Motor primitives and synergies in the spinal cord and after injury--the current state of play

Towards humanlike grasp in robotic hands: mechanical implementation of force synergies

In the field of robotic hands, finger force coordination is usually achieved by complex mechanical structures and control systems. This study presents the design of a novel transmission system inspired from the physiological concept of force synergies, aiming to simplify the control of multifingered robotic hands. To this end, we collected human finger force data during six isometric grasping tasks, and force synergies (i.e. the synergy weightings and the corresponding activation coefficients) were extracted from the concatenated force data to explore their potential for force modulation. We then implemented two force synergies with a cable-driven transmission mechanism consisting of two spring-loaded sliders and five V-shaped bars. Specifically, we used fixed synergy weightings to determine the stiffness of the compression springs, and the displacements of sliders were determined by time-varying activation coefficients. The derived transmission system was then used to drive a five-finger robotic hand named SYN hand. We also designed a motion encoder to selectively activate desired fingers, making it possible for two motors to empower a variety of hand postures. Experiments on the prototype demonstrate successful grasp of a wide range of objects in everyday life, and the finger force distribution of SYN hand can approximate that of human hand during six typical tasks. To our best knowledge, this study shows the first attempt to mechanically implement force synergies for finger force modulation in a robotic hand. In comparison to state-of-the-art robotic hands with similar functionality, the proposed hand can distribute humanlike force ratios on the fingers by simple position control, rather than resorting to additional force sensors or complex control strategies. The outcome of this study may provide alternatives for the design of novel anthropomorphic robotic hands, and thus show application prospects in the field of hand prostheses and exoskeletons.

Neural ensemble dynamics in trunk and hindlimb sensorimotor cortex encode for the control of postural stability

The cortex has a disputed role in monitoring postural equilibrium and intervening in cases of major postural disturbances. Here, we investigate the patterns of neural activity in the cortex that underlie neural dynamics during unexpected perturbations. In both the primary sensory (S1) and motor (M1) cortices of the rat, unique neuronal classes differentially covary their responses to distinguish different characteristics of applied postural perturbations; however, there is substantial information gain in M1, demonstrating a role for higher-order computations in motor control. A dynamical systems model of M1 activity and forces generated by the limbs reveals that these neuronal classes contribute to a low-dimensional manifold comprised of separate subspaces enabled by congruent and incongruent neural firing patterns that define different computations depending on the postural responses. These results inform how the cortex engages in postural control, directing work aiming to understand postural instability after neurological disease.

Proposing a neural framework for the evolution of elaborate courtship displays

In many vertebrates, courtship occurs through the performance of elaborate behavioral displays that are as spectacular as they are complex. The question of how sexual selection acts upon these animals' neuromuscular systems to transform a repertoire of pre-existing movements into such remarkable (if not unusual) display routines has received relatively little research attention. This is a surprising gap in knowledge, given that unraveling this extraordinary process is central to understanding the evolution of behavioral diversity and its neural control. In many vertebrates, courtship displays often push the limits of neuromuscular performance, and often in a ritualized manner. These displays can range from songs that require rapid switching between two independently controlled 'voice boxes' to precisely choreographed acrobatics. Here, we propose a framework for thinking about how the brain might not only control these displays, but also shape their evolution. Our framework focuses specifically on a major midbrain area, which we view as a likely important node in the orchestration of the complex neural control of behavior used in the courtship process. This area is the periaqueductal grey (PAG), as studies suggest that it is both necessary and sufficient for the production of many instinctive survival behaviors, including courtship vocalizations. Thus, we speculate about why the PAG, as well as its key inputs, might serve as targets of sexual selection for display behavior. In doing so, we attempt to combine core ideas about the neural control of behavior with principles of display evolution. Our intent is to spur research in this area and bring together neurobiologists and behavioral ecologists to more fully understand the role that the brain might play in behavioral innovation and diversification.

A network information theoretic framework to characterise muscle synergies in space and time

Objective Current approaches to muscle synergy extraction rely on linear dimensionality reduction algorithms that make specific assumptions on the underlying signals. However, to capture nonlinear time varying, large-scale but also muscle-specific interactions, a more generalised approach is required. Approach Here we developed a novel framework for muscle synergy extraction that relaxes model assumptions by using a combination of information- and network theory and dimensionality reduction. We first quantify informational dynamics between muscles, time-samples or muscle-time pairings using a novel mutual information formulation. We then model these pairwise interactions as multiplex networks and identify modules representing the network architecture. We employ this modularity criterion as the input parameter for dimensionality reduction, which verifiably extracts the identified modules, and also to characterise salient structures within each module. Main results This novel framework captures spatial, temporal and spatiotemporal interactions across two benchmark datasets of reaching movements, producing distinct spatial groupings and both tonic and phasic temporal patterns. Readily interpretable muscle synergies spanning multiple spatial and temporal scales were identified, demonstrating significant task dependence, ability to capture trial-to-trial fluctuations and concordance across participants. Furthermore, our framework identifies submodular structures that represent the distributed networks of co-occurring signal interactions across scales. Significance The capabilities of this framework are illustrated through the concomitant continuity with previous research and novelty of the insights gained. Several previous limitations are circumvented including the extraction of functionally meaningful and multiplexed pairwise muscle couplings under relaxed model assumptions. The extracted synergies provide a holistic view of the movement while important details of task performance are readily interpretable. The identified muscle groupings transcend biomechanical constraints and the temporal patterns reveal characteristics of fundamental motor control mechanisms. We conclude that this framework opens new opportunities for muscle synergy research and can constitute a bridge between existing models and recent network-theoretic endeavours.

Embodied Cooperation to Promote Forgiving Interactions With Autonomous Machines

During every waking moment, we must engage with our environments, the people around us, the tools we use, and even our own bodies to perform actions and achieve our intentions. There is a spectrum of control that we have over our surroundings that spans the extremes from full to negligible. When the outcomes of our actions do not align with our goals, we have a tremendous capacity to displace blame and frustration on external factors while forgiving ourselves. This is especially true when we cooperate with machines; they are rarely afforded the level of forgiveness we provide our bodies and often bear much of our blame. Yet, our brain readily engages with autonomous processes in controlling our bodies to coordinate complex patterns of muscle contractions, make postural adjustments, adapt to external perturbations, among many others. This acceptance of biological autonomy may provide avenues to promote more forgiving human-machine partnerships. In this perspectives paper, we argue that striving for machine embodiment is a pathway to achieving effective and forgiving human-machine relationships. We discuss the mechanisms that help us identify ourselves and our bodies as separate from our environments and we describe their roles in achieving embodied cooperation. Using a representative selection of examples in neurally interfaced prosthetic limbs and intelligent mechatronics, we describe techniques to engage these same mechanisms when designing autonomous systems and their potential bidirectional interfaces.

Fuzziness of muscle synergies in patients with multiple sclerosis indicates increased robustness of motor control during walking

Deficits during gait poses a significant threat to the quality of life in patients with Multiple Sclerosis (MS). Using the muscle synergy concept, we investigated the modular organization of the neuromuscular control during walking in MS patients compared to healthy participants (HP). We hypothesized a widening and increased fuzziness of motor primitives (e.g. increased overlap intervals) in MS patients compared to HP allowing the motor system to increase robustness during walking. We analysed temporal gait parameters, local dynamic stability and muscle synergies from myoelectric signals of 13 ipsilateral leg muscles using non-negative matrix factorization. Compared to HP, MS patients showed a significant decrease in the local dynamic stability of walking during both, preferred and fixed (0.7 m/s) speed. MS patients demonstrated changes in time-dependent activation patterns (motor primitives) and alterations of the relative muscle contribution to the specific synergies (motor modules). We specifically found a widening in three out of four motor primitives during preferred speed and in two out of four during fixed speed in MS patients compared to HP. The widening increased the fuzziness of motor control in MS patients, which allows the motor system to increase its robustness when coping with pathology-related motor deficits during walking.

On Primitives in Motor Control

The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.

Muscular Activity Modulation During Post-operative Walking With Hybrid Assistive Limb (HAL) in a Patient With Thoracic Myelopathy Due to Ossification of Posterior Longitudinal Ligament: A Case Report

Disorders of the central nervous system sometimes cause severe sensory motor paralysis accompanied by gait impairment. Recently, there are several reports on the effectiveness of robot-assisted gait training for patients experiencing these issues. The purpose of this case report was to assess the neuromechanical effect of a wearable robot suit HAL (Hybrid Assistive Limb) during post-operative gait training in a patient with gait impairment due to compressive myelopathy caused by ossification of the posterior longitudinal ligament (OPLL). For this purpose, we compared lower limb muscular activities while the patient was walking with and without the robot through a course of treatment sessions by (i) gait phase-dependent muscle usage analysis, (ii) muscle synergy analysis, and (iii) muscle network analysis. The results show (i) enhanced activity of the extensor muscles for weight-bearing in the initial sessions by using HAL and reduced knee extensor and increased hip extensor activations for achieving larger steps and faster gait in the later sessions; (ii) involvement of a greater number of synergies during walking with HAL than without HAL; and (iii) modulated muscle network property during walking with HAL remaining until the next HAL session. The patient's gait was improved after completing HAL sessions, acquiring close to normal joint profile with greater range of joint movement, faster walking speed, and larger step length. We discuss that the muscular activity modulation during walking with HAL suggests altered control of the muscles by the central nervous system during post-operative walking. Activity-dependent sensorimotor augmentation by HAL is discussed in the context of recovery of gait control by the central nervous system. The relationship between the altered control and the achieved gait recovery requires further investigation.

Curated Model Development Using NEUROiD: A Web-Based NEUROmotor Integration and Design Platform

Decades of research on neuromotor circuits and systems has provided valuable information on neuronal control of movement. Computational models of several elements of the neuromotor system have been developed at various scales, from sub-cellular to system. While several small models abound, their structured integration is the key to building larger and more biologically realistic models which can predict the behavior of the system in different scenarios. This effort calls for integration of elements across neuroscience and musculoskeletal biomechanics. There is also a need for development of methods and tools for structured integration that yield larger in silico models demonstrating a set of desired system responses. We take a small step in this direction with the NEUROmotor integration and Design (NEUROiD) platform. NEUROiD helps integrate results from motor systems anatomy, physiology, and biomechanics into an integrated neuromotor system model. Simulation and visualization of the model across multiple scales is supported. Standard electrophysiological operations such as slicing, current injection, recording of membrane potential, and local field potential are part of NEUROiD. The platform allows traceability of model parameters to primary literature. We illustrate the power and utility of NEUROiD by building a simple ankle model and its controlling neural circuitry by curating a set of published components. NEUROiD allows researchers to utilize remote high-performance computers for simulation, while controlling the model using a web browser.

Motor primitives are determined in early development and are then robustly conserved into adulthood

Motor patterns in legged vertebrates show modularity in both young and adult animals, comprising motor synergies or primitives. Are such spinal modules observed in young mammals conserved into adulthood or altered? Conceivably, early circuit modules alter radically through experience and descending pathways' activity. We analyze lumbar motor patterns of intact adult rats and the same rats after spinal transection and compare these with adult rats spinal transected 5 days postnatally, before most motor experience, using only rats that never developed hind limb weight bearing. We use independent component analysis (ICA) to extract synergies from electromyography (EMG). ICA information-based methods identify both weakly active and strongly active synergies. We compare all spatial synergies and their activation/drive strengths as proxies of spinal modules and their underlying circuits. Remarkably, we find that spatial primitives/synergies of adult injured and neonatal injured rats differed insignificantly, despite different developmental histories. However, intact rats possess some synergies that differ significantly, although modestly, in spatial structure. Rats injured as adults were more similar in modularity to rats that had neonatal spinal transection than to themselves before injury. We surmise that spinal circuit modules for spatial synergy patterns may be determined early, before postnatal day 5 (P5), and remain largely unaltered by subsequent development or weight-bearing experience. An alternative explanation but equally important is that, after complete spinal transection, both neonatal and mature adult spinal cords rapidly converge to common synergy sets. This fundamental or convergent synergy circuitry, fully determined by P5, is revealed after spinal cord transection.

Spinal control of muscle synergies for adult mammalian locomotion

KEY POINTS

The control of locomotion is thought to be generated by activating groups of muscles that perform similar actions, which are termed muscle synergies. Here, we investigated if muscle synergies are controlled at the level of the spinal cord. We did this by comparing muscle activity in the legs of cats during stepping on a treadmill before and after a complete spinal transection that abolishes commands from the brain. We show that muscle synergies were maintained following spinal transection, validating the concept that muscle synergies for locomotion are primarily controlled by circuits of neurons within the spinal cord.

ABSTRACT

Locomotion is thought to involve the sequential activation of functional modules or muscle synergies. Here, we tested the hypothesis that muscle synergies for locomotion are organized within the spinal cord. We recorded bursts of muscle activity in the same cats (n = 7) before and after spinal transection during tied-belt locomotion at three speeds and split-belt locomotion at three left-right speed differences. We identified seven muscles synergies before (intact state) and after (spinal state) spinal transection. The muscles comprising the different synergies were the same in the intact and spinal states as well as at different speeds or left-right speed differences. However, there were some significant shifts in the onsets and offsets of certain synergies as a function of state, speed and left-right speed differences. The most notable difference between the intact and spinal states was a change in the timing between the knee flexor and hip flexor muscle synergies. In the intact state, the knee flexor synergy preceded the hip flexor synergy, whereas in the spinal state both synergies occurred concurrently. Afferent inputs also appear important for the expression of some muscle synergies, specifically those involving biphasic patterns of muscle activity. We propose that muscle synergies for locomotion are primarily organized within the spinal cord, although their full expression and proper timing requires inputs from supraspinal structures and/or limb afferents.

Modular Control of Human Movement During Running: An Open Access Data Set

The human body is an outstandingly complex machine including around 1000 muscles and joints acting synergistically. Yet, the coordination of the enormous amount of degrees of freedom needed for movement is mastered by our one brain and spinal cord. The idea that some synergistic neural components of movement exist was already suggested at the beginning of the 20th century. Since then, it has been widely accepted that the central nervous system might simplify the production of movement by avoiding the control of each muscle individually. Instead, it might be controlling muscles in common patterns that have been called muscle synergies. Only with the advent of modern computational methods and hardware it has been possible to numerically extract synergies from electromyography (EMG) signals. However, typical experimental setups do not include a big number of individuals, with common sample sizes of 5 to 20 participants. With this study, we make publicly available a set of EMG activities recorded during treadmill running from the right lower limb of 135 healthy and young adults (78 males and 57 females). Moreover, we include in this open access data set the code used to extract synergies from EMG data using non-negative matrix factorization (NMF) and the relative outcomes. Muscle synergies, containing the time-invariant muscle weightings (motor modules) and the time-dependent activation coefficients (motor primitives), were extracted from 13 ipsilateral EMG activities using NMF. Four synergies were enough to describe as many gait cycle phases during running: weight acceptance, propulsion, early swing, and late swing. We foresee many possible applications of our data that we can summarize in three key points. First, it can be a prime source for broadening the representation of human motor control due to the big sample size. Second, it could serve as a benchmark for scientists from multiple disciplines such as musculoskeletal modeling, robotics, clinical neuroscience, sport science, etc. Third, the data set could be used both to train students or to support established scientists in the perfection of current muscle synergies extraction methods. All the data is available at Zenodo (doi: 10.5281/zenodo.1254380).

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

Dynamic structure of locomotor behavior in walking fruit flies

The function of the brain is unlikely to be understood without an accurate description of its output, yet the nature of movement elements and their organization remains an open problem. Here, movement elements are identified from dynamics of walking in flies, using unbiased criteria. On one time scale, dynamics of walking are consistent over hundreds of milliseconds, allowing elementary features to be defined. Over longer periods, walking is well described by a stochastic process composed of these elementary features, and a generative model of this process reproduces individual behavior sequences accurately over seconds or longer. Within elementary features, velocities diverge, suggesting that dynamical stability of movement elements is a weak behavioral constraint. Rather, long-term instability can be limited by the finite memory between these elementary features. This structure suggests how complex dynamics may arise in biological systems from elements whose combination need not be tuned for dynamic stability.

Modular organization of the multipartite central pattern generator for turtle rostral scratch: knee-related interneurons during deletions

Central pattern generators (CPGs) are neuronal networks in the spinal cord that generate rhythmic patterns of motor activity in the absence of movement-related sensory feedback. For many vertebrate rhythmic behaviors, CPGs generate normal patterns of motor neuron activities as well as variations of the normal patterns, termed deletions, in which bursts in one or more motor nerves are absent from one or more cycles of the rhythm. Prior work with hip-extensor deletions during turtle rostral scratch supports hypotheses of hip-extensor interneurons in a hip-extensor module and of hip-flexor interneurons in a hip-flexor module. We present here single-unit interneuronal recording data that support hypotheses of knee-extensor interneurons in a knee-extensor module and of knee-flexor interneurons in a knee-flexor module. Members of knee-related modules are not members of hip-related modules and vice versa. These results in turtle provide experimental support at the single-unit interneuronal level for the organizational concept that the rostral-scratch CPG for the turtle hindlimb is multipartite, that is, composed of more than two modules. This work, when combined with experimental and computational work in other vertebrates, does not support the classical view that the vertebrate limb CPG is bipartite with only two modules, one controlling all the flexors of the limb and the other controlling all the extensors of the limb. Instead, these results support the general principle that spinal CPGs are multipartite.

Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures

We used a musculoskeletal model to investigate the possible biomechanical and neural bases of using consistent muscle synergy patterns to produce functional motor outputs across different biomechanical conditions, which we define as generalizability. Experimental studies in cats demonstrate that the same muscle synergies are used during reactive postural responses at widely varying configurations, producing similarly-oriented endpoint force vectors with respect to the limb axis. However, whether generalizability across postures arises due to similar biomechanical properties or to neural selection of a particular muscle activation pattern has not been explicitly tested. Here, we used a detailed cat hindlimb model to explore the set of feasible muscle activation patterns that produce experimental synergy force vectors at a target posture, and tested their generalizability by applying them to different test postures. We used three methods to select candidate muscle activation patterns: (1) randomly-selected feasible muscle activation patterns, (2) optimal muscle activation patterns minimizing muscle effort at a given posture, and (3) generalizable muscle activation patterns that explicitly minimized deviations from experimentally-identified synergy force vectors across all postures. Generalizability was measured by the deviation between the simulated force direction of the candidate muscle activation pattern and the experimental synergy force vectors at the test postures. Force angle deviations were the greatest for the randomly selected feasible muscle activation patterns (e.g., >100°), intermediate for effort-wise optimal muscle activation patterns (e.g., ~20°), and smallest for generalizable muscle activation patterns (e.g., <5°). Generalizable muscle activation patterns were suboptimal in terms of effort, often exceeding 50% of the maximum possible effort (cf. ~5% in minimum-effort muscle activation patterns). The feasible muscle activation ranges of individual muscles associated with producing a specific synergy force vector was reduced by ~45% when generalizability requirements were imposed. Muscles recruited in the generalizable muscle activation patterns had less sensitive torque-producing characteristics to changes in postures. We conclude that generalization of function across postures does not arise from limb biomechanics or a single optimality criterion. Muscle synergies may reflect acquired motor solutions globally tuned for generalizability across biomechanical contexts, facilitating rapid motor adaptation.

Gait post-stroke: Pathophysiology and rehabilitation strategies

We reviewed neural control and biomechanical description of gait in both non-disabled and post-stroke subjects. In addition, we reviewed most of the gait rehabilitation strategies currently in use or in development and observed their principles in relation to recent pathophysiology of post-stroke gait. In both non-disabled and post-stroke subjects, motor control is organized on a task-oriented basis using a common set of a few muscle modules to simultaneously achieve body support, balance control, and forward progression during gait. Hemiparesis following stroke is due to disruption of descending neural pathways, usually with no direct lesion of the brainstem and cerebellar structures involved in motor automatic processes. Post-stroke, improvements of motor activities including standing and locomotion are variable but are typically characterized by a common postural behaviour which involves the unaffected side more for body support and balance control, likely in response to initial muscle weakness of the affected side. Various rehabilitation strategies are regularly used or in development, targeting muscle activity, postural and gait tasks, using more or less high-technology equipment. Reduced walking speed often improves with time and with various rehabilitation strategies, but asymmetric postural behaviour during standing and walking is often reinforced, maintained, or only transitorily decreased. This asymmetric compensatory postural behaviour appears to be robust, driven by support and balance tasks maintaining the predominant use of the unaffected side over the initially impaired affected side. Based on these elements, stroke rehabilitation including affected muscle strengthening and often stretching would first need to correct the postural asymmetric pattern by exploiting postural automatic processes in various particular motor tasks secondarily beneficial to gait.

Genetically identified spinal interneurons integrating tactile afferents for motor control

Our movements are shaped by our perception of the world as communicated by our senses. Perception of sensory information has been largely attributed to cortical activity. However, a prior level of sensory processing occurs in the spinal cord. Indeed, sensory inputs directly project to many spinal circuits, some of which communicate with motor circuits within the spinal cord. Therefore, the processing of sensory information for the purpose of ensuring proper movements is distributed between spinal and supraspinal circuits. The mechanisms underlying the integration of sensory information for motor control at the level of the spinal cord have yet to be fully described. Recent research has led to the characterization of spinal neuron populations that share common molecular identities. Identification of molecular markers that define specific populations of spinal neurons is a prerequisite to the application of genetic techniques devised to both delineate the function of these spinal neurons and their connectivity. This strategy has been used in the study of spinal neurons that receive tactile inputs from sensory neurons innervating the skin. As a result, the circuits that include these spinal neurons have been revealed to play important roles in specific aspects of motor function. We describe these genetically identified spinal neurons that integrate tactile information and the contribution of these studies to our understanding of how tactile information shapes motor output. Furthermore, we describe future opportunities that these circuits present for shedding light on the neural mechanisms of tactile processing.

Advancing brain-machine interfaces: moving beyond linear state space models

Advances in recent years have dramatically improved output control by Brain-Machine Interfaces (BMIs). Such devices nevertheless remain robotic and limited in their movements compared to normal human motor performance. Most current BMIs rely on transforming recorded neural activity to a linear state space composed of a set number of fixed degrees of freedom. Here we consider a variety of ways in which BMI design might be advanced further by applying non-linear dynamics observed in normal motor behavior. We consider (i) the dynamic range and precision of natural movements, (ii) differences between cortical activity and actual body movement, (iii) kinematic and muscular synergies, and (iv) the implications of large neuronal populations. We advance the hypothesis that a given population of recorded neurons may transmit more useful information than can be captured by a single, linear model across all movement phases and contexts. We argue that incorporating these various non-linear characteristics will be an important next step in advancing BMIs to more closely match natural motor performance.

Trunk robot rehabilitation training with active stepping reorganizes and enriches trunk motor cortex representations in spinal transected rats

Trunk motor control is crucial for postural stability and propulsion after low thoracic spinal cord injury (SCI) in animals and humans. Robotic rehabilitation aimed at trunk shows promise in SCI animal models and patients. However, little is known about the effect of SCI and robot rehabilitation of trunk on cortical motor representations. We previously showed reorganization of trunk motor cortex after adult SCI. Non-stepping training also exacerbated some SCI-driven plastic changes. Here we examine effects of robot rehabilitation that promotes recovery of hindlimb weight support functions on trunk motor cortex representations. Adult rats spinal transected as neonates (NTX rats) at the T9/10 level significantly improve function with our robot rehabilitation paradigm, whereas treadmill-only trained do not. We used intracortical microstimulation to map motor cortex in two NTX groups: (1) treadmill trained (control group); and (2) robot-assisted treadmill trained (improved function group). We found significant robot rehabilitation-driven changes in motor cortex: (1) caudal trunk motor areas expanded; (2) trunk coactivation at cortex sites increased; (3) richness of trunk cortex motor representations, as examined by cumulative entropy and mutual information for different trunk representations, increased; (4) trunk motor representations in the cortex moved toward more normal topography; and (5) trunk and forelimb motor representations that SCI-driven plasticity and compensations had caused to overlap were segregated. We conclude that effective robot rehabilitation training induces significant reorganization of trunk motor cortex and partially reverses some plastic changes that may be adaptive in non-stepping paraplegia after SCI.

Neuromechanical principles underlying movement modularity and their implications for rehabilitation

Neuromechanical principles define the properties and problems that shape neural solutions for movement. Although the theoretical and experimental evidence is debated, we present arguments for consistent structures in motor patterns, i.e., motor modules, that are neuromechanical solutions for movement particular to an individual and shaped by evolutionary, developmental, and learning processes. As a consequence, motor modules may be useful in assessing sensorimotor deficits specific to an individual and define targets for the rational development of novel rehabilitation therapies that enhance neural plasticity and sculpt motor recovery. We propose that motor module organization is disrupted and may be improved by therapy in spinal cord injury, stroke, and Parkinson's disease. Recent studies provide insights into the yet-unknown underlying neural mechanisms of motor modules, motor impairment, and motor learning and may lead to better understanding of the causal nature of modularity and its underlying neural substrates.

Spinal primitives and intra-spinal micro-stimulation (ISMS) based prostheses: a neurobiological perspective on the "known unknowns" in ISMS and future prospects

The current literature on Intra-Spinal Micro-Stimulation (ISMS) for motor prostheses is reviewed in light of neurobiological data on spinal organization, and a neurobiological perspective on output motor modularity, ISMS maps, stimulation combination effects, and stability. By comparing published data in these areas, the review identifies several gaps in current knowledge that are crucial to the development of effective intraspinal neuroprostheses. Gaps can be categorized into a lack of systematic and reproducible details of: (a) Topography and threshold for ISMS across the segmental motor system, the topography of autonomic recruitment by ISMS, and the coupling relations between these two types of outputs in practice. (b) Compositional rules for ISMS motor responses tested across the full range of the target spinal topographies. (c) Rules for ISMS effects' dependence on spinal cord state and neural dynamics during naturally elicited or ISMS triggered behaviors. (d) Plasticity of the compositional rules for ISMS motor responses, and understanding plasticity of ISMS topography in different spinal cord lesion states, disease states, and following rehabilitation. All these knowledge gaps to a greater or lesser extent require novel electrode technology in order to allow high density chronic recording and stimulation. The current lack of this technology may explain why these prominent gaps in the ISMS literature currently exist. It is also argued that given the "known unknowns" in the current ISMS literature, it may be prudent to adopt and develop control schemes that can manage the current results with simple superposition and winner-take-all interactions, but can also incorporate the possible plastic and stochastic dynamic interactions that may emerge in fuller analyses over longer terms, and which have already been noted in some simpler model systems.

Somatosensory feedback refines the perception of hand shape with respect to external constraints

Motor commands issued by the CNS are based upon memories of past experiences with similar objects, the current state of the hand and arm postures, and sensory input. Thus widespread somatosensory information is available to form precise representations of hand shape on which to base motor commands to match a desired posture or movement. The aim of this study was to examine the extent to which somatosensory information reflecting external influences on independent finger movement is incorporated into the perception of hand shape driving the motor command. To address this issue, a matching task was performed while pairs of fingers in the grasping hand were constrained to move in tandem when grasping familiar objects. The hypothesis was that motor commands would be driven by comparison of the online sensory information from the matching hand to a desired somatosensory state determined by the current somatosensory input from the grasping hand. The results demonstrated that multi-muscle patterns of activation and hand postures were altered with respect to the external constraint on independent finger movement. A secondary aim of this study was to examine the influence of sensory information on the structure of the multi-muscle patterns. The hypothesis was that the same synergies (patterns of activation across muscles) would be used to complete the task but would be rescaled with respect to condition. The results demonstrated that rescaling the patterns of multi-muscle activity from the unconstrained condition could not equivalently represent those from the constrained conditions. Thus it appears that external restriction of independent finger movement was signaled by somatosensory feedback and incorporated into the desired state driving the motor command resulting in selective activation of groups of muscles.

Human spinal locomotor control is based on flexibly organized burst generators

Constant drive provided to the human lumbar spinal cord by epidural electrical stimulation can cause local neural circuits to generate rhythmic motor outputs to lower limb muscles in people paralysed by spinal cord injury. Epidural spinal cord stimulation thus allows the study of spinal rhythm and pattern generating circuits without their configuration by volitional motor tasks or task-specific peripheral feedback. To reveal spinal locomotor control principles, we studied the repertoire of rhythmic patterns that can be generated by the functionally isolated human lumbar spinal cord, detected as electromyographic activity from the legs, and investigated basic temporal components shared across these patterns. Ten subjects with chronic, motor-complete spinal cord injury were studied. Surface electromyographic responses to lumbar spinal cord stimulation were collected from quadriceps, hamstrings, tibialis anterior, and triceps surae in the supine position. From these data, 10-s segments of rhythmic activity present in the four muscle groups of one limb were extracted. Such samples were found in seven subjects. Physiologically adequate cycle durations and relative extension- and flexion-phase durations similar to those needed for locomotion were generated. The multi-muscle activation patterns exhibited a variety of coactivation, mixed-synergy and locomotor-like configurations. Statistical decomposition of the electromyographic data across subjects, muscles and samples of rhythmic patterns identified three common temporal components, i.e. basic or shared activation patterns. Two of these basic patterns controlled muscles to contract either synchronously or alternatingly during extension- and flexion-like phases. The third basic pattern contributed to the observed muscle activities independently from these extensor- and flexor-related basic patterns. Each bifunctional muscle group was able to express both extensor- and flexor-patterns, with variable ratios across the samples of rhythmic patterns. The basic activation patterns can be interpreted as central drives implemented by spinal burst generators that impose specific spatiotemporally organized activation on the lumbosacral motor neuron pools. Our data thus imply that the human lumbar spinal cord circuits can form burst-generating elements that flexibly combine to obtain a wide range of locomotor outputs from a constant, repetitive input. It may be possible to use this flexibility to incorporate specific adaptations to gait and stance to improve locomotor control, even after severe central nervous system damage.

Are movement disorders and sensorimotor injuries pathologic synergies? When normal multi-joint movement synergies become pathologic

The intact nervous system has an exquisite ability to modulate the activity of multiple muscles acting at one or more joints to produce an enormous range of actions. Seemingly simple tasks, such as reaching for an object or walking, in fact rely on very complex spatial and temporal patterns of muscle activations. Neurological disorders such as stroke and focal dystonia affect the ability to coordinate multi-joint movements. This article reviews the state of the art of research of muscle synergies in the intact and damaged nervous system, their implications for recovery and rehabilitation, and proposes avenues for research aimed at restoring the nervous system’s ability to control movement.

Transition of pattern generation: the phenomenon of post-scratching locomotion

A fundamental problem in neurophysiology is the understanding of neuronal mechanisms by which the central nervous system produces a sequence of voluntary or involuntary motor acts from a diverse repertory of movements. These kinds of transitions between motor acts are extremely complex; however, they could be analyzed in a more simple form in decerebrate animals in the context of spinal central pattern generation. Here, we present for the first time a physiological phenomenon of post-scratching locomotion in which decerebrate cats exhibit a compulsory locomotor activity after an episode of scratching. We found flexor, extensor and intermediate single interneurons rhythmically firing in the same phase during both scratching and the subsequent post-scratching locomotion. Because no changes in phase of these neurons from scratching to post-scratching locomotion were found, we suggest that in the lumbar spinal cord there are neurons associated with both motor tasks. Moreover, because of its high reproducibility we suggest that the study of post-scratching fictive locomotion, together with the unitary recording of neurons, could become a useful tool to study neuronal mechanisms underlying transitions from one rhythmic motor task to another, and to study in more detail the central pattern generator circuitry in the spinal cord.

Principal components of hand kinematics and neurophysiological signals in motor cortex during reach to grasp movements

A few kinematic synergies identified by principal component analysis (PCA) account for most of the variance in the coordinated joint rotations of the fingers and wrist used for a wide variety of hand movements. To examine the possibility that motor cortex might control the hand through such synergies, we collected simultaneous kinematic and neurophysiological data from monkeys performing a reach-to-grasp task. We used PCA, jPCA and isomap to extract kinematic synergies from 18 joint angles in the fingers and wrist and analyzed the relationships of both single-unit and multiunit spike recordings, as well as local field potentials (LFPs), to these synergies. For most spike recordings, the maximal absolute cross-correlations of firing rates were somewhat stronger with an individual joint angle than with any principal component (PC), any jPC or any isomap dimension. In decoding analyses, where spikes and LFP power in the 100- to 170-Hz band each provided better decoding than other LFP-based signals, the first PC was decoded as well as the best decoded joint angle. But the remaining PCs and jPCs were predicted with lower accuracy than individual joint angles. Although PCs, jPCs or isomap dimensions might provide a more parsimonious description of kinematics, our findings indicate that the kinematic synergies identified with these techniques are not represented in motor cortex more strongly than the original joint angles. We suggest that the motor cortex might act to sculpt the synergies generated by subcortical centers, superimposing an ability to individuate finger movements and adapt the hand to grasp a wide variety of objects.

Plasticity and alterations of trunk motor cortex following spinal cord injury and non-stepping robot and treadmill training

Spinal cord injury (SCI) induces significant reorganization in the sensorimotor cortex. Trunk motor control is crucial for postural stability and propulsion after low thoracic SCI and several rehabilitative strategies are aimed at trunk stability and control. However little is known about the effect of SCI and rehabilitation training on trunk motor representations and their plasticity in the cortex. Here, we used intracortical microstimulation to examine the motor cortex representations of the trunk in relation to other representations in three groups of chronic adult complete low thoracic SCI rats: chronic untrained, treadmill trained (but 'non-stepping') and robot assisted treadmill trained (but 'non-stepping') and compared with a group of normal rats. Our results demonstrate extensive and significant reorganization of the trunk motor cortex after chronic adult SCI which includes (1) expansion and rostral displacement of trunk motor representations in the cortex, with the greatest significant increase observed for rostral (to injury) trunk, and slight but significant increase of motor representation for caudal (to injury) trunk at low thoracic levels in all spinalized rats; (2) significant changes in coactivation and the synergy representation (or map overlap) between different trunk muscles and between trunk and forelimb. No significant differences were observed between the groups of transected rats for the majority of the comparisons. However, (3) the treadmill and robot-treadmill trained groups of rats showed a further small but significant rostral migration of the trunk representations, beyond the shift caused by transection alone. We conclude that SCI induces a significant reorganization of the trunk motor cortex, which is not qualitatively altered by non-stepping treadmill training or non-stepping robot assisted treadmill training, but is shifted further from normal topography by the training. This shift may potentially make subsequent rehabilitation with stepping longer or less successful.

Quantification of dexterity as the dynamical regulation of instabilities: comparisons across gender, age, and disease

Dexterous manipulation depends on using the fingertips to stabilize unstable objects. The Strength-Dexterity paradigm consists of asking subjects to compress a slender and compliant spring prone to buckling. The maximal level of compression [requiring low fingertip forces <300 grams force (gf)] quantifies the neural control capability to dynamically regulate fingertip force vectors and motions for a dynamic manipulation task. We found that finger dexterity is significantly affected by age (p = 0.017) and gender (p = 0.021) in 147 healthy individuals (66F, 81M, 20-88 years). We then measured finger dexterity in 42 hands of patients following treatment for osteoarthritis of the base of the thumb (CMC OA, 33F, 65.8 ± 9.7 years), and 31 hands from patients being treated for Parkinson's disease (PD, 6F, 10M, 67.68 ± 8.5 years). Importantly, we found no differences in finger compression force among patients or controls. However, we did find stronger age-related declines in performance in the patients with PD (slope -2.7 gf/year, p = 0.002) than in those with CMC OA (slope -1.4 gf/year, p = 0.015), than in controls (slope -0.86 gf/year). In addition, the temporal variability of forces during spring compression shows clearly different dynamics in the clinical populations compared to the controls (p < 0.001). Lastly, we compared dexterity across extremities. We found stronger age (p = 0.005) and gender (p = 0.002) effects of leg compression force in 188 healthy subjects who compressed a larger spring with the foot of an isolated leg (73F, 115M, 14-92 years). In 81 subjects who performed the tests with all four limbs separately, we found finger and leg compression force to be significantly correlated (females ρ = 0.529, p = 0.004; males ρ = 0.403, p = 0.003; 28F, 53M, 20-85 years), but surprisingly found no differences between dominant and non-dominant limbs. These results have important clinical implications, and suggest the existence - and compel the investigation - of systemic versus limb-specific mechanisms for dexterity.

Dimensionality of joint torques and muscle patterns for reaching

Muscle activities underlying many motor behaviors can be generated by a small number of basic activation patterns with specific features shared across movement conditions. Such low-dimensionality suggests that the central nervous system (CNS) relies on a modular organization to simplify control. However, the relationship between the dimensionality of muscle patterns and that of joint torques is not fixed, because of redundancy and non-linearity in mapping the former into the latter, and needs to be investigated. We compared the torques acting at four arm joints during fast reaching movements in different directions in the frontal and sagittal planes and the underlying muscle patterns. The dimensionality of the non-gravitational components of torques and muscle patterns in the spatial, temporal, and spatiotemporal domains was estimated by multidimensional decomposition techniques. The spatial organization of torques was captured by two or three generators, indicating that not all the available coordination patterns are employed by the CNS. A single temporal generator with a biphasic profile was identified, generalizing previous observations on a single plane. The number of spatiotemporal generators was equal to the product of the spatial and temporal dimensionalities and their organization was essentially synchronous. Muscle pattern dimensionalities were higher than torques dimensionalities but also higher than the minimum imposed by the inherent non-negativity of muscle activations. The spatiotemporal dimensionality of the muscle patterns was lower than the product of their spatial and temporal dimensionality, indicating the existence of specific asynchronous coordination patterns. Thus, the larger dimensionalities of the muscle patterns may be required for CNS to overcome the non-linearities of the musculoskeletal system and to flexibly generate endpoint trajectories with simple kinematic features using a limited number of building blocks.

Muscle activation patterns are bilaterally linked during split-belt treadmill walking in humans

There is growing evidence that human locomotion is controlled by flexibly combining a set of basic muscle activity patterns. To explore how these patterns are modified to cope with environmental constraints, 10 healthy young adults 1st walked on a split-belt treadmill at symmetric speeds of 4 and 6 km/h for 2 min. An asymmetric condition was then performed for 10 min in which treadmill speeds for the dominant (fast) and nondominant (slow) sides were 6 and 4 km/h, respectively. This was immediately followed by a symmetric speed condition of 4 km/h for 5 min. Gait kinematics and ground reaction forces were recorded. Electromyography (EMG) was collected from 12 lower limb muscles on each side of the body. Nonnegative matrix factorization was applied to the EMG signals bilaterally and unilaterally to obtain basic activation patterns. A cross-correlation analysis was then used to quantify temporal changes in the activation patterns. During the early (1st 10 strides) and late (final 10 strides) phases of the asymmetric condition, the patterns related to ankle plantar flexor (push-off) of the fast limb and quadriceps muscle (contralateral heel contact) of the slow limb occurred earlier in the gait cycle compared with the symmetric conditions. Moreover, a bilateral temporal alignment of basic patterns between limbs was still maintained in the split-belt condition since a similar shift was observed in the unilateral patterns. The results suggest that the temporal structure of these locomotor patterns is shaped by sensory feedback and that the patterns are bilaterally linked.

Neuromodulation of the lumbar spinal locomotor circuit

The lumbar spinal cord contains the necessary circuitry to independently drive locomotor behaviors. This function is retained following spinal cord injury (SCI) and is amenable to rehabilitation. Although the effectiveness of task-specific training and pharmacologic modulation has been repeatedly demonstrated in animal studies, results from human studies are less striking. Recently, lumbar epidural stimulation (EDS) along with locomotor training was shown to restore weight-bearing function and lower-extremity voluntary control in a chronic, motor-complete human SCI subject. Related animal studies incorporating EDS as part of the therapeutic regiment are also encouraging. EDS is emerging as a promising neuromodulatory tool for SCI.

Plasticity and modular control of locomotor patterns in neurological disorders with motor deficits

Human locomotor movements exhibit considerable variability and are highly complex in terms of both neural activation and biomechanical output. The building blocks with which the central nervous system constructs these motor patterns can be preserved in patients with various sensory-motor disorders. In particular, several studies highlighted a modular burst-like organization of the muscle activity. Here we review and discuss this issue with a particular emphasis on the various examples of adaptation of locomotor patterns in patients (with large fiber neuropathy, amputees, stroke and spinal cord injury). The results highlight plasticity and different solutions to reorganize muscle patterns in both peripheral and central nervous system lesions. The findings are discussed in a general context of compensatory gait mechanisms, spatiotemporal architecture and modularity of the locomotor program.

Joint-specific changes in locomotor complexity in the absence of muscle atrophy following incomplete spinal cord injury

Background

Following incomplete spinal cord injury (iSCI), descending drive is impaired, possibly leading to a decrease in the complexity of gait. To test the hypothesis that iSCI impairs gait coordination and decreases locomotor complexity, we collected 3D joint angle kinematics and muscle parameters of rats with a sham or an incomplete spinal cord injury.

Methods

12 adult, female, Long-Evans rats, 6 sham and 6 mild-moderate T8 iSCI, were tested 4 weeks following injury. The Basso Beattie Bresnahan locomotor score was used to verify injury severity. Animals had reflective markers placed on the bony prominences of their limb joints and were filmed in 3D while walking on a treadmill. Joint angles and segment motion were analyzed quantitatively, and complexity of joint angle trajectory and overall gait were calculated using permutation entropy and principal component analysis, respectively. Following treadmill testing, the animals were euthanized and hindlimb muscles removed. Excised muscles were tested for mass, density, fiber length, pennation angle, and relaxed sarcomere length.

Results

Muscle parameters were similar between groups with no evidence of muscle atrophy. The animals showed overextension of the ankle, which was compensated for by a decreased range of motion at the knee. Left-right coordination was altered, leading to left and right knee movements that are entirely out of phase, with one joint moving while the other is stationary. Movement patterns remained symmetric. Permutation entropy measures indicated changes in complexity on a joint specific basis, with the largest changes at the ankle. No significant difference was seen using principal component analysis. Rats were able to achieve stable weight bearing locomotion at reasonable speeds on the treadmill despite these deficiencies.

Conclusions

Decrease in supraspinal control following iSCI causes a loss of complexity of ankle kinematics. This loss can be entirely due to loss of supraspinal control in the absence of muscle atrophy and may be quantified using permutation entropy. Joint-specific differences in kinematic complexity may be attributed to different sources of motor control. This work indicates the importance of the ankle for rehabilitation interventions following spinal cord injury.

Motor cortical regulation of sparse synergies provides a framework for the flexible control of precision walking

We have previously described a modular organization of the locomotor step cycle in the cat in which a number of sparse synergies are activated sequentially during the swing phase of the step cycle (Krouchev et al., 2006). Here, we address how these synergies are modified during voluntary gait modifications. Data were analysed from 27 bursts of muscle activity (recorded from 18 muscles) recorded in the forelimb of the cat during locomotion. These were grouped into 10 clusters, or synergies, during unobstructed locomotion. Each synergy was comprised of only a small number of muscles bursts (sparse synergies), some of which included both proximal and distal muscles. Eight (8/10) of these synergies were active during the swing phase of locomotion. Synergies observed during the gait modifications were very similar to those observed during unobstructed locomotion. Constraining these synergies to be identical in both the lead (first forelimb to pass over the obstacle) and the trail (second limb) conditions allowed us to compare the changes in phase and magnitude of the synergies required to modify gait. In the lead condition, changes were observed particularly in those synergies responsible for transport of the limb and preparation for landing. During the trail condition, changes were particularly evident in those synergies responsible for lifting the limb from the ground at the onset of the swing phase. These changes in phase and magnitude were adapted to the size and shape of the obstacle over which the cat stepped. These results demonstrate that by modifying the phase and magnitude of a finite number of muscle synergies, each comprised of a small number of simultaneously active muscles, descending control signals could produce very specific modifications in limb trajectory during locomotion. We discuss the possibility that these changes in phase and magnitude could be produced by changes in the activity of neurones in the motor cortex.

Molecular, genetic, cellular, and network functions in the spinal cord and brainstem

Studies of the model systems of spinal cord and brainstem reveal molecular, genetic, and cellular mechanisms that are critical for network and behavioral functions in the nervous system. Recent experiments establish the importance of neurogenetics in revealing cellular and network properties. Breakthroughs that utilize direct visualization of neuronal activity and network structure provide new insights. Major discoveries of plasticity in the spinal cord and brainstem contribute to basic neuroscience and, in addition, have promising therapeutic implications.