An α-MN collateral to γ-MNs can mitigate velocity-dependent stretch reflexes during voluntary movement: A computational study

The primary motor cortex does not uniquely or directly produce α -MN drive to muscles during voluntary movement. Rather, α -MN drive emerges from the synthesis and competition among excitatory and inhibitory inputs from multiple descending tracts, spinal interneurons, sensory inputs, and proprioceptive afferents. One such fundamental input is velocity-dependent stretch reflexes in lengthening (antagonist) muscles, which are thought to be inhibited by the shortening (agonist) muscles. It remains an open question, however, the extent to which velocity-dependent stretch reflexes disrupt voluntary movement, and whether and how they are inhibited in limbs with numerous monoand multi-articular muscles where agonist and antagonist roles become unclear and can switch during a movement. We used a computational model of a Rhesus Macaque arm to simulate movements with feedforward α -MN commands only, and with added velocity-dependent stretch reflex feedback. We found that velocity-dependent stretch reflex caused movement-specific, typically large and variable disruptions to the arm endpoint trajectories. In contrast, these disruptions became small when the velocity-dependent stretch reflexes were simply scaled by the α -MN drive to each muscle (equivalent to an α -MN excitatory collateral to its homologous γ -MNs, but distinct from α - γ co-activation. We argue this circuitry is more neuroanatomically tenable, generalizable, and scalable than α - γ co-activation or movement-specific reciprocal inhibition. We propose that this mechanism at the homologous propriospinal level, by locally and automatically regulating the highly nonlinear neuro-musculo-skeletal mechanics of the limb, could be a critical low-level enabler of learning, adaptation, and performance via cerebellar and cortical mechanisms.

Attainment of Quiet Standing in Humans: Are the Lower Limb Joints Controlled Relative to a Misaligned Postural Reference?

In human quiet standing, the relative position between ankle joint centre and line of gravity is neurally regulated within tight limits. The regulation of the knee and hip configuration is unclear and thought to be controlled passively. However, perturbed standing experiments have shown a lower limb multi-joint coordination. Here, measuring the relative alignment between lower limb joints and the line of gravity in quiet standing after walking, we investigated whether the configuration is maintained over time through passive mechanisms or active control. Thirteen healthy adults walked without following a path and then stood quietly for 7.6 s on a force platform (up to four trials). The transition between initiation and steady-state standing (7.6 s) was measured using motion capture. Sagittal lower limb joint centres' position relative to line of gravity (CoG_AP) and their time constants were calculated in each trial. Ankle, knee, and hip joint moments were also calculated through inverse dynamics. After walking, the body decelerated (τ = 0.16 s). The ankle and hip joints' position relative to CoG_AP measured at two time intervals of quiet standing (Mid = 0.5-0.55 s; End = 7.55-7.6 s) were different (mean ± SEM, CoG_{AP-Ankle_Mid} = 47 ± 4 mm, CoG_{AP-Ankle_End} = 58 ± 5 mm; CoG_{AP-Hip_Mid} = 2 ± 5 mm, CoG_{AP-Hip_End} = -5 ± 5 mm). The ankle, knee, and hip flexion-extension moments significantly changed. Changes in joints position relative to CoG_AP and misalignment suggest that joint position is not maintained over 7.6 s, but regulated relative to a standing reference. Higher joint moments at steady-state standing suggest mechanisms other than passive knee and hip regulation are involved in standing.

Motor Unit Action Potential Clustering-Theoretical Consideration for Muscle Activation during a Motor Task

During dynamic or sustained isometric contractions, bursts of muscle activity appear in the electromyography (EMG) signal. Theoretically, these bursts of activity likely occur because motor units are constrained to fire temporally close to one another and thus the impulses are "clustered" with short delays to elicit bursts of muscle activity. The purpose of this study was to investigate whether a sequence comprised of "clustered" motor unit action potentials (MUAP) can explain spectral and amplitude changes of the EMG during a simulated motor task. This question would be difficult to answer experimentally and thus, required a model to study this type of muscle activation pattern. To this end, we modeled two EMG signals, whereby a single MUAP was either convolved with a randomly distributed impulse train (EMG-rand) or a "clustered" sequence of impulses (EMG-clust). The clustering occurred in windows lasting 5-100 ms. A final mixed signal of EMG-clust and EMG-rand, with ratios (1:1-1:10), was also modeled. A ratio of 1:1 would indicate that 50% of MUAP were randomly distributed, while 50% of "clustered" MUAP occurred in a given time window (5-100 ms). The results of the model showed that clustering MUAP caused a downshift in the mean power frequency (i.e., ~30 Hz) with the largest shift occurring with a cluster window of 10 ms. The mean frequency shift was largest when the ratio of EMG-clust to EMG-rand was high. Further, the clustering of MUAP also caused a substantial increase in the amplitude of the EMG signal. This model potentially explains an activation pattern that changes the EMG spectra during a motor task and thus, a potential activation pattern of muscles observed experimentally. Changes in EMG measurements during fatiguing conditions are typically attributed to slowing of conduction velocity but could, per this model, also result from changes of the clustering of MUAP. From a clinical standpoint, this type of muscle activation pattern might help describe the pathological movement issues in people with Parkinson's disease or essential tremor. Based on our model, researchers moving forward should consider how MUAP clustering influences EMG spectral and amplitude measurements and how these changes influence movements.

Promoting Translational Research Among Movement Science, Occupational Science, and Occupational Therapy

Integration of research in the fields of neural control of movement and biomechanics (collectively referred to as movement science) with the field of human occupation directly benefits both areas of study. Specifically, incorporating many of the quantitative scientific methods and analyses employed in movement science can help accelerate the development of rehabilitation-relevant research in occupational therapy (OT) and occupational science (OS). Reciprocally, OT and OS, which focus on the performance of everyday activities (occupations) to promote health and well-being, provide theoretical frameworks to guide research on the performance of actions in the context of social, psychological, and environmental factors. Given both fields' mutual interest in the study of movement as it relates to health and disease, the authors posit that combining OS and OT theories and principles with the theories and methods in movement science may lead to new, impactful, and clinically relevant knowledge. The first step is to ensure that individuals with OS or OT backgrounds are academically prepared to pursue advanced study in movement science. In this article, the authors propose 2 strategies to address this need.

Motor plan differs for young and older adults during similar movements

Older adults exhibit altered activation of the agonist and antagonist muscles during goal-directed movements compared with young adults. However, it remains unclear whether the differential activation of the antagonistic muscles in older adults results from an impaired motor plan or an altered ability of the muscle to contract. The purpose of this study, therefore, was to determine whether the motor plan differs for young and older adults. Ten young (26.1 ± 4.3 yr, 4 women) and 16 older adults (71.9 ± 6.9 yr, 9 women) participated in the study. Participants performed 100 trials of fast goal directed movements with ankle dorsiflexion while we recorded the electromyographic activity of the primary agonist (tibialis anterior; TA) and antagonist (soleus; SOL) muscles. From those 100 trials we selected 5 trials in each of 3 movement end-point categories (fast, accurate, and slow). We investigated age-associated differences in the motor plan by quantifying the individual activity and coordination of the agonist and antagonist muscles. During similar movement end points, older adults exhibited similar activation of the agonist (TA) and antagonist (SOL) muscles compared with young adults. In addition, the coordination of the agonist and antagonist muscles (TA and SOL) was different between the two age groups. Specifically, older adults exhibited lower TA-SOL overlap (F_1,23 = 41.2, P < 0.001) and greater TA-SOL peak EMG delay (F_1,25 = 35.5, P < 0.001). This finding suggests that although subjects in both age groups displayed similar movement end points, they exhibited a different motor plan, as demonstrated by altered coordination between the agonist and antagonist muscles.NEW & NOTEWORTHY We aimed to determine whether the altered activation of muscles in older adults compared with young adults during fast goal-directed movements is related to an altered motor plan. For matched movements, there were differences in the coordination of antagonistic muscles but no differences in the individual activation of muscles. We provide novel evidence that the differential activation of muscles in older adults is related to an altered motor plan.

Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control

The current rise of neurodevelopmental disorders poses a critical need to detect risk early in order to rapidly intervene. One of the tools pediatricians use to track development is the standard growth chart. The growth charts are somewhat limited in predicting possible neurodevelopmental issues. They rely on linear models and assumptions of normality for physical growth data - obscuring key statistical information about possible neurodevelopmental risk in growth data that actually has accelerated, non-linear rates-of-change and variability encompassing skewed distributions. Here, we use new analytics to profile growth data from 36 newborn babies that were tracked longitudinally for 5 months. By switching to incremental (velocity-based) growth charts and combining these dynamic changes with underlying fluctuations in motor performance - as the transition from spontaneous random noise to a systematic signal - we demonstrate a method to detect very early stunting in the development of voluntary neuromotor control and to flag risk of neurodevelopmental derail.