Diverse and complex muscle spindle afferent firing properties emerge from multiscale muscle mechanics

MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks

Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet's focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.

Reduced rate of force development under fatigued conditions is associated to the decline in force complexity in adult males

PURPOSE

This study aimed to verify whether the slowing of muscle contraction quickness, typically observed in states of fatigue, may worsen force control by decreasing the rate with which force fluctuations are modulated. Therefore, we investigated the relationship between rate of force development (RFD), and force fluctuations' magnitude (Coefficient of variation, CoV) and complexity (Approximate Entropy, ApEn; Detrended fluctuation analysis, DFAα).

METHODS

Fourteen participants performed intermittent ballistic isometric contractions of the plantar dorsiflexors at 70% of maximal voluntary force until task failure (under 60% twice).

RESULTS

Indices of RFD (RFDpeak, RFD50, RFD100, and RFD150) decreased over time by approximately 46, 32, 44, and 39%, respectively (p all ≤ 0.007). DFAα increased by 10% (p < 0.001), and CoV increased by 15% (p < 0.001), indicating decreased force complexity along with increased force fluctuations, respectively. ApEn decreased by just over a quarter (28%, p < 0.001). The linear hierarchical models showed negative associations between RFDpeak and DFAα (β =  - 3.6 10-4, p < 0.001), CoV (β =  - 1.8 10-3, p < 0.001), while ApEn showed a positive association (β = 8.2 × 10-5, p < 0.001).

CONCLUSION

The results suggest that exercise-induced reductions in contraction speed, lead to smoother force complexity and diminished force control due to slower adjustments around the target force. The fatigued state resulted in worsened force producing capacity and overall force control.

Modeling proprioception with task-driven neural network models

In a recent issue of Cell, Vargas and colleagues1 demonstrate that task-driven neural network models are superior at predicting proprioceptive activity in the primate cuneate nucleus and sensorimotor cortex compared with other models. This provides valuable insights for better understanding the proprioceptive pathway.

Task-driven neural network models predict neural dynamics of proprioception

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

Conserved mammalian muscle mechanics during eccentric contractions

Skeletal muscle has a broad range of biomechanical functions, including power generation and energy absorption. These roles are underpinned by the force-velocity relationship, which comprises two distinct components: a concentric and an eccentric force-velocity relationship. The concentric component has been extensively studied across a wide range of muscles with different muscle properties. However, to date, little progress has been made in accurately characterising the eccentric force-velocity relationship in mammalian muscle with varying muscle properties. Consequently, mathematical models of this muscle behaviour are based on a poorly understood phenomenon. Here, we present a comprehensive assessment of the concentric force-velocity and eccentric force-velocity relationships of four mammalian muscles (soleus, extensor digitorum longus, diaphragm and digastric) with varying biomechanical functions, spanning three orders of magnitude in body mass (mouse, rat and rabbits). The force-velocity relationship was characterised using a hyperbolic-linear equation for the concentric component a hyperbolic equation for the eccentric component, at the same time as measuring the rate of force development in the two phases of force development in relation to eccentric lengthening velocity. We demonstrate that, despite differences in the curvature and plateau height of the eccentric force-velocity relationship, the rates of relative force development were consistent for the two phases of the force-time response during isovelocity lengthening ramps, in relation to lengthening velocity, in the four muscles studied. Our data support the hypothesis that this relationship depends on cross-bridge and titin activation. Hill-type musculoskeletal models of the eccentric force-velocity relationship for mammalian muscles should incorporate this biphasic force response. KEY POINTS: The capacity of skeletal muscle to generate mechanical work and absorb energy is underpinned by the force-velocity relationship. Despite identification of the lengthening (eccentric) force-velocity relationship over 80 years ago, no comprehensive study has been undertaken to characterise this relationship in skeletal muscle. We show that the biphasic force response seen during active muscle lengthening is conserved over three orders of magnitude of mammalian skeletal muscle mass. Using mice with a small deletion in titin, we show that part of this biphasic force profile in response to muscle lengthening is reliant on normal titin activation. The rate of force development during muscle stretch may be a more reliable way to describe the forces experienced during eccentric muscle contractions compared to the traditional hyperbolic curve fitting, and functions as a novel predictor of force-velocity characteristics that may be used to better inform hill-type musculoskeletal models and assess pathophysiological remodelling.

Mechanosensory encoding of forces in walking uphill and downhill: force feedback can stabilize leg movements in stick insects

Force feedback could be valuable in adapting walking to diverse terrains, but the effects of changes in substrate inclination on discharges of sensory receptors that encode forces have rarely been examined. In insects, force feedback is provided by campaniform sensilla, mechanoreceptors that monitor forces as cuticular strains. We neurographically recorded responses of stick insect tibial campaniform sensilla to "naturalistic" forces (joint torques) that occur at the hind leg femur-tibia (FT) joint in uphill, downhill, and level walking. The FT joint torques, obtained in a previous study that used inverse dynamics to analyze data from freely moving stick insects, are quite variable during level walking (including changes in sign) but are larger in magnitude and more consistent when traversing sloped surfaces. Similar to vertebrates, insects used predominantly extension torque in propulsion on uphill slopes and flexion torques to brake forward motion when going downhill. Sensory discharges to joint torques reflected the torque direction but, unexpectedly, often occurred as multiple bursts that encoded the rate of change of positive forces (dF/dt) even when force levels were high. All discharges also showed hysteresis (history dependence), as firing substantially decreased or ceased during transient force decrements. These findings have been tested in simulation in a mathematical model of the sensilla (Szczecinski NS, Dallmann CJ, Quinn RD, Zill SN. Bioinspir Biomim 16: 065001, 2021) that accurately reproduced the biological data. Our results suggest the hypothesis that sensory feedback from the femoro-tibial joint indicating force dynamics (dF/dt) can be used to counter the instability in traversing sloped surfaces in animals and, potentially, in walking machines.NEW & NOTEWORTHY Discharges of sensory receptors (campaniform sensilla) in the hind legs of stick insects can differentially signal forces that occur in walking uphill versus walking downhill. Unexpectedly, sensory firing most closely reflects the rate of change of force (dF/dt) even when the force levels are high. These signals have been replicated in a mathematical model of the receptors and could be used to stabilize leg movements both in the animal and in a walking robot.

Mechanosensory encoding in ex vivo muscle-nerve preparations

Our objective was to evaluate an ex vivo muscle-nerve preparation used to study mechanosensory signalling by low threshold mechanosensory receptors (LTMRs). Specifically, we aimed to assess how well the ex vivo preparation represents in vivo firing behaviours of the three major LTMR subtypes of muscle primary sensory afferents, namely type Ia and II muscle spindle (MS) afferents and type Ib tendon organ afferents. Using published procedures for ex vivo study of LTMRs in mouse hindlimb muscles, we replicated earlier reports on afferent firing in response to conventional stretch paradigms applied to non-contracting, that is passive, muscle. Relative to in vivo studies, stretch-evoked firing for confirmed MS afferents in the ex vivo preparation was markedly reduced in firing rate and deficient in encoding dynamic features of muscle stretch. These deficiencies precluded conventional means of discriminating type Ia and II afferents. Muscle afferents, including confirmed Ib afferents were often indistinguishable based on their similar firing responses to the same physiologically relevant stretch paradigms. These observations raise uncertainty about conclusions drawn from earlier ex vivo studies that either attribute findings to specific afferent types or suggest an absence of treatment effects on dynamic firing. However, we found that replacing the recording solution with bicarbonate buffer resulted in afferent firing rates and profiles more like those seen in vivo. Improving representation of the distinctive sensory encoding properties in ex vivo muscle-nerve preparations will promote accuracy in assigning molecular markers and mechanisms to heterogeneous types of muscle mechanosensory neurons.

Attenuation of muscle spindle firing with artificially increased series compliance during stretch of relaxed muscle

Muscle spindles relay vital mechanosensory information for movement and posture, but muscle spindle feedback is coupled to skeletal motion by a compliant tendon. Little is known about the effects of tendon compliance on muscle spindle feedback during movement, and the complex firing of muscle spindles makes these effects difficult to predict. Our goal was to investigate changes in muscle spindle firing using added series elastic elements (SEEs) to mimic a more compliant tendon, and to characterize the accompanying changes in firing with respect to muscle-tendon unit (MTU) and muscle fascicle displacements (recorded via sonomicrometry). Sinusoidal, ramp-and-hold and triangular stretches were analysed to examine potential changes in muscle spindle instantaneous firing rates (IFRs) in locomotor- and perturbation-like stretches as well as serial history dependence. Added SEEs effectively reduced overall MTU stiffness and generally reduced muscle spindle firing rates, but the effect differed across stretch types. During sinusoidal stretches, peak and mean firing rates were not reduced and IFR was best-correlated with fascicle velocity. During ramp stretches, SEEs reduced the initial burst, dynamic and static responses of the spindle. Notably, IFR was negatively related to fascicle displacement during the hold phase. During triangular stretches, SEEs reduced the mean IFR during the first and second stretches, affecting the serial history dependence of mean IFR. Overall, these results demonstrate that tendon compliance may attenuate muscle spindle feedback during movement, but these changes cannot be fully explained by reduced muscle fascicle length or velocity, or MTU force.

Intrafusal cross-bridge dynamics shape history-dependent muscle spindle responses to stretch

Computational models can be critical to linking complex properties of muscle spindle organs to the sensory information that they encode during behaviours such as postural sway and locomotion where few muscle spindle recordings exist. Here, we augment a biophysical muscle spindle model to predict the muscle spindle sensory signal. Muscle spindles comprise several intrafusal muscle fibres with varied myosin expression and are innervated by sensory neurons that fire during muscle stretch. We demonstrate how cross-bridge dynamics from thick and thin filament interactions affect the sensory receptor potential at the spike initiating region. Equivalent to the Ia afferent's instantaneous firing rate, the receptor potential is modelled as a linear sum of the force and rate change of force (yank) of a dynamic bag1 fibre and the force of a static bag2/chain fibre. We show the importance of inter-filament interactions in (i) generating large changes in force at stretch onset that drive initial bursts and (ii) faster recovery of bag fibre force and receptor potential following a shortening. We show how myosin attachment and detachment rates qualitatively alter the receptor potential. Finally, we show the effect of faster recovery of receptor potential on cyclic stretch-shorten cycles. Specifically, the model predicts history-dependence in muscle spindle receptor potentials as a function of inter-stretch interval (ISI), pre-stretch amplitude and the amplitude of sinusoidal stretches. This model provides a computational platform for predicting muscle spindle response in behaviourally relevant stretches and can link myosin expression seen in healthy and diseased intrafusal muscle fibres to muscle spindle function.

Biophysical model of muscle spindle encoding

Muscle spindles encode mechanosensory information by mechanisms that remain only partially understood. Their complexity is expressed in mounting evidence of various molecular mechanisms that play essential roles in muscle mechanics, mechanotransduction and intrinsic modulation of muscle spindle firing behaviour. Biophysical modelling provides a tractable approach to achieve more comprehensive mechanistic understanding of such complex systems that would be difficult/impossible by more traditional, reductionist means. Our objective here was to construct the first integrative biophysical model of muscle spindle firing. We leveraged current knowledge of muscle spindle neuroanatomy and in vivo electrophysiology to develop and validate a biophysical model that reproduces key in vivo muscle spindle encoding characteristics. Crucially, to our knowledge, this is the first computational model of mammalian muscle spindle that integrates the asymmetric distribution of known voltage-gated ion channels (VGCs) with neuronal architecture to generate realistic firing profiles, both of which seem likely to be of great biophysical importance. Results predict that particular features of neuronal architecture regulate specific characteristics of Ia encoding. Computational simulations also predict that the asymmetric distribution and ratios of VGCs is a complementary and, in some instances, orthogonal means to regulate Ia encoding. These results generate testable hypotheses and highlight the integral role of peripheral neuronal structure and ion channel composition and distribution in somatosensory signalling.

A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers

The muscle spindle is an essential proprioceptor, significantly involved in sensing limb position and movement. Although biological spindle models exist for years, the gold-standard for motor control in biomechanics are still sensors built of homogenized spindle output models due to their simpler combination with neuro-musculoskeletal models. Aiming to improve biomechanical simulations, this work establishes a more physiological model of the muscle spindle, aligned to the advantage of easy integration into large-scale musculoskeletal models. We implemented four variations of a spindle model in Matlab/Simulink®: the Mileusnic et al. (2006) model, Mileusnic model without mass, our enhanced Hill-type model, and our enhanced Hill-type model with parallel damping element (PDE). Different stretches in the intrafusal fibers were simulated in all model variations following the spindle afferent recorded in previous experiments in feline soleus muscle. Additionally, the enhanced Hill-type models had their parameters extensively optimized to match the experimental conditions, and the resulting model was validated against data from rats' triceps surae muscle. As result, the Mileusnic models present a better overall performance generating the afferent firings compared to the common data evaluated. However, the enhanced Hill-type model with PDE exhibits a more stable performance than the original Mileusnic model, at the same time that presents a well-tuned Hill-type model as muscle spindle fibers, and also accounts for real sarcomere force-length and force-velocity aspects. Finally, our activation dynamics is similar to the one applied to Hill-type model for extrafusal fibers, making our proposed model more easily integrated in multi-body simulations.

History-dependent muscle resistance to stretch remains high after small, posturally relevant pre-movements

The contributions of intrinsic muscle fiber resistance during mechanical perturbations to standing and other postural behaviors are unclear. Muscle short-range stiffness is known to vary depending on the current level and history of the muscle's activation, as well as the muscle's recent movement history; this property has been referred to as history dependence or muscle thixotropy. However, we currently lack sufficient data about the degree to which muscle stiffness is modulated across posturally relevant characteristics of muscle stretch and activation. We characterized the history dependence of muscle's resistance to stretch in single, permeabilized, activated, muscle fibers in posturally relevant stretch conditions and activation levels. We used a classic paired muscle stretch paradigm, varying the amplitude of a 'conditioning' triangular stretch-shorten cycle followed by a 'test' ramp-and-hold imposed after a variable inter-stretch interval. We tested low (<15%), intermediate (15-50%) and high (>50%) muscle fiber activation levels, evaluating short-range stiffness and total impulse in the test stretch. Muscle fiber resistance to stretch remained high at conditioning amplitudes of <1% optimal fiber length, L0, and inter-stretch intervals of >1 s, characteristic of healthy standing postural sway. An ∼70% attenuation of muscle resistance to stretch was reached at conditioning amplitudes of >3% L0 and inter-stretch intervals of <0.1 s, characteristic of larger, faster postural sway in balance-impaired individuals. The thixotropic changes cannot be predicted solely on muscle force at the time of stretch. Consistent with the disruption of muscle cross-bridges, muscle resistance to stretch during behavior can be substantially attenuated if the prior motion is large enough and/or frequent enough.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Voluntary muscle coactivation in quiet standing elicits reciprocal rather than coactive agonist-antagonist control of reactive balance

Muscle coactivation increases in challenging balance conditions as well as with advanced age and mobility impairments. Increased muscle coactivation can occur both in anticipation of (feedforward) and in reaction to (feedback) perturbations, however, the causal relationship between feedforward and feedback muscle coactivation remains elusive. Here, we hypothesized that feedforward muscle coactivation would increase both the body's initial mechanical resistance due to muscle intrinsic properties and the later feedback-mediated muscle coactivation in response to postural perturbations. Young adults voluntarily increased leg muscle coactivation using visual biofeedback before support-surface perturbations. In contrast to our hypothesis, feedforward muscle coactivation did not increase the body's initial intrinsic resistance to perturbations, nor did it increase feedback muscle coactivation. Rather, perturbations with feedforward muscle coactivation elicited a medium- to long-latency increase of feedback-mediated agonist activity but a decrease of feedback-mediated antagonist activity. This reciprocal rather than coactivation effect on ankle agonist and antagonist muscles enabled faster reactive ankle torque generation, reduced ankle dorsiflexion, and reduced center of mass (CoM) motion. We conclude that in young adults, voluntary feedforward muscle coactivation can be independently modulated with respect to feedback-mediated muscle coactivation. Furthermore, our findings suggest feedforward muscle coactivation may be useful for enabling quicker joint torque generation through reciprocal, rather than coactivated, agonist-antagonist feedback muscle activity. As such our results suggest that behavioral context is critical to whether muscle coactivation functions to increase agility versus stability.NEW & NOTEWORTHY Feedforward and feedback muscle coactivation are commonly observed in older and mobility impaired adults and are considered strategies to improve stability by increasing body stiffness prior to and in response to perturbations. In young adults, voluntary feedforward coactivation does not necessarily increase feedback coactivation in response to perturbations. Instead, feedforward coactivation enabled faster ankle torques through reciprocal agonist-antagonist muscle activity. As such, coactivation may promote either agility or stability depending on the behavioral context.

Linking cortex and contraction-Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons  and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

How to Confuse Motor Control: Passive Muscle Shortening after Contraction in Lengthened Position Reduces the Muscular Holding Stability in the Sense of Adaptive Force

Adaptation to external forces relies on a well-functioning proprioceptive system including muscle spindle afferents. Muscle length and tension control in reaction to external forces is most important regarding the Adaptive Force (AF). This study investigated the effect of different procedures, which are assumed to influence the function of muscle spindles, on the AF. Elbow flexors of 12 healthy participants (n = 19 limbs) were assessed by an objectified manual muscle test (MMT) with different procedures: regular MMT, MMT after precontraction (self-estimated 20% MVIC) in lengthened position with passive return to test position (CL), and MMT after CL with a second precontraction in test position (CL-CT). During regular MMTs, muscles maintained their length up to 99.7% ± 1.0% of the maximal AF (AFmax). After CL, muscles started to lengthen at 53.0% ± 22.5% of AFmax. For CL-CT, muscles were again able to maintain the static position up to 98.3% ± 5.5% of AFmax. AFisomax differed highly significantly between CL vs. CL-CT and regular MMT. CL was assumed to generate a slack of muscle spindles, which led to a substantial reduction of the holding capacity. This was immediately erased by a precontraction in the test position. The results substantiate that muscle spindle sensitivity seems to play an important role for neuromuscular functioning and musculoskeletal stability.

Fascicle dynamics of the tibialis anterior muscle reflect whole-body walking economy

Humans can inherently adapt their gait pattern in a way that minimizes the metabolic cost of transport, or walking economy, within a few steps, which is faster than any known direct physiological sensor of metabolic energy. Instead, walking economy may be indirectly sensed through mechanoreceptors that correlate with the metabolic cost per step to make such gait adaptations. We tested whether velocity feedback from tibialis anterior (TA) muscle fascicles during the early stance phase of walking could potentially act to indirectly sense walking economy. As participants walked within a range of steady-state speeds and step frequencies, we observed that TA fascicles lengthen on almost every step. Moreover, the average peak fascicle velocity experienced during lengthening reflected the metabolic cost of transport of the given walking condition. We observed that the peak TA muscle activation occurred earlier than could be explained by a short latency reflex response. The activation of the TA muscle just prior to heel strike may serve as a prediction of the magnitude of the ground collision and the associated energy exchange. In this scenario, any unexpected length change experienced by the TA fascicle would serve as an error signal to the nervous system and provide additional information about energy lost per step. Our work helps provide a biomechanical framework to understand the possible neural mechanisms underlying the rapid optimization of walking economy.

The association between muscle architecture and muscle spindle abundance

Across the human body, skeletal muscles have a broad range of biomechanical roles that employ complex proprioceptive control strategies to successfully execute a desired movement. This information is derived from peripherally located sensory apparatus, the muscle spindle and Golgi tendon organs. The abundance of these sensory organs, particularly muscle spindles, is known to differ considerably across individual muscles. Here we present a comprehensive data set of 119 muscles across the human body including architectural properties (muscle fibre length, mass, pennation angle and physiological cross-sectional area) and statistically test their relationships with absolute spindle number and relative spindle abundance (the residual value of the linear regression of the log-transformed spindle number and muscle mass). These data highlight a significant positive relationship between muscle spindle number and fibre length, emphasising the importance of fibre length as an input into the central nervous system. However, there appears to be no relationship between muscles architecturally optimised to function as displacement specialists and their provision of muscle spindles. Additionally, while there appears to be regional differences in muscle spindle abundance, independent of muscle mass and fibre length, our data provide no support for the hypothesis that muscle spindle abundance is related to anatomical specialisation.

Muscle spindles and their role in maintaining robust locomotion

Muscle spindles, one of the two main classes of proprioceptors together with Golgi tendon organs, are sensory structures that keep the central nervous system updated about the position and movement of body parts. Although they were discovered more than 150 years ago, their function during movement is not yet fully understood. Here, we summarize the morphology and known functions of muscle spindles, with a particular focus on locomotion. Although certain properties such as the sensitivity to dynamic and static muscle stretch are long known, recent advances in molecular biology have allowed the characterization of the molecular mechanisms for signal transduction in muscle spindles. Building upon classic literature showing that a lack of sensory feedback is deleterious to locomotion, we bring to the discussion more recent findings that support a pivotal role of muscle spindles in maintaining murine and human locomotor robustness, defined as the ability to cope with perturbations. Yet, more research is needed to expand the existing mechanistic understanding of how muscle spindles contribute to the production of robust, functional locomotion in real world settings. Future investigations should focus on combining different animal models to identify, in health and disease, those peripheral, spinal and brain proprioceptive structures involved in the fine tuning of motor control when locomotion happens in challenging conditions.

Skeletal muscle function underpins muscle spindle abundance

Muscle spindle abundance is highly variable within and across species, but we currently lack any clear picture of the mechanistic causes or consequences of this variation. Previous use of spindle abundance as a correlate for muscle function implies a mechanical underpinning to this variation, but these ideas have not been tested. Herein, we use integrated medical imaging and subject-specific musculoskeletal models to investigate the relationship between spindle abundance, muscle architecture and in vivo muscle behaviour in the human locomotor system. These analyses indicate that muscle spindle number is tightly correlated with muscle fascicle length, absolute fascicle length change, velocity of fibre lengthening and active muscle forces during walking. Novel correlations between functional indices and spindle abundance are also recovered, where muscles with a high abundance predominantly function as springs, compared to those with a lower abundance mostly functioning as brakes during walking. These data demonstrate that muscle fibre length, lengthening velocity and fibre force are key physiological signals to the central nervous system and its modulation of locomotion, and that muscle spindle abundance may be tightly correlated to how a muscle generates work. These insights may be combined with neuromechanics and robotic studies of motor control to help further tease apart the functional drivers of muscle spindle composition.

Translations of the Humeral Head Elicit Reflexes in Rotator Cuff Muscles That Are Larger Than Those in the Primary Shoulder Movers

Muscle activation helps stabilize the glenohumeral joint and prevent dislocations, which are more common at the shoulder than at any other human joint. Feedforward control of shoulder muscles is important for protecting the glenohumeral joint from harm caused by anticipated external perturbations. However, dislocations are frequently caused by unexpected perturbations for which feedback control is essential. Stretch-evoked reflexes elicited by translations of the glenohumeral joint may therefore be an important mechanism for maintaining joint integrity, yet little is known about them. Specifically, reflexes elicited by glenohumeral translations have only been studied under passive conditions, and there have been no investigations of how responses are coordinated across the functional groupings of muscles found at the shoulder. Our objective was to characterize stretch-evoked reflexes elicited by translations of the glenohumeral joint while shoulder muscles are active. We aimed to determine how these responses differ between the rotator cuff muscles, which are essential for maintaining glenohumeral stability, and the primary shoulder movers, which are essential for the large mobility of this joint. We evoked reflexes using anterior and posterior translations of the humeral head while participants produced voluntary isometric torque in six directions spanning the three rotational degrees-of-freedom about the shoulder. Electromyograms were used to measure the stretch-evoked reflexes elicited in nine shoulder muscles. We found that reflex amplitudes were larger in the rotator cuff muscles than in the primary shoulder movers, in part due to increased background activation during torque generation but more so due to an increased scaling of reflex responses with background activation. The reflexes we observed likely arose from the diversity of proprioceptors within the muscles and in the passive structures surrounding the shoulder. The large reflexes observed in the rotator cuff muscles suggest that feedback control of the rotator cuff augments the feedforward control that serves to compress the humeral head into the glenoid. This coordination may serve to stabilize the shoulder rapidly when preparing for and responding to unexpected disturbances.

Control of Mammalian Locomotion by Somatosensory Feedback

When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. © 2021 American Physiological Society. Compr Physiol 11:1-71, 2021.

Neural circuit mechanisms of sensorimotor disability in cancer treatment

Cancer survivors rank sensorimotor disability among the most distressing, long-term consequences of chemotherapy. Disorders in gait, balance, and skilled movements are commonly assigned to chemotoxic damage of peripheral sensory neurons without consideration of the deterministic role played by the neural circuits that translate sensory information into movement. This oversight precludes sufficient, mechanistic understanding and contributes to the absence of effective treatment for reversing chemotherapy-induced disability. We rectified this omission through the use of a combination of electrophysiology, behavior, and modeling to study the operation of a spinal sensorimotor circuit in vivo in a rat model of chronic, oxaliplatin (chemotherapy)-induced neuropathy (cOIN). Key sequential events were studied in the encoding of propriosensory information and its circuit translation into the synaptic potentials produced in motoneurons. In cOIN rats, multiple classes of propriosensory neurons expressed defective firing that reduced accurate sensory representation of muscle mechanical responses to stretch. Accuracy degraded further in the translation of propriosensory signals into synaptic potentials as a result of defective mechanisms residing inside the spinal cord. These sequential, peripheral, and central defects compounded to drive the sensorimotor circuit into a functional collapse that was consequential in predicting the significant errors in propriosensory-guided movement behaviors demonstrated here in our rat model and reported for people with cOIN. We conclude that sensorimotor disability induced by cancer treatment emerges from the joint expression of independent defects occurring in both peripheral and central elements of sensorimotor circuits.

Secondary endings of muscle spindles: Structure, reflex action, role in motor control and proprioception

NEW FINDINGS

What is the topic of this review? We describe the structure and function of secondary sensory endings of muscle spindles, their reflex action and role in motor control and proprioception. What advances does it highlight? In most mammalian skeletal muscles, secondary endings of spindles are more or much more numerous than primary endings but are much less well studied. By focusing on secondary endings in this review, we aim to redress the balance, draw attention to what is not known and stimulate future research.

ABSTRACT

Kinaesthesia and the control of bodily movement rely heavily on the sensory input from muscle spindles. Hundreds of these sensory structures are embedded in mammalian muscles. Each spindle has one or more sensory endings and its own complement of small muscle fibres that are activated by the CNS via fusimotor neurons, providing efferent control of sensory responses. Exactly how the CNS wields this influence remains the subject of much fascination and debate. There are two types of sensory endings, primary and secondary, with differing development, morphology, distribution and responsiveness. Spindle primary endings have received more attention than secondaries, although the latter usually outnumber them. This review focuses on the secondary endings. Their location within the spindle, their response properties, the projection of their afferents within the CNS and their reflex actions all suggest that secondaries have certain separate roles from the primaries in proprioception and motor control. Specifically, spindle secondaries seem more adapted than primaries to signalling slow and maintained changes in the relative position of bodily segments, thereby contributing to position sense, postural control and static limb positioning. By highlighting, in this way, the roles of secondary endings, a final aim of the review is to broaden understanding of muscle spindles more generally and of the important contributions they make to both sensory and motor mechanisms.

Computational Modeling: Human Dynamic Model

Improvements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide valuable constraints for understanding neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. The model includes the major body segments and joints to report human movements' energetic components. Its 48 degrees of freedom strike a balance between very detailed models that include muscle models and straightforward two-dimensional models. It has sufficient accuracy to analyze and synthesize movements captured in real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to animate a humanoid character. It can also estimate internal joint forces used during a movement to create effort-contingent stimuli and support controlled experiments to measure the dynamics generating human behaviors systematically. The paper describes the innovative features that allow the model to integrate its dynamic equations accurately and illustrates its performance and accuracy with demonstrations. The model has a two-foot stance ability, capable of generating results comparable with an experiment done with subjects, and illustrates the uncontrolled manifold concept. Additionally, the model's facility to capture large energetic databases opens new possibilities for theorizing as to human movement function. The model is freely available.

Disentangling acceleration-, velocity-, and duration-dependency of the short- and medium-latency stretch reflexes in the ankle plantarflexors

Motorized assessment of the stretch reflex is instrumental to gain understanding of the stretch reflex, its physiological origin and to differentiate effects of neurological disorders, like spasticity. Both short-latency (M1) and medium-latency (M2) stretch reflexes have been reported to depend on the velocity and acceleration of an applied ramp-and-hold perturbation. In the upper limb, M2 has also been reported to depend on stretch duration. However, wrong conclusions might have been drawn in previous studies as the interdependence of perturbation parameters (amplitude, duration, velocity, and acceleration) possibly created uncontrolled, confounding effects. We disentangled the duration-, velocity-, and acceleration-dependence and their interactions of the M1 and M2 stretch reflex in the ankle plantarflexors. To disentangle the parameter interdependence, 49 unique ramp-and-hold joint perturbations elicited reflexes in 10 healthy volunteers during a torque control task. Linear mixed model analysis showed that M1 depended on acceleration, not velocity or duration, whereas M2 depended on acceleration, velocity, and duration. Simulations of the muscle spindle Ia afferents coupled to a motoneuron pool corroborated these experimental findings. In addition, this simulation model did show a nonlinear M1 velocity- and duration-dependence for perturbation parameters outside the experimental scope. In conclusion, motorized assessment of the stretch reflex or spasticity using ramp-and-hold perturbations should be systematically executed and reported. Our systematic motorized and simulation assessments showed that M1 and M2 depend on acceleration, velocity, and duration of the applied perturbation. The simulation model suggested that these dependencies emerge from: muscle-tendon unit and muscle cross-bridge dynamics, Ia sensitivity to force and yank, and motoneuron synchronization.NEW & NOTEWORTHY Previous research and definitions of the stretch reflex and spasticity have focused on velocity-dependence. We showed that perturbation acceleration, velocity, and duration all shape the M1 and M2 response, often via nonlinear or interacting dependencies. Consequently, systematic execution and reporting of stretch reflex and spasticity studies, avoiding uncontrolled parameter interdependence, is essential for proper understanding of the reflex neurophysiology.

A computational model of insect campaniform sensilla predicts encoding of forces during walking

Control of forces is essential in both animals and walking machines. Insects measure forces as strains in their exoskeletons via campaniform sensilla (CS). Deformations of cuticular caps embedded in the exoskeleton excite afferents that project to the central nervous system. CS afferent firing frequency (i.e. 'discharge') is highly dynamic, correlating with the rate of change of the force. Discharges adapt over time to tonic forces and exhibit hysteresis during cyclic loading.In this study we characterized a phenomenological model that predicts CS discharge, in which discharge is proportional to the instantaneous stimulus force relative to an adaptive variable. In contrast to previous studies of sensory adaptation, our model (1) is nonlinear and (2) reproduces the characteristic power-law adaptation with first order dynamics only (i.e. no 'fractional derivatives' are required to explain dynamics). We solve the response of the system analytically in multiple cases and use these solutions to derive the dynamics of the adaptive variable. We show that the model can reproduce responses of insect CS to many different force stimuli after being tuned to reproduce only one response, suggesting that the model captures the underlying dynamics of the system. We show that adaptation to tonic forces, rate-sensitivity, and hysteresis are different manifestations of the same underlying mechanism: the adaptive variable. We tune the model to replicate the dynamics of three different CS groups from two insects (cockroach and stick insect), demonstrating that it is generalizable. We also invert the model to estimate the stimulus force given the discharge recording from the animal. We discuss the adaptive neural and mechanical processes that the model may mimic and the model's use for understanding the role of load feedback in insect motor control. A preliminary model and results were previously published in the proceedings of the Conference on Biohybrid and Biomimetic Systems.

A leg to stand on: computational models of proprioception

Dexterous motor control requires feedback from proprioceptors, internal mechanosensory neurons that sense the body's position and movement. An outstanding question in neuroscience is how diverse proprioceptive feedback signals contribute to flexible motor control. Genetic tools now enable targeted recording and perturbation of proprioceptive neurons in behaving animals; however, these experiments can be challenging to interpret, due to the tight coupling of proprioception and motor control. Here, we argue that understanding the role of proprioceptive feedback in controlling behavior will be aided by the development of multiscale models of sensorimotor loops. We review current phenomenological and structural models for proprioceptor encoding and discuss how they may be integrated with existing models of posture, movement, and body state estimation.

Abnormal center of mass feedback responses during balance: A potential biomarker of falls in Parkinson's disease

Although Parkinson disease (PD) causes profound balance impairments, we know very little about how PD impacts the sensorimotor networks we rely on for automatically maintaining balance control. In young healthy people and animals, muscles are activated in a precise temporal and spatial organization when the center of body mass (CoM) is unexpectedly moved that is largely automatic and determined by feedback of CoM motion. Here, we show that PD alters the sensitivity of the sensorimotor feedback transformation. Importantly, sensorimotor feedback transformations for balance in PD remain temporally precise, but become spatially diffuse by recruiting additional muscle activity in antagonist muscles during balance responses. The abnormal antagonist muscle activity remains precisely time-locked to sensorimotor feedback signals encoding undesirable motion of the body in space. Further, among people with PD, the sensitivity of abnormal antagonist muscle activity to CoM motion varies directly with the number of recent falls. Our work shows that in people with PD, sensorimotor feedback transformations for balance are intact but disinhibited in antagonist muscles, likely contributing to balance deficits and falls.

Diverse and complex muscle spindle afferent firing properties emerge from multiscale muscle mechanics

Despite decades of research, we lack a mechanistic framework capable of predicting how movement-related signals are transformed into the diversity of muscle spindle afferent firing patterns observed experimentally, particularly in naturalistic behaviors. Here, a biophysical model demonstrates that well-known firing characteristics of mammalian muscle spindle Ia afferents - including movement history dependence, and nonlinear scaling with muscle stretch velocity - emerge from first principles of muscle contractile mechanics. Further, mechanical interactions of the muscle spindle with muscle-tendon dynamics reveal how motor commands to the muscle (alpha drive) versus muscle spindle (gamma drive) can cause highly variable and complex activity during active muscle contraction and muscle stretch that defy simple explanation. Depending on the neuromechanical conditions, the muscle spindle model output appears to 'encode' aspects of muscle force, yank, length, stiffness, velocity, and/or acceleration, providing an extendable, multiscale, biophysical framework for understanding and predicting proprioceptive sensory signals in health and disease.