Coordination and localization in spinal motor systems

Ethnokinesiology: towards a neuromechanical understanding of cultural differences in movement

Each individual's movements are sculpted by constant interactions between sensorimotor and sociocultural factors. A theoretical framework grounded in motor control mechanisms articulating how sociocultural and biological signals converge to shape movement is currently missing. Here, we propose a framework for the emerging field of ethnokinesiology aiming to provide a conceptual space and vocabulary to help bring together researchers at this intersection. We offer a first-level schema for generating and testing hypotheses about cultural differences in movement to bridge gaps between the rich observations of cross-cultural movement variations and neurophysiological and biomechanical accounts of movement. We explicitly dissociate two interacting feedback loops that determine culturally relevant movement: one governing sensorimotor tasks regulated by neural signals internal to the body, the other governing ecological tasks generated through actions in the environment producing ecological consequences. A key idea is the emergence of individual-specific and culturally influenced motor concepts in the nervous system, low-dimensional functional mappings between sensorimotor and ecological task spaces. Motor accents arise from perceived differences in motor concept topologies across cultural contexts. We apply the framework to three examples: speech, gait and grasp. Finally, we discuss how ethnokinesiological studies may inform personalized motor skill training and rehabilitation, and challenges moving forward.This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.

Synaptic architecture of leg and wing premotor control networks in Drosophila

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Developing new intermuscular coordination patterns through an electromyographic signal-guided training in the upper extremity

BACKGROUND

Muscle synergies, computationally identified intermuscular coordination patterns, have been utilized to characterize neuromuscular control and learning in humans. However, it is unclear whether it is possible to alter the existing muscle synergies or develop new ones in an intended way through a relatively short-term motor exercise in adulthood. This study aimed to test the feasibility of expanding the repertoire of intermuscular coordination patterns through an isometric, electromyographic (EMG) signal-guided exercise in the upper extremity (UE) of neurologically intact individuals.

METHODS

10 participants were trained for six weeks to induce independent control of activating a pair of elbow flexor muscles that tended to be naturally co-activated in force generation. An untrained isometric force generation task was performed to assess the effect of the training on the intermuscular coordination of the trained UE. We applied a non-negative matrix factorization on the EMG signals recorded from 12 major UE muscles during the assessment to identify the muscle synergies. In addition, the performance of training tasks and the characteristics of individual muscles' activity in both time and frequency domains were quantified as the training outcomes.

RESULTS

Typically, in two weeks of the training, participants could use newly developed muscle synergies when requested to perform new, untrained motor tasks by activating their UE muscles in the trained way. Meanwhile, their habitually expressed muscle synergies, the synergistic muscle activation groups that were used before the training, were conserved throughout the entire training period. The number of muscle synergies activated for the task performance remained the same. As the new muscle synergies were developed, the neuromotor control of the trained muscles reflected in the metrics, such as the ratio between the targeted muscles, number of matched targets, and task completion time, was improved.

CONCLUSION

These findings suggest that our protocol can increase the repertoire of readily available muscle synergies and improve motor control by developing the activation of new muscle coordination patterns in healthy adults within a relatively short period. Furthermore, the study shows the potential of the isometric EMG-guided protocol as a neurorehabilitation tool for aiming motor deficits induced by abnormal intermuscular coordination after neurological disorders.

TRIAL REGISTRATION

This study was registered at the Clinical Research Information Service (CRiS) of the Korea National Institute of Health (KCT0005803) on 1/22/2021.

Compromised neuromuscular function of walking in people with diabetes: a narrative review

AIM

This review summarizes recent studies that have investigated the neuromuscular dysfunction of walking in people with diabetes and its relationship to ulcer formation.

METHODS

A comprehensive electronic search in the database (Scopus, Web of Science, PsycINFO, ProQuest, and PubMed) was performed for articles pertaining to diabetes and gait biomechanics.

RESULTS

The Achilles tendon is thicker and stiffer in those with diabetes. People with diabetes demonstrate changes in walking kinematics and kinetics, including slower self-selected gait speed, shorter stride length, longer stance phase duration, and decreased ankle, knee, and metatarsophalangeal (MTP) joint range of motion. EMG is altered during walking and may reflect diabetes-induced changes in muscle synergies. Synergies are notable because they provide a more holistic pattern of muscle activations and can help develop better tools for characterizing disease progression.

CONCLUSION

Diabetes compromises neuromuscular coordination and function. The mechanisms contributing to ulcer formation are incompletely understood. Diabetes-related gait impairments may be a significant independent risk factor for the development of foot ulcers.

Muscle synergy analysis of eight inter-limb coordination modes during human hands-knees crawling movement

In order to reveal in-depth the neuromuscular control mechanism of human crawling, this study carries out muscle synergy extraction and analysis on human hands-knees crawling under eight specific inter-limb coordination modes, which are defined according to the swing sequence of limbs and includes two-limb swing crawling modes and six single-limb swing crawling modes. Ten healthy adults participate in crawling data collection, and surface electromyography (sEMG) signals are recorded from 30 muscles of limbs and trunk. Non-negative matrix factorization (NNMF) algorithm is adopted for muscle synergy extraction, and a three-step muscle synergy analysis scheme is implemented by using the hierarchical clustering method. Based on results of muscle synergy extraction, 4 to 7 synergies are extracted from each participant in each inter-limb coordination mode, which supports the muscle synergy hypothesis to some extent, namely, central nervous system (CNS) controls the inter-limb coordination modes during crawling movement by recruiting a certain amount of muscle synergies, rather than a single muscle. In addition, when different participants crawl in the same inter-limb coordination mode, they share more temporal features in recruiting muscle synergies. Further, by extracting and analyzing intra-mode shared synergies among participants and inter-mode shared synergies among the eight inter-limb coordination modes, the CNS is found to realize single-limb swing crawling modes by recruiting the four inter-mode shared synergy structures related to the swing function of each limb in different orders, and realize the two-limb swing crawling modes by recruiting synchronously two intra-mode shared synergy structures. The research results of the muscle synergy analysis on the eight specific inter-limb coordination modes, on the one hand, provide a basis for muscle synergy hypothesis from the perspective of crawling motion, on the other hand, also provide a possible explanation for the choice of the inter-limb coordination mode in human crawling.

Muscle coordination and recruitment during squat assistance using a robotic ankle-foot exoskeleton

Squatting is an intensive activity routinely performed in the workplace to lift and lower loads. The effort to perform a squat can decrease using an exoskeleton that considers individual worker's differences and assists them with a customized solution, namely, personalized assistance. Designing such an exoskeleton could be improved by understanding how the user's muscle activity changes when assistance is provided. This study investigated the change in the muscle recruitment and activation pattern when personalized assistance was provided. The personalized assistance was provided by an ankle-foot exoskeleton during squatting and we compared its effect with that of the no-device and unpowered exoskeleton conditions using previously collected data. We identified four main muscle recruitment strategies across ten participants. One of the strategies mainly used quadriceps muscles, and the activation level corresponding to the strategy was reduced under exoskeleton assistance compared to the no-device and unpowered conditions. These quadriceps dominant synergy and rectus femoris activations showed reasonable correlations (r = 0.65, 0.59) to the metabolic cost of squatting. These results indicate that the assistance helped reduce quadriceps activation, and thus, the metabolic cost of squatting. These outcomes suggest that the muscle recruitment and activation patterns could be used to design an exoskeleton and training methods.

The effect of limb position on a static knee extension task can be explained with a simple spinal cord circuit model

The influence of proprioceptive feedback on muscle activity during isometric tasks is the subject of conflicting studies. We performed an isometric knee extension task experiment based on two common clinical tests for mobility and flexibility. The task was carried out at four preset angles of the knee, and we recorded from five muscles for two different hip positions. We applied muscle synergy analysis using nonnegative matrix factorization on surface electromyograph recordings to identify patterns in the data that changed with internal knee angle, suggesting a link between proprioception and muscle activity. We hypothesized that such patterns arise from the way proprioceptive and cortical signals are integrated in neural circuits of the spinal cord. Using the MIIND neural simulation platform, we developed a computational model based on current understanding of spinal circuits with an adjustable afferent input. The model produces the same synergy trends as observed in the data, driven by changes in the afferent input. To match the activation patterns from each knee angle and position of the experiment, the model predicts the need for three distinct inputs: two to control a nonlinear bias toward the extensors and against the flexors, and a further input to control additional inhibition of rectus femoris. The results show that proprioception may be involved in modulating muscle synergies encoded in cortical or spinal neural circuits.NEW & NOTEWORTHY The role of sensory feedback in motor control when limbs are held in a fixed position is disputed. We performed a novel experiment involving fixed position tasks based on two common clinical tests. We identified patterns of muscle activity during the tasks that changed with different leg positions and then inferred how sensory feedback might influence the observations. We developed a computational model that required three distinct inputs to reproduce the activity patterns observed experimentally. The model provides a neural explanation for how the activity patterns can be changed by sensory feedback.

The contemporary model of vertebral column joint dysfunction and impact of high-velocity, low-amplitude controlled vertebral thrusts on neuromuscular function

Purpose

There is growing evidence that vertebral column function and dysfunction play a vital role in neuromuscular control. This invited review summarises the evidence about how vertebral column dysfunction, known as a central segmental motor control (CSMC) problem, alters neuromuscular function and how spinal adjustments (high-velocity, low-amplitude or HVLA thrusts directed at a CSMC problem) and spinal manipulation (HVLA thrusts directed at segments of the vertebral column that may not have clinical indicators of a CSMC problem) alters neuromuscular function.

Methods

The current review elucidates the peripheral mechanisms by which CSMC problems, the spinal adjustment or spinal manipulation alter the afferent input from the paravertebral tissues. It summarises the contemporary model that provides a biologically plausible explanation for CSMC problems, the manipulable spinal lesion. This review also summarises the contemporary, biologically plausible understanding about how spinal adjustments enable more efficient production of muscular force. The evidence showing how spinal dysfunction, spinal manipulation and spinal adjustments alter central multimodal integration and motor control centres will be covered in a second invited review.

Results

Many studies have shown spinal adjustments increase voluntary force and prevent fatigue, which mainly occurs due to altered supraspinal excitability and multimodal integration. The literature suggests physical injury, pain, inflammation, and acute or chronic physiological or psychological stress can alter the vertebral column’s central neural motor control, leading to a CSMC problem. The many gaps in the literature have been identified, along with suggestions for future studies.

Conclusion

Spinal adjustments of CSMC problems impact motor control in a variety of ways. These include increasing muscle force and preventing fatigue. These changes in neuromuscular function most likely occur due to changes in supraspinal excitability. The current contemporary model of the CSMC problem, and our understanding of the mechanisms of spinal adjustments, provide a biologically plausible explanation for how the vertebral column’s central neural motor control can dysfunction, can lead to a self-perpetuating central segmental motor control problem, and how HVLA spinal adjustments can improve neuromuscular function.

A Novel Muscle Synergy Extraction Method Used for Motor Function Evaluation of Stroke Patients: A Pilot Study

In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS were the most similar to true synergies as compared with SMMA and NMF. MCR-ALS was used to analyze the muscle synergy characteristics of upper limb movements performed by healthy (n = 11) and stroke (n = 5) subjects. The repeatability and intra-subject consistency were used to evaluate the performance of MCR-ALS. As a result, MCR-ALS provided much higher repeatability and intra-subject consistency as compared with NMF, which were important for the reliability of the motor function evaluation. The stroke subjects had lower intra-subject consistency and seemingly had more synergies as compared with the healthy subjects. Thus, MCR-ALS is a promising muscle synergy analysis method for motor function evaluation of stroke patients.

Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients

Objective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing.Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores.Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement.Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.

Approaches to revealing the neural basis of muscle synergies: a review and a critique

The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies.

Neuromuscular compensation strategies adopted at the shoulder following bilateral subpectoral implant breast reconstruction

Immediate two-stage subpectoral implant breast reconstruction after mastectomy requires the surgical disinsertion of the sternocostal fiber region of the pectoralis major (PM). The disinsertion of the PM would need increased contributions from intact shoulder musculature to generate shoulder torques. This study aimed to identify neuromuscular compensation strategies adopted by subpectoral implant breast reconstruction patients using novel muscle synergy analyses. Fourteen patients treated bilaterally with subpectoral implant breast reconstruction (>2.5 years post-reconstruction) were compared to ten healthy controls. Surface electromyography was obtained from sixteen shoulder muscles as participants generated eight three-dimensional (3D) shoulder torques in five two-dimensional arm postures bilaterally. Non-negative matrix factorization revealed the muscle synergies utilized by each experimental group on the dominant and non-dominant limbs, and the normalized similarity index assessed group differences in overall synergy structure. Bilateral subpectoral implant patients exhibited similar shoulder strength to healthy controls on the dominant and non-dominant arms. Our results suggest that 3D shoulder torque is driven by three shoulder muscle synergies in both healthy participants and subpectoral implant patients. Two out of three synergies were more similar than is expected by chance between the groups on the non-dominant arm, whereas only one synergy is more similar than is expected by chance on the dominant arm. While bilateral shoulder strength is maintained following bilateral subpectoral implant breast reconstruction, a closer analysis of the muscle synergy patterns underlying 3D shoulder torque generation reveals that subpectoral implant patients adopt compensatory neuromuscular strategies only with the dominant arm.

Quantal biomechanical effects in speech postures of the lips

The unique biomechanical and functional constraints on human speech make it a promising area for research investigating modular control of movement. The present article illustrates how a modular control approach to speech can provide insights relevant to understanding both motor control and observed variation across languages. We specifically explore the robust typological finding that languages produce different degrees of labial constriction using distinct muscle groupings and concomitantly distinct lip postures. Research has suggested that these lip postures exploit biomechanical regions of nonlinearity between neural activation and movement, also known as quantal regions, to allow movement goals to be realized despite variable activation signals. We present two sets of computer simulations showing that these labial postures can be generated under the assumption of modular control and that the corresponding modules are biomechanically robust: first to variation in the activation levels of participating muscles, and second to interference from surrounding muscles. These results provide support for the hypothesis that biomechanical robustness is an important factor in selecting the muscle groupings used for speech movements and provide insight into the neurological control of speech movements and how biomechanical and functional constraints govern the emergence of speech motor modules. We anticipate that future experimental work guided by biomechanical simulation results will provide new insights into the neural organization of speech movements.NEW & NOTEWORTHY This article provides additional evidence that speech motor control is organized in a modular fashion and that biomechanics constrain the kinds of motor modules that may emerge. It also suggests that speech can be a fruitful domain for the study of modularity and that a better understanding of speech motor modules will be useful for speech research. Finally, it suggests that biomechanical modeling can serve as a useful complement to experimental work when studying modularity.

Application of a neural interface for restoration of leg movements: Intra-spinal stimulation using the brain electrical activity in spinally injured rabbits

This study aimed to design a neural interface that extracts movement commands from the brain to generate appropriate intra-spinal stimulation to restore leg movement. This study comprised four steps: (1) Recording electrocorticographic (ECoG) signals and corresponding leg movements in different trials. (2) Partial laminectomy to induce spinal cord injury (SCI) and detect motor modules in the spinal cord. (3) Delivering appropriate intra-spinal stimulation to the motor modules for restoration of the movements to those documented before SCI. (4) Development of a neural interface created by sparse linear regression (SLiR) model to detect movement commands transmitted from the brain to the modules. Correlation coefficient (CC) and normalized root mean square (NRMS) error was calculated to evaluate the neural interface effectiveness. It was found that by stimulating detected spinal cord modules, joint angle evaluated before SCI was not significantly different from that of post-SCI (P > 0.05). Based on results of SLiR model, overall CC and NRMS values were 0.63 ± 0.14 and 0.34 ± 0.16 (mean ± SD), respectively. These results indicated that ECoG data contained information about intra-spinal stimulations and the developed neural interface could produce intra-spinal stimulation based on ECoG data, for restoration of leg movements after SCI.

Non-negative matrix factorisation is the most appropriate method for extraction of muscle synergies in walking and running

Muscle synergies provide a simple description of a complex motor control mechanism. Synergies are extracted from muscle activation patterns using factorisation methods. Despite the availability of several factorisation methods in the literature, the most appropriate method for muscle synergy extraction is currently unknown. In this study, we compared four muscle synergy extraction methods: non-negative matrix factorisation, principal component analysis, independent component analysis, and factor analysis. Probability distribution of muscle activation patterns were compared with the probability distribution of synergy excitation primitives obtained from the four factorisation methods. Muscle synergies extracted using non-negative matrix factorisation best matched the probability distribution of muscle activation patterns across different walking and running speeds. Non-negative matrix factorisation also best tracked changes in muscle activation patterns compared to the other factorisation methods. Our results suggest that non-negative matrix factorisation is the best factorisation method for identifying muscle synergies in dynamic tasks with different levels of muscle contraction.

Posture-dependent neuromuscular contributions to three-dimensional isometric shoulder torque generation

This study is the first to identify the muscle synergies underlying three-dimensional isometric shoulder torque generation. Although the overall structure of these synergies was unaffected by arm posture, the weighted contributions of several muscles composing two synergy patterns changed as a function of the elevation or plane of elevation of the shoulder. Our findings provide valuable insight for the development of targeted interventions for the restoration of shoulder function after neuromuscular or orthopedic pathologies.

Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait

Children with unilateral cerebral palsy (CP) walk independently although with an asymmetrical, more poorly coordinated pattern compared to their peers. While gait biomechanics in unilateral CP and their alteration from those without CP have been well documented, cortical mechanisms underlying gait remain inadequately understood. To the best of our knowledge, this is the first study utilizing electroencephalography (EEG) during treadmill gait in older children with and without CP. Lower limb surface electromyographic (EMG) data were collected and muscle synergy analyses performed to quantify motor output. Our primary goal was to evaluate the relationships between cortical and muscle activation within and across groups and hemispheres to provide novel insights into neural control of gait and how it may be disrupted by an early unilateral brain injury. Participants included 9 children with unilateral CP, mean age 16.0 ± 2.7 years, and 12 with typical development (TD), mean age 14.8 ± 3.0 years. EEG data were collected during a standing baseline and treadmill walking at self-selected speed. EMG of 16 lower limb muscles were also collected bilaterally and synchronized with EEG. No significant group differences were found in synergy number or structure across groups. Six cortical clusters were identified as having gait-related activation and all contained participants from both CP and TD groups; however, the percent of individuals per group appearing in different clusters varied. Notably, the cluster least represented in CP was the non-dominant motor region. Both groups showed mu-band ERD in the motor clusters during gait although sustained beta-band ERD was not evident in TD. The CP group showed greater cortical activation than TD during walking as measured by mu- and beta-ERD in the dominant and non-dominant motor and parietal regions and elevated low gamma-activity in the frontal and parietal areas, a unique finding in CP. CP showed greater bilateral motor EEG-EMG coherence in the gamma-band with the hallucis longus compared to TD. In summary, individuals with CP display increased cortical activation during gait possibly relating to differences in distal motor control of the more affected side. Strategies that iteratively reduce cortical activation while improving selective motor control are needed in CP.

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

Background

Children with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP.

Aim

Investigate the underlying SMC and changes that may occur when gait is adapted with biofeedback.

Methods

Twenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6–16 years, M: 16/F: 9) were challenged with real-time biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials.

Results

Despite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF₁ from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials.

Conclusion

These results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these are clinically meaningful at the level of an individual. Adaptations may be limited in the short term, and further investigation is essential to establish if long term training using biofeedback leads to adapted SMC.

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.

Augmentation of spinal cord glutamatergic synaptic currents in zebrafish primary motoneurons expressing mutant human TARDBP (TDP-43)

Though there is compelling evidence that de-innervation of neuromuscular junctions (NMJ) occurs early in amyotrophic lateral sclerosis (ALS), defects arising at synapses in the spinal cord remain incompletely understood. To investigate spinal cord synaptic dysfunction, we took advantage of a zebrafish larval model and expressed either wild type human TARDBP (wtTARDBP) or the ALS-causing G348C variant (mutTARDBP). The larval zebrafish is ideally suited to examine synaptic connectivity between descending populations of neurons and spinal cord motoneurons as a fully intact spinal cord is preserved during experimentation. Here we provide evidence that the tail-beat motor pattern is reduced in both frequency and duration in larvae expressing mutTARDBP. In addition, we report that motor-related synaptic depolarizations in primary motoneurons of the spinal cord are shorter in duration and fewer action potentials are evoked in larvae expressing mutTARDBP. To more thoroughly examine spinal cord synaptic dysfunction in our ALS model, we isolated AMPA/kainate-mediated glutamatergic miniature excitatory post-synaptic currents in primary motoneurons and found that in addition to displaying a larger amplitude, the frequency of quantal events was higher in larvae expressing mutTARDBP when compared to larvae expressing wtTARDBP. In a final series of experiments, we optogenetically drove neuronal activity in the hindbrain and spinal cord population of descending ipsilateral glutamatergic interneurons (expressing Chx10) using the Gal4-UAS system and found that larvae expressing mutTARDBP displayed abnormal tail-beat patterns in response to optogenetic stimuli and augmented synaptic connectivity with motoneurons. These findings indicate that expression of mutTARDBP results in functionally altered glutamatergic synapses in the spinal cord.

Motor Control After Human SCI Through Activation of Muscle Synergies Under Spinal Cord Stimulation

Spinal cord stimulation (SCS) has enabled motor recovery in paraplegics with motor complete spinal cord injury (SCI). However, the physiological mechanisms underlying this recovery are unknown. This paper analyzes muscle synergies in two motor complete SCI patients under SCS during standing and compares them with muscle synergies in healthy subjects, in order to help elucidate the mechanisms that enable motor control through SCS. One challenge is that standard muscle synergy extraction algorithms, such as non-negative matrix factorization (NMF), fail when applied to SCI patients under SCS. We develop a new algorithm-rShiftNMF-to extract muscle synergies in these cases. We find muscle synergies extracted by rShiftNMF are significantly better at interpreting electromyography (EMG) activity, and resulting synergy features are more physiologically meaningful. By analyzing muscle synergies from SCI patients and healthy subjects, we find that: 1) SCI patients rely significantly on muscle synergy activation to generate motor activity; 2) interleaving SCS can selectively activate an additional muscle synergy that is critical to SCI standing; and 3) muscle synergies extracted from SCI patients under SCS differ substantially from those extracted from healthy subjects. We provide evidence that after spinal cord injury, SCS influences motor function through muscle synergy activation.

Design and effectiveness evaluation of mirror myoelectric interfaces: a novel method to restore movement in hemiplegic patients

The motor impairment occurring after a stroke is characterized by pathological muscle activation patterns or synergies. However, while robot-aided myoelectric interfaces have been proposed for stroke rehabilitation, they do not address this issue, which might result in inefficient interventions. Here, we present a novel paradigm that relies on the correction of the pathological muscle activity as a way to elicit rehabilitation, even in patients with complete paralysis. Previous studies demonstrated that there are no substantial inter-limb differences in the muscle synergy organization of healthy individuals. We propose building a subject-specific model of muscle activity from the healthy limb and mirroring it to use it as a learning tool for the patient to reproduce the same healthy myoelectric patterns on the paretic limb during functional task training. Here, we aim at understanding how this myoelectric model, which translates muscle activity into continuous movements of a 7-degree of freedom upper limb exoskeleton, could transfer between sessions, arms and tasks. The experiments with 8 healthy individuals and 2 chronic stroke patients proved the feasibility and effectiveness of such myoelectric interface. We anticipate the proposed method to become an efficient strategy for the correction of maladaptive muscle activity and the rehabilitation of stroke patients.

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).

Challenging human locomotion: stability and modular organisation in unsteady conditions

The need to move over uneven terrain is a daily challenge. In order to face unexpected perturbations due to changes in the morphology of the terrain, the central nervous system must flexibly modify its control strategies. We analysed the local dynamic stability and the modular organisation of muscle activation (muscle synergies) during walking and running on an even- and an uneven-surface treadmill. We hypothesized a reduced stability during uneven-surface locomotion and a reorganisation of the modular control. We found a decreased stability when switching from even- to uneven-surface locomotion (p < 0.001 in walking, p = 0.001 in running). Moreover, we observed a substantial modification of the time-dependent muscle activation patterns (motor primitives) despite a general conservation of the time-independent coefficients (motor modules). The motor primitives were considerably wider in the uneven-surface condition. Specifically, the widening was significant in both the early (+40.5%, p < 0.001) and late swing (+7.7%, p = 0.040) phase in walking and in the weight acceptance (+13.6%, p = 0.006) and propulsion (+6.0%, p = 0.041) phase in running. This widening highlighted an increased motor output’s robustness (i.e. ability to cope with errors) when dealing with the unexpected perturbations. Our results confirmed the hypothesis that humans adjust their motor control strategies’ timing to deal with unsteady locomotion.

The Influence of Footwear on the Modular Organization of Running

For most of our history, we predominantly ran barefoot or in minimalist shoes. The advent of modern footwear, however, might have introduced alterations in the motor control of running. The present study investigated shod and barefoot running under the perspective of the modular organization of muscle activation, in order to help addressing the neurophysiological factors underlying human locomotion. On a treadmill, 20 young and healthy inexperienced barefoot runners ran shod and barefoot at preferred speed (2.8 ± 0.4 m/s). Fundamental synergies, containing the time-dependent activation coefficients (motor primitives) and the time-invariant muscle weightings (motor modules), were extracted from 24 ipsilateral electromyographic activities using non-negative matrix factorization. In shod running, the average foot strike pattern was a rearfoot strike, while in barefoot running it was a mid-forefoot strike. In both conditions, five fundamental synergies were enough to describe as many gait cycle phases: weight acceptance, propulsion, arm swing, early swing and late swing. We found the motor primitives to be generally shifted earlier in time during the stance-related phases and later in the swing-related ones in barefoot running. The motor primitive describing the propulsion phase was significantly of shorter duration (peculiarity confirmed by the analysis of the spinal motor output). The arm swing primitive, instead, was significantly wider in the barefoot condition. The motor modules demonstrated analogous organization with some significant differences in the propulsion, arm swing and late swing synergies. Other than to the trivial absence of shoes, the differences might be deputed to the lower ankle gear ratio (and the consequent increased system instability) and to the higher recoil capabilities of the longitudinal foot arch during barefoot compared to shod running.

Muscle proprioceptors in adult rat: mechanosensory signaling and synapse distribution in spinal cord

The characteristic signaling and intraspinal projections of muscle proprioceptors best described in the cat are often generalized across mammalian species. However, species-dependent adaptations within this system seem necessary to accommodate asymmetric scaling of length, velocity, and force information required by the physics of movement. In the present study we report mechanosensory responses and intraspinal destinations of three classes of muscle proprioceptors. Proprioceptors from triceps surae muscles in adult female Wistar rats anesthetized with isoflurane were physiologically classified as muscle spindle group Ia or II or as tendon organ group Ib afferents, studied for their firing responses to passive-muscle stretch, and in some cases labeled and imaged for axon projections and varicosities in spinal segments. Afferent projections and the laminar distributions of provisional synapses in rats closely resembled those found in the cat. Afferent signaling of muscle kinematics was also similar to reports in the cat, but rat Ib afferents fired robustly during passive-muscle stretch and Ia afferents displayed an exaggerated dynamic response, even after locomotor scaling was accounted for. These differences in mechanosensory signaling by muscle proprioceptors may represent adaptations for movement control in different animal species.NEW & NOTEWORTHY Muscle sensory neurons signal information necessary for controlling limb movements. The information encoded and transmitted by muscle proprioceptors to networks in the spinal cord is known in detail only for the cat, but differences in size and behavior of other species challenge the presumed generalizability. This report presents the first findings detailing specializations in mechanosensory signaling and intraspinal targets for functionally identified subtypes of muscle proprioceptors in the rat.

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).

A Longitudinal Electromyography Study of Complex Movements in Poststroke Therapy. 2: Changes in Coordinated Muscle Activation

Fine motor control is achieved through the coordinated activation of groups of muscles, or "muscle synergies." Muscle synergies change after stroke as a consequence of the motor deficit. We investigated the pattern and longitudinal changes in upper limb muscle synergies during therapy in a largely unconstrained movement in patients with a broad spectrum of poststroke residual voluntary motor capacity. Electromyography (EMG) was recorded using wireless telemetry from 6 muscles acting on the more-affected upper body in 24 stroke patients at early and late therapy during formal Wii-based Movement Therapy (WMT) sessions, and in a subset of 13 patients at 6-month follow-up. Patients were classified with low, moderate, or high motor-function. The Wii-baseball swing was analyzed using a non-negative matrix factorization (NMF) algorithm to extract muscle synergies from EMG recordings based on the temporal activation of each synergy and the contribution of each muscle to a synergy. Motor-function was clinically assessed immediately pre- and post-therapy and at 6-month follow-up using the Wolf Motor Function Test, upper limb motor Fugl-Meyer Assessment, and Motor Activity Log Quality of Movement scale. Clinical assessments and game performance demonstrated improved motor-function for all patients at post-therapy (p < 0.01), and these improvements were sustained at 6-month follow-up (p > 0.05). NMF analysis revealed fewer muscle synergies (mean ± SE) for patients with low motor-function (3.38 ± 0.2) than those with high motor-function (4.00 ± 0.3) at early therapy (p = 0.036) with an association trend between the number of synergies and the level of motor-function. By late therapy, there was no significant change between groups, although there was a pattern of increase for those with low motor-function over time. The variability accounted for demonstrated differences with motor-function level (p < 0.05) but not time. Cluster analysis of the pooled synergies highlighted the therapy-induced change in muscle activation. Muscle synergies could be identified for all patients during therapy activities. These results show less complexity and more co-activation in the muscle activation for patients with low motor-function as a higher number of muscle synergies reflects greater movement complexity and task-related phasic muscle activation. The increased number of synergies and changes within synergies by late-therapy suggests improved motor control and movement quality with more distinct phases of movement.

On the Methodological Implications of Extracting Muscle Synergies from Human Locomotion

We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To evaluate the effects of signal recording and processing on the outcomes, we analyzed the intraday and interday computation reliability. Results show that the IGNMF achieved a significantly higher reconstruction quality and on average needs one less synergy to sufficiently reconstruct the original signals compared to the GNMF. For both factorizations, the HP with a cut-off frequency of 250[Formula: see text]Hz significantly reduces the number of synergies. We identified the filter configuration of fourth order, HP 50[Formula: see text]Hz and LP 20[Formula: see text]Hz as the most suitable to minimize the combination of fundamental synergies, providing a higher reliability across all filtering conditions even if HP 250[Formula: see text]Hz is excluded. Defining a fundamental synergy as a single-peaked activation pattern, for walking and running we identified five and six fundamental synergies, respectively using both algorithms. The variability in combined synergies produced by different filtering conditions and factorization methods on the same data set suggests caution when attributing a neurophysiological nature to the combined synergies.

Motor synergies research in physical therapy: advantages of the uncontrolled manifold approach

ABSTRACT Movement is central to physical therapy identity and practice. Advances in the science of movement control, motor learning and development are thus inextricably tied to professional development and clinical activity. This paper aims to describe a prominent approach to motor control with potential to greatly advance the understanding of movement dysfunction: the uncontrolled manifold (UCM). An argument is formulated for incorporating this method of data analysis in rehabilitation research. It is a narrative review of the relevant literature. Research in physical therapy could greatly benefit from investigating synergies with the theory and methods of UCM. Research should seek connections between functioning in daily life tasks and the assembling of synergies to stabilize different performance variables, the UCM variability measures, the synergy strength indexes, and the anticipatory synergy adjustments. Changes in these synergy variables should also be quantified after rehabilitation interventions. UCM can offer one solid science-based approach to inform clinical decisions on whether synergies have to be broken, rebalanced, created, or reinforced in patients with movement dysfunction.

An Optogenetic Demonstration of Motor Modularity in the Mammalian Spinal Cord

Motor modules are neural entities hypothesized to be building blocks of movement construction. How motor modules are underpinned by neural circuits has remained obscured. As a first step towards dissecting these circuits, we optogenetically evoked motor outputs from the lumbosacral spinal cord of two strains of transgenic mice – the Chat, with channelrhodopsin (ChR2) expressed in motoneurons, and the Thy1, expressed in putatively excitatory neurons. Motor output was represented as a spatial field of isometric ankle force. We found that Thy1 force fields were more complex and diverse in structure than Chat fields: the Thy1 fields comprised mostly non-parallel vectors while the Chat fields, mostly parallel vectors. In both, most fields elicited by co-stimulation of two laser beams were well explained by linear combination of the separately-evoked fields. We interpreted the Thy1 force fields as representations of spinal motor modules. Our comparison of the Chat and Thy1 fields allowed us to conclude, with reasonable certainty, that the structure of neuromotor modules originates from excitatory spinal interneurons. Our results not only demonstrate, for the first time using optogenetics, how the spinal modules follow linearity in their combinations, but also provide a reference against which future optogenetic studies of modularity can be compared.

A Quasi-Likelihood Approach to Nonnegative Matrix Factorization

A unified approach to nonnegative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proved using the expectation-maximization algorithm. In addition, a measure to evaluate the goodness of fit of the resulting factorization is described. The proposed methods allow modeling of nonlinear effects using appropriate link functions and are illustrated using an application in biomedical signal processing.

A modular robust control framework for control of movement elicited by multi-electrode intraspinal microstimulation

OBJECTIVE

An important issue in restoring motor function through intraspinal microstimulation (ISMS) is the motor control. To provide a physiologically plausible motor control using ISMS, it should be able to control the individual motor unit which is the lowest functional unit of motor control. By focal stimulation only a small group of motor neurons (MNs) within a motor pool can be activated. Different groups of MNs within a motor pool can potentially be activated without involving adjacent motor pools by local stimulation of different parts of a motor pool via microelectrode array implanted into a motor pool. However, since the system has multiple inputs with single output during multi-electrode ISMS, it poses a challenge to movement control. In this paper, we proposed a modular robust control strategy for movement control, whereas multi-electrode array is implanted into each motor activation pool of a muscle.

APPROACH

The controller was based on the combination of proportional-integral-derivative and adaptive fuzzy sliding mode control. The global stability of the controller was guaranteed.

MAIN RESULTS

The results of the experiments on rat models showed that the multi-electrode control can provide a more robust control and accurate tracking performance than a single-electrode control. The control output can be pulse amplitude (pulse amplitude modulation, PAM) or pulse width (pulse width modulation, PWM) of the stimulation signal. The results demonstrated that the controller with PAM provided faster convergence rate and better tracking performance than the controller with PWM.

SIGNIFICANCE

This work represents a promising control approach to the restoring motor functions using ISMS. The proposed controller requires no prior knowledge about the dynamics of the system to be controlled and no offline learning phase. The proposed control design is modular in the sense that each motor pool has an independent controller and each controller is able to control ISMS through an array of microelectrodes.

Similar Motor Cortical Control Mechanisms for Precise Limb Control during Reaching and Locomotion

Throughout the course of evolution there has been a parallel development of the complexity and flexibility of the nervous system and the skeletomuscular system that it controls. This development is particularly evident for the cerebral cortical areas and the transformation of the use of the upper limbs from a purely locomotor function to one including, or restricted to, reaching and grasping. This study addresses the issue of whether the control of reaching has involved the development of new cortical circuits or whether the same neurons are used to control both locomotion and reaching. We recorded the activity of pyramidal tract neurons in the motor cortex of the cat both during voluntary gait modifications and during reaching. All cells showed generally similar patterns of activity in both tasks. More specifically, we showed that, in many cases, cells maintained a constant temporal relationship to the activity of synergistic muscle groups in each task. In addition, in some cells the relationship between the intensity of the cell discharge activity and the magnitude of the EMG activity was equally constant during gait modifications and reaching. As such, the results are compatible with the hypothesis that the corticospinal circuits used to control reaching evolved from those used to precisely modify gait.

A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis

A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES) has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue). This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4-degree of freedom gait model.

Experimental Muscle Pain Impairs the Synergistic Modular Control of Neck Muscles

A motor task can be performed via different patterns of muscle activation that show regularities that can be factorized in combinations of a reduced number of muscle groupings (also referred to as motor modules, or muscle synergies). In this study we evaluate whether an acute noxious stimulus induces a change in the way motor modules are combined to generate movement by neck muscles. The neck region was selected as it is a region with potentially high muscular redundancy. We used the motor modules framework to assess the redistribution of muscular activity of 12 muscles (6 per side) in the neck region of 8 healthy individuals engaged in a head and neck aiming task, in non-painful conditions (baseline, isotonic saline injection, post pain) and after the injection of hypertonic saline into the right splenius capitis muscle. The kinematics of the task was similar in the painful and control conditions. A general decrease of activity was noted for the injected muscle during the painful condition together with an increase or decrease of the activity of the other muscles. Subjects did not adopt shared control strategies (motor modules inter subject similarity at baseline 0.73±0.14); the motor modules recorded during the painful condition could not be used to reconstruct the activation patterns of the control conditions, and the painful stimulus triggered a subject-specific redistribution of muscular activation (i.e., in some subjects the activity of a given muscle increased, whereas in other subjects it decreased with pain). Alterations of afferent input (i.e., painful stimulus) influenced motor control at a multi muscular level, but not kinematic output. These findings provide new insights into the motor adaptation to pain.

Neuromuscular adjustments of gait associated with unstable conditions

A compact description of coordinated muscle activity is provided by the factorization of electromyographic (EMG) signals. With the use of this approach, it has consistently been shown that multimuscle activity during human locomotion can be accounted for by four to five modules, each one comprised of a basic pattern timed at a different phase of gait cycle and the weighting coefficients of synergistic muscle activations. These modules are flexible, in so far as the timing of patterns and the amplitude of weightings can change as a function of gait speed and mode. Here we consider the adjustments of the locomotor modules related to unstable walking conditions. We compared three different conditions, i.e., locomotion of healthy subjects on slippery ground (SL) and on narrow beam (NB) and of cerebellar ataxic (CA) patients on normal ground. Motor modules were computed from the EMG signals of 12 muscles of the right lower limb using non-negative matrix factorization. The unstable gait of SL, NB, and CA showed significant changes compared with controls in the stride length, stride width, range of angular motion, and trunk oscillations. In most subjects of all three unstable conditions, >70% of the overall variation of EMG waveforms was accounted for by four modules that were characterized by a widening of muscle activity patterns. This suggests that the nervous system adopts the strategy of prolonging the duration of basic muscle activity patterns to cope with unstable conditions resulting from either slippery ground, reduced support surface, or pathology.

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.

Efferent Feedback in a Spinal-Like Controller: Reaching With Perturbations

We use simulations of a controller that adopts a spinal-like network topology for goal-oriented reaching and assess its sensitivity to the dynamics of internal elements that allow context-independent performance. Such internal elements are often referred to as inverse or forward models of the periphery dynamics, depending on the proposed controller theory. Here, the "models" are used in a forward implementation, and we evaluate how the controller's performance would be affected by the nature of the model. For each point-to-point reaching motion experiment, we use forms of internal "efference models" (e.g., full mathematical representations of peripheral dynamics, simple spindle feedback, etc.) driven by motor reafference, then compare hand trajectories and hand path speeds in the presence or absence of external perturbations. It is demonstrated that a simple velocity-based model reduced the effects of dynamic perturbations by as much as 66%. In addition, the 2D hand trajectories varied from a biological reference by only 0.05 cm. Thus, the controller facilitated biological like motions while providing response to dynamic events which are omitted in earlier biomimetic controllers. This research suggests that these spinal-like systems are robust and tunable via gain-fields without the need of context dependent pre-planning.

Evidence for altered upper extremity muscle synergies in chronic stroke survivors with mild and moderate impairment

Previous studies indicate that motor coordination may be achieved by assembling task-dependent combinations of a few muscle synergies, defined here as fixed patterns of activation across a set of muscles. Our recent study of severely impaired chronic stroke survivors showed that some muscle synergies underlying isometric force generation at the hand are altered in the affected arm. However, whether similar alterations are evident in stroke survivors with lesser impairment remains unclear. Accordingly, we examined muscle synergies underlying spatial patterns of elbow and shoulder muscle activation recorded during an isometric force target matching protocol performed by 16 chronic stroke survivors, evenly divided across mild and moderate impairment levels. We applied non-negative matrix factorization to identify the muscle synergies and compared their structure across groups, including previously collected data from six age-matched control subjects and eight severely impaired stroke survivors. For all groups, EMG spatial patterns were well explained by task-dependent combinations of only a few (typically 4) muscle synergies. Broadly speaking, elbow-related synergies were conserved across stroke survivors, regardless of impairment level. In contrast, the shoulder-related synergies of some stroke survivors with mild and moderate impairment differed from controls, in a manner similar to severely impaired subjects. Cluster analysis of pooled synergies for the 30 subjects identified seven distinct clusters (synergies). Subsequent analysis confirmed that the incidences of three elbow-related synergies were independent of impairment level, while the incidences of four shoulder-related synergies were systematically correlated with impairment level. Overall, our results suggest that alterations in the shoulder muscle synergies underlying isometric force generation appear prominently in mild and moderate stroke, as in most cases of severe stroke, in an impairment level-dependent manner.

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.

Comparative need for spinal stabilisation between quadrupedal and bipedal locomotion

Sheep are commonly used as an animal model for the human lumbar spine, but similarities in trunk muscle activity of humans and sheep during functional tasks such as locomotion have not been investigated. Therefore, the aim of the study was to evaluate trunk and pelvic limb muscle activity during walk and run/trot gaits in man and sheep. Electromyography of the muscles erector spinae (ES), gluteus maximus (GM), rectus abdominis (RA), obliquus externus (OE) and obliquus internus (OI) were collected in 24 humans and 15 sheep during treadmill walk and run/trot. Kinematic data from the tarsus (human) or metatarsus (sheep) were obtained to define motion cycles and determine stride characteristics. Mean and range of normalised muscle activity were calculated. In phasic muscles, the occurrence of the maximum was reported. At walk, mean activity was greater in humans for all three abdominal muscles (all p<0.01). At the run/trot, mean activity of ES was significantly greater in sheep (p<0.05) and mean activity of right OI was greater in humans (p=0.016). At the walk, range of ES activity was significantly greater in humans compared to sheep (p<0.01), but significantly smaller in humans in RA and right OE (p<0.05). At the run/trot, range of activity was significantly greater in humans compared to sheep in all muscles (p<0.05), except right RA and OI. Compared to humans, occurrence of maximum activity was earlier in sheep for ES right during walk (p=0.005), and later for GM during walk and run/trot (p<0.001). The results suggest that numerous differences in trunk muscle activity exist between man and sheep during treadmill walk and run/trot, and that these differences are muscle-and gait-specific. Trunk muscle activity should therefore be regarded as species-specific which suggests differences in stabilization strategies. This should be taken into consideration when extrapolating animal model findings to the human spine.

Spinal reflexes in brain death

Spontaneous and reflex movements have been described in brain death and these unusual movements might cause uncertainties in diagnosis. In this study we evaluated the presence of spinal reflexes in patients who fulfilled the criteria for brain death. Thirty-two (22 %) of 144 patients presented unexpected motor movements spontaneously or during examinations. These patients exhibited the following signs: undulating toe, increased deep tendon reflexes, plantar responses, Lazarus sign, flexion-withdrawal reflex, facial myokymia, neck-arm flexion, finger jerks and fasciculations. In comparison, there were no significant differences in age, sex, etiology of brain death and hemodynamic laboratory findings in patients with and without reflex motor movement. Spinal reflexes should be well recognized by physicians and it should be born in mind that brain death can be determined in the presence of spinal reflexes.

An adaptive spinal-like controller: tunable biomimetic behavior for a robotic limb

Background

Spinal-like regulators have recently been shown to support complex behavioral patterns during volitional goal-oriented reaching paradigms. We use an interpretation of the adaptive spinal-like controller as inspiration for the development of a controller for a robotic limb. It will be demonstrated that a simulated robot arm with linear actuators can achieve biological-like limb movements. In addition, it will be shown that programmability in the regulator enables independent spatial and temporal changes to be defined for movement tasks, downstream of central commands using sensory stimuli. The adaptive spinal-like controller is the first to demonstrate such behavior for complex motor behaviors in multi-joint limb movements.

Methods

The controller is evaluated using a simulated robotic apparatus and three goal-oriented reaching paradigms: 1) shaping of trajectory profiles during reaching; 2) sensitivity of trajectories to sudden perturbations; 3) reaching to a moving target. The experiments were designed to highlight complex motor tasks that are omitted in earlier studies, and important for the development of improved artificial limb control.

Results

In all three cases the controller was able to reach the targets without a priori planning of end-point or segmental motor trajectories. Instead, trajectory spatio-temporal dynamics evolve from properties of the controller architecture using the spatial error (vector distance to goal). Results show that curvature amplitude in hand trajectory paths are reduced by as much as 98% using simple gain scaling techniques, while adaptive network behavior allows the regulator to successfully adapt to perturbations and track a moving target. An important observation for this study is that all motions resemble human-like movements with non-linear muscles and complex joint mechanics.

Conclusions

The controller shows that it can adapt to various behavioral contexts which are not included in previous biomimetic studies. The research supplements an earlier study by examining the tunability of the spinal-like controller for complex reaching tasks. This work is a step toward building more robust controllers for powered artificial limbs.