a selection-bias in the recruitment of subjects making the generalization of their findings difficult. Utilizing high-density electromyography arrays and motor unit (MU) decomposition, the aim of the current study is to compare MU yield and discharge properties of the tibialis anterior between male and female humans. Twenty-four subjects (10 females) performed two submaximal (20%) isometric dorsiflexion contractions. On average, males yielded nearly twice the amount of MUs as females. Further, females had significantly higher MU discharge rate, lower MU action potential amplitude, and lower MU action potential frequency content than males despite similar levels of torque and MU discharge variability. These findings suggest differences in central neuromuscular control of force production between sexes; however, it is unclear how lower yield counts affect the accuracy of these results.

The force-generation capacity of the tibialis anterior muscle at different muscle-tendon lengths depends on its motor unit contractile properties

Purpose

Muscle–tendon length can influence central and peripheral motor unit (MU) characteristics, but their interplay is unknown. This study aims to explain the effect of muscle length on MU firing and contractile properties by applying deconvolution of high-density surface EMG (HDEMG), and torque signals on the same MUs followed at different lengths during voluntary contractions.

Methods

Fourteen participants performed isometric ankle dorsiflexion at 10% and 20% of the maximal voluntary torque (MVC) at short, optimal, and long muscle lengths (90°, 110°, and 130° ankle angles, respectively). HDEMG signals were recorded from the tibialis anterior, and MUs were tracked by cross-correlation of MU action potentials across ankle angles and torques. Torque twitch profiles were estimated using model-based deconvolution of the torque signal based on composite MU spike trains.

Results

Mean discharge rate of matched motor units was similar across all muscle lengths (P = 0.975). Interestingly, the increase in mean discharge rate of MUs matched from 10 to 20% MVC force levels at the same ankle angle was smaller at 110° compared with the other two ankle positions (P = 0.003), and the phenomenon was explained by a greater increase in twitch torque at 110° compared to the shortened and lengthened positions (P = 0.002). This result was confirmed by the deconvolution of electrically evoked contractions at different stimulation frequencies and muscle–tendon lengths.

Conclusion

Higher variations in MU twitch torque at optimal muscle lengths likely explain the greater force-generation capacity of muscles in this position.

Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges

Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.

Inability to increase the neural drive to muscle is associated with task failure during submaximal contractions

Motor unit firing and contractile properties during a submaximal contraction until failure were assessed with a new tracking technique. Two distinct phases in firing behavior were observed, which compensated for changes in twitch area and predicted time to failure. However, the late increase in firing rate was below the rates attained in the absence of fatigue, which points to an inability of the central nervous system to sufficiently increase the neural drive to muscle with fatigue.

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

It is commonly believed that tremor, one of the cardinal signs of Parkinson’s disease, is associated with cerebello-thalamo-cortical oscillations set off by the dopamine-depleted basal ganglia networks. The triggering mechanism has been, however, not entirely delineated. Several reports have pointed to the relevance of interactions with peripheral/spinal mechanisms to tremor generation. Investigations of motor unit synchronization and discharge patterns suggested that exaggerated beta-band oscillations may intermittently reach alpha-motoneurons and modulate low-amplitude membrane oscillations due to spinal loop transmission delays. As a result, the spinal reflex loop will oscillate more vigorously and at a lower frequency and, in turn, entrain larger transcortical loops. Motoneurons may thus represent the specific generator “node” in a tremor network encompassing both cerebral and peripheral/spinal recurrent circuits.

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

KEY POINTS

The spinal alpha motoneuron is the only cell in the human CNS whose discharge can be routinely recorded in humans. We have reengineered motor unit collection and decomposition approaches, originally developed in humans, to measure the neural drive to muscle and estimate muscle force generation in the in vivo cat model. Experimental, computational, and predictive approaches are used to demonstrate the validity of this approach across a wide range of modes to activate the motor pool. The utility of this approach is shown through the ability to track individual motor units across trials, allowing for better predictions of muscle force than the electromyography signal, and providing insights in to the stereotypical discharge characteristics in response to synaptic activation of the motor pool. This approach now allows for a direct link between the intracellular data of single motoneurons, the discharge properties of motoneuron populations, and muscle force generation in the same preparation.

ABSTRACT

The discharge of a spinal alpha motoneuron and the resulting contraction of its muscle fibres represents the functional quantum of the motor system. Recent advances in the recording and decomposition of the electromyographic signal allow for the identification of several tens of concurrently active motor units. These detailed population data provide the potential to achieve deep insights into the synaptic organization of motor commands. Yet most of our understanding of the synaptic input to motoneurons is derived from intracellular recordings in animal preparations. Thus, it is necessary to extend the new electrode and decomposition methods to recording of motor unit populations in these same preparations. To achieve this goal, we use high-density electrode arrays and decomposition techniques, analogous to those developed for humans, to record and decompose the activity of tens of concurrently active motor units in a hindlimb muscle in the in vivo cat. Our results showed that the decomposition method in this animal preparation was highly accurate, with conventional two-source validation providing rates of agreement equal to or superior to those found in humans. Multidimensional reconstruction of the motor unit action potential provides the ability to accurately track the same motor unit across multiple contractions. Additionally, correlational analyses demonstrate that the composite spike train provides better estimates of whole muscle force than conventional estimates obtained from the electromyographic signal. Lastly, stark differences are observed between the modes of activation, in particular tendon vibration produced quantal interspike intervals at integer multiples of the vibration period.