Spinal circuits can accommodate interaction torques during multijoint limb movements

Inverting a model of neuromuscular control to estimate descending activation patterns that generate fast-reaching movements

Reaching movements generally show smooth kinematic profiles that are invariant across varying movement speeds even as interaction torques and muscle properties vary nonlinearly with speed. How the brain brings about these invariant profiles is an open question. We developed an analytical inverse dynamics method to estimate descending activation patterns directly from observed joint angle trajectories based on a simple model of the stretch reflex, and of muscle and biomechanical dynamics. We estimated descending activation patterns for experimental data from eight different planar two-joint movements performed at two movement times (fast: 400 ms; slow: 800 ms). The temporal structure of descending activation differed qualitatively across speeds, consistent with the idea that the nervous system uses an internal model to generate anticipatory torques during fast movement. This temporal structure also depended on the cocontraction level of antagonistic muscle groups. Comparing estimated muscle activation and descending activation revealed the contribution of the stretch reflex to movement generation that was found to set in after about 20% of movement time.NEW & NOTEWORTHY By estimating descending activation patterns directly from observed movement kinematics based on a model of the dynamics of the stretch reflex, of muscle force generation, and of the biomechanics of the limb, we observed how brain signals must be temporally structured to enable fast movement.

Age-Related Changes in Inter-Joint Interactions for Global and Local Kinematics While Standing

Inter-joint interactions are involved in human standing. These interactions work not only for global kinematics that control the center of mass (COM) of the entire body, but also for local kinematics that control joint angular movements. Age-related changes in these interactions are thought to cause unstable standing postures in older people. Interactions of global kinematics are known to be deficient owing to aging. However, it is unclear whether the interaction of local kinematics is affected by aging. We investigated the age-related changes in inter-joint interactions, especially local kinematics, during standing. Differences were investigated in these two inter-joint interactions between older and younger adults in three different postures: normal, eyes-closed, and foam-surface standings. The inter-joint interaction for local kinematics was computed using the induced-acceleration analysis with a double-inverted pendulum model and quantified using an uncontrolled manifold approach. Consistent with previous studies, the inter-joint interaction for COM acceleration (global kinematics) deteriorated in older adults. In contrast, the interactions for angular accelerations in the ankle and hip joints (local kinematics) were slightly better in the older adults. Moreover, the individual components of angular acceleration which were induced by net torques from homonymous and remote joints were significantly increased in older adults. Thus, global and local inter-joint interactions are driven by distinct neural mechanisms and the interaction of local kinematics can compensate for the increment of each component of joint angular acceleration in older adults.

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.

Putting down the revolt: Enactivism as a philosophy of nature

Enactivists frequently argue their account heralds a revolution in cognitive science: enactivism will unseat cognitivism as the dominant paradigm. We examine the lines of reasoning enactivists employ in stirring revolt, but show that none of these prove compelling reasons for cognitivism to be replaced by enactivism. First, we examine the hard sell of enactivism: enactivism reveals a critical explanatory gap at the heart of cognitivism. We show that enactivism does not meet the requirements to incite a paradigm shift in the Kuhnian sense—there is no internal crisis in cognitivism. Nor does it provide inherently better explanations of cognition as some have claimed. Second, we consider the soft sell of enactivism: enactivism provides a more attractive, parsimonious, or clear-eyed lens on cognition. This move proves to boil down to a misunderstanding of how theories are selected in science. Instead we lend support to a broader and more desirable way to conceive of enactivism, the recent proposal that enactivism is a philosophy of nature. We explain how a philosophy of nature does more than support a single research paradigm by integrating scientific questions into a cohesive picture.

Quadriceps muscle stimulation evokes heteronymous inhibition onto soleus with limited Ia activation compared to femoral nerve stimulation

Heteronymous excitatory feedback from muscle spindles and inhibitory feedback from Golgi tendon organs and recurrent inhibitory circuits can influence motor coordination. The functional role of inhibitory feedback is difficult to determine, because nerve stimulation, the primary method used in humans, cannot evoke inhibition without first activating the largest diameter muscle spindle axons. Here, we tested the hypothesis that quadriceps muscle stimulation could be used to examine heteronymous inhibition more selectively when compared to femoral nerve stimulation by comparing the effects of nerve and muscle stimulation onto ongoing soleus EMG held at 20% of maximal effort. Motor threshold and two higher femoral nerve and quadriceps stimulus intensities matched by twitch evoked torque magnitudes were examined. We found that significantly fewer participants exhibited excitation during quadriceps muscle stimulation when compared to nerve stimulation (14-29% vs. 64-71% of participants across stimulation intensities) and the magnitude of heteronymous excitation from muscle stimulation, when present, was much reduced compared to nerve stimulation. Muscle and nerve stimulation resulted in heteronymous inhibition that significantly increased with increasing stimulation evoked torque magnitudes. This study provides novel evidence that muscle stimulation may be used to more selectively examine inhibitory heteronymous feedback between muscles in the human lower limb when compared to nerve stimulation.

A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements

Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

Active inference through whiskers

Rodents use whisking to probe actively their environment and to locate objects in space, hence providing a paradigmatic biological example of active sensing. Numerous studies show that the control of whisking has anticipatory aspects. For example, rodents target their whisker protraction to the distance at which they expect objects, rather than just reacting fast to contacts with unexpected objects. Here we characterize the anticipatory control of whisking in rodents as an active inference process. In this perspective, the rodent is endowed with a prior belief that it will touch something at the end of the whisker protraction, and it continuously modulates its whisking amplitude to minimize (proprioceptive and somatosensory) prediction errors arising from an unexpected whisker-object contact, or from a lack of an expected contact. We will use the model to qualitatively reproduce key empirical findings about the ways rodents modulate their whisker amplitude during exploration and the scanning of (expected or unexpected) objects. Furthermore, we will discuss how the components of active inference model can in principle map to the neurobiological circuits of rodent whisking.

The computational neurology of movement under active inference

We propose a computational neurology of movement based on the convergence of theoretical neurobiology and clinical neurology. A significant development in the former is the idea that we can frame brain function as a process of (active) inference, in which the nervous system makes predictions about its sensory data. These predictions depend upon an implicit predictive (generative) model used by the brain. This means neural dynamics can be framed as generating actions to ensure sensations are consistent with these predictions-and adjusting predictions when they are not. We illustrate the significance of this formulation for clinical neurology by simulating a clinical examination of the motor system using an upper limb coordination task. Specifically, we show how tendon reflexes emerge naturally under the right kind of generative model. Through simulated perturbations, pertaining to prior probabilities of this model's variables, we illustrate the emergence of hyperreflexia and pendular reflexes, reminiscent of neurological lesions in the corticospinal tract and cerebellum. We then turn to the computational lesions causing hypokinesia and deficits of coordination. This in silico lesion-deficit analysis provides an opportunity to revisit classic neurological dichotomies (e.g. pyramidal versus extrapyramidal systems) from the perspective of modern approaches to theoretical neurobiology-and our understanding of the neurocomputational architecture of movement control based on first principles.

Human muscle activity and lower limb biomechanics of overground walking at varying levels of simulated reduced gravity and gait speeds

Reducing the mechanical load on the human body through simulated reduced gravity can reveal important insight into locomotion biomechanics. The purpose of this study was to quantify the effects of simulated reduced gravity on muscle activation levels and lower limb biomechanics across a range of overground walking speeds. Our overall hypothesis was that muscle activation amplitudes would not decrease proportionally to gravity level. We recruited 12 participants (6 female, 6 male) to walk overground at 1.0, 0.76, 0.55, and 0.31 G for four speeds: 0.4, 0.8, 1.2, and 1.6 ms^-1. We found that peak ground reaction forces, peak knee extension moment in early stance, peak hip flexion moment, and peak ankle extension moment all decreased substantially with reduced gravity. The peak knee extension moment at late stance/early swing did not change with gravity. The effect of gravity on muscle activity amplitude varied considerably with muscle and speed, often varying nonlinearly with gravity level. Quadriceps (rectus femoris, vastus lateralis, & vastus medialis) and medial gastrocnemius activity decreased in stance phase with reduced gravity. Soleus and lateral gastrocnemius activity had no statistical differences with gravity level. Tibialis anterior and biceps femoris increased with simulated reduced gravity in swing and stance phase, respectively. The uncoupled relationship between simulated gravity level and muscle activity have important implications for understanding biomechanical muscle functions during human walking and for the use of bodyweight support for gait rehabilitation after injury.

Neural control of matched motor units during muscle shortening and lengthening at increasing velocities

Modulation of movement velocity is necessary during daily life tasks, work, and sports activities. However, assessing motor unit behavior during muscle shortening and lengthening at different velocities is challenging. High-density surface electromyography (HD-sEMG) is an established method to identify and track motor unit behavior in isometric contractions. Therefore, we used this methodology to unravel the behavior of the same motor units in dynamic contractions at low contraction velocities. Velocity-related changes in tibialis anterior motor unit behavior during concentric and eccentric contractions at 10% and 25% maximum voluntary isometric contraction were assessed by decomposing HD-sEMG signals recorded from the tibialis anterior muscle of eleven healthy participants at 5°/s, 10°/s, and 20°/s. Motor units extracted from the dynamic contractions were tracked across different velocities at the same load levels. On average, 14 motor units/participant were matched across different velocities, showing specific changes in discharge rate modulation. Specifically, increased velocity led to an increased rate of change in discharge rate (e.g., discharge rate slope, P = 0.025), recruitment and derecruitment discharge rates (P = 0.003 and P = 0.001), and decreased recruitment angles (P = 0.0001). Surprisingly, the application of the motor unit extraction filters calculated from 20°/s onto the recordings at 5°/s and 10°/s revealed that >92% of motor units recruited at the highest velocity were active on both lower velocities, indicating no additional recruitment of motor units. Our results suggest that motor unit rate coding rather than recruitment is responsible for controlling muscle shortening and lengthening contractions at increasing velocities against a constant load.NEW & NOTEWORTHY The control of movement velocity is accomplished by the modulation of the neural drive to muscle and its variation over time. In this study, we tracked motor units decomposed from HD-sEMG across shortening and lengthening contractions at increasing velocities in two submaximal load levels. We demonstrate that concentric and eccentric contractions of the tibialis anterior muscle at slow velocities are achieved by specific motor unit rate coding strategies rather than distinct recruitment schemes.

Embodied skillful performance: where the action is

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory (OMCT), as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed-a motor command. This paper aims to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference-behavioral modeling frameworks that descend, but are distinct, from OMCT-and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference.

Long-latency reflexes for inter-effector coordination reflect a continuous state feedback controller

Successful performance in many everyday tasks requires compensating unexpected mechanical disturbance to our limbs and body. The long-latency reflex plays an important role in this process because it is the fastest response to integrate sensory information across several effectors, like when linking the elbow and shoulder or the arm and body. Despite the dozens of studies on inter-effector long-latency reflexes, there has not been a comprehensive treatment of how these reveal the basic control organization that sets constraints on any candidate model of neural feedback control such as optimal feedback control. We considered three contrasting ways that controllers can be organized: multiple independent controllers vs. a multiple-input multiple-output (MIMO) controller, a continuous feedback controller vs. an intermittent feedback controller, and a direct MIMO controller vs. a state feedback controller. Following a primer on control theory and review of the relevant evidence, we conclude that continuous state feedback control best describes the organization of inter-effector coordination by the long-latency reflex.

Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint

The study aimed at investigating the extent to which the brain adaptively exploits or compensates interaction torque (IT) during movement control in various velocity and load conditions. Participants performed arm pointing movements toward a horizontal plane without a prescribed reach endpoint at slow, neutral and rapid speeds and with/without load attached to the forearm. Experimental results indicated that IT overall contributed to net torque (NT) to assist the movement, and that such contribution increased with limb inertia and instructed speed and led to hand trajectory variations. We interpreted these results within the (inverse) optimal control framework, assuming that the empirical arm trajectories derive from the minimization of a certain, possibly composite, cost function. Results indicated that mixing kinematic, energetic and dynamic costs was necessary to replicate the participants' adaptive behavior at both kinematic and dynamic levels. Furthermore, the larger contribution of IT to NT was associated with an overall decrease of the kinematic cost contribution and an increase of its dynamic/energetic counterparts. Altogether, these results suggest that the adaptive use of IT might be tightly linked to the optimization of a composite cost which implicitly favors more the kinematic or kinetic aspects of movement depending on load and speed.

Long-latency reflexes of elbow and shoulder muscles suggest reciprocal excitation of flexors, reciprocal excitation of extensors, and reciprocal inhibition between flexors and extensors

Postural corrections of the upper limb are required in tasks ranging from handling an umbrella in the changing wind to securing a wriggling baby. One complication in this process is the mechanical interaction between the different segments of the arm where torque applied at one joint induces motion at multiple joints. Previous studies have shown the long-latency reflexes of shoulder muscles (50-100 ms after a limb perturbation) account for these mechanical interactions by integrating information about motion of both the shoulder and elbow. It is less clear whether long-latency reflexes of elbow muscles exhibit a similar capability and what is the relation between the responses of shoulder and elbow muscles. The present study utilized joint-based loads tailored to the subjects' arm dynamics to induce well-controlled displacements of their shoulder and elbow. Our results demonstrate that the long-latency reflexes of shoulder and elbow muscles integrate motion from both joints: the shoulder and elbow flexors respond to extension at both joints, whereas the shoulder and elbow extensors respond to flexion at both joints. This general pattern accounts for the inherent flexion-extension coupling of the two joints arising from the arm's intersegmental dynamics and is consistent with spindle-based reciprocal excitation of shoulder and elbow flexors, reciprocal excitation of shoulder and elbow extensors, and across-joint inhibition between the flexors and extensors.