Muscle synergies are associated with intermuscular coherence and cortico-synergy coherence in an isometric upper limb task.

To elucidate the underlying physiological mechanisms of muscle synergies, we investigated long-range functional connectivity by cortico-muscular (CMC), intermuscular (IMC) and cortico-synergy (CSC) coherence. Fourteen healthy participants executed an isometric upper limb task in synergy-tuned directions. Cortical activity was recorded using 32-channel electroencephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorisation (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy-preferred directions (PDs). A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Overall, we were able to identify four different synergies from the multidirectional task. A significant alpha band IMC was consistently present in all extracted synergies. Moreover, IMC alpha band was higher between muscles with higher weights within a synergy. Interestingly, CSC alpha band was also significantly higher across muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. The presence of a shared input onto synergistic muscles within a synergy supports the idea of neurally derived muscle synergies that build human movement. Our findings suggest cortical modulation of some of the synergies and the consequential existence of shared input between muscles within cortically modulated synergies.

Effects of arm weight support on neuromuscular activation during reaching in chronic stroke patients.

To better understand how arm weight support (WS) can be used to alleviate upper limb impairment after stroke, we investigated the effects of WS on muscle activity, muscle synergy expression, and corticomotor excitability (CME) in 13 chronic stroke patients and 6 age-similar healthy controls. For patients, lesion location and corticospinal tract integrity were assessed using magnetic resonance imaging. Upper limb impairment was assessed using the Fugl-Meyer upper extremity assessment with patients categorised as either mild or moderate-severe. Three levels of WS were examined: low = 0, medium = 50 and high = 100% of full support. Surface EMG was recorded from 8 upper limb muscles, and muscle synergies were decomposed using non-negative matrix factorisation from data obtained during reaching movements to an array of 14 targets using the paretic or dominant arm. Interactions between impairment level and WS were found for the number of targets hit, and EMG measures. Overall, greater WS resulted in lower EMG levels, although the degree of modulation between WS levels was less for patients with moderate-severe compared to mild impairment. Healthy controls expressed more synergies than patients with moderate-severe impairment. Healthy controls and patients with mild impairment showed more synergies with high compared to low weight support. Transcranial magnetic stimulation was used to elicit motor-evoked potentials (MEPs) to which stimulus-response curves were fitted as a measure of corticomotor excitability (CME). The effect of WS on CME varied between muscles and across impairment level. These preliminary findings demonstrate that WS has direct and indirect effects on muscle activity, synergies, and CME and warrants further study in order to reduce upper limb impairment after stroke.

Motor cortical correlates of arm resting in the context of a reaching task and implications for prosthetic control.

Prosthetic devices are being developed to restore movement for motor-impaired individuals. A robotic arm can be controlled based on models that relate motor-cortical ensemble activity to kinematic parameters. The models are typically built and validated on data from structured trial periods during which a subject actively performs specific movements, but real-world prosthetic devices will need to operate correctly during rest periods as well. To develop a model of motor cortical modulation during rest, we trained monkeys (Macaca mulatta) to perform a reaching task with their own arm while recording motor-cortical single-unit activity. When a monkey spontaneously put its arm down to rest between trials, our traditional movement decoder produced a nonzero velocity prediction, which would cause undesired motion when applied to a prosthetic arm. During these rest periods, a marked shift was found in individual units' tuning functions. The activity pattern of the whole population during rest (Idle state) was highly distinct from that during reaching movements (Active state), allowing us to predict arm resting from instantaneous firing rates with 98% accuracy using a simple classifier. By cascading this state classifier and the movement decoder, we were able to predict zero velocity correctly, which would avoid undesired motion in a prosthetic application. Interestingly, firing rates during hold periods followed the Active pattern even though hold kinematics were similar to those during rest with near-zero velocity. These findings expand our concept of motor-cortical function by showing that population activity reflects behavioral context in addition to the direct parameters of the movement itself.

High-performance neuroprosthetic control by an individual with tetraplegia.

BACKGROUND: Paralysis or amputation of an arm results in the loss of the ability to orient the hand and grasp, manipulate, and carry objects, functions that are essential for activities of daily living. Brain-machine interfaces could provide a solution to restoring many of these lost functions. We therefore tested whether an individual with tetraplegia could rapidly achieve neurological control of a high-performance prosthetic limb using this type of an interface. METHODS: We implanted two 96-channel intracortical microelectrodes in the motor cortex of a 52-year-old individual with tetraplegia. Brain-machine-interface training was done for 13 weeks with the goal of controlling an anthropomorphic prosthetic limb with seven degrees of freedom (three-dimensional translation, three-dimensional orientation, one-dimensional grasping). The participant's ability to control the prosthetic limb was assessed with clinical measures of upper limb function. This study is registered with ClinicalTrials.gov, NCT01364480. FINDINGS: The participant was able to move the prosthetic limb freely in the three-dimensional workspace on the second day of training. After 13 weeks, robust seven-dimensional movements were performed routinely. Mean success rate on target-based reaching tasks was 91·6% (SD 4·4) versus median chance level 6·2% (95% CI 2·0-15·3). Improvements were seen in completion time (decreased from a mean of 148 s [SD 60] to 112 s [6]) and path efficiency (increased from 0·30 [0·04] to 0·38 [0·02]). The participant was also able to use the prosthetic limb to do skilful and coordinated reach and grasp movements that resulted in clinically significant gains in tests of upper limb function. No adverse events were reported. INTERPRETATION: With continued development of neuroprosthetic limbs, individuals with long-term paralysis could recover the natural and intuitive command signals for hand placement, orientation, and reaching, allowing them to perform activities of daily living. FUNDING: Defense Advanced Research Projects Agency, National Institutes of Health, Department of Veterans Affairs, and UPMC Rehabilitation Institute.

Deep-Learning Markerless Tracking of Infant General Movements using Standard Video Recordings.

Monitoring spontaneous General Movements (GM) of infants 6-20 weeks post-term age is a reliable tool to assess the quality of neurodevelopment in early infancy. Abnormal or absent GMs are reliable prognostic indicators of whether an infant is at risk of developing neurological impairments and disorders such as cerebral palsy (CP). Therapeutic interventions are most effective at improving neuromuscular outcomes if administered in early infancy. Current clinical protocols require trained assessors to rate videos of infant movements, a time-intensive task. This work proposes a simple, inexpensive, and broadly applicable markerless pose-estimation approach for automatic infant movement tracking using conventional video recordings from handheld devices (e.g., tablets and mobile phones). We leverage the enhanced capabilities of deep-learning technology in image processing to identify 12 anatomical locations (3 per limb) in each video frame, tracking a baby's natural movement throughout the recordings. We validate the capability of resnet152 and a mobile-net-v2-1 to identify body-parts in unseen frames from a full-term male infant, using a novel automatic unsupervised approach that fuses likelihood outputs of a Kalman filter and the deep-nets. Both deep-net models were found to perform very well in the identification of anatomical locations in the unseen data with high average Percentage of Correct Keypoints (aPCK) performances of >99.65% across all locations.Clinical relevance-Results of this research confirm the feasibility of a low-cost and publicly accessible technology to automatically track infants' GMs and diagnose those at higher risk of developing neurological conditions early, when clinical interventions are most effective.

Fatigue Influences the Recruitment, but Not Structure, of Muscle Synergies.

The development of fatigue elicits multiple adaptations from the neuromuscular system. Muscle synergies are common patterns of neuromuscular activation that have been proposed as the building blocks of human movement. We wanted to identify possible adaptations of muscle synergies to the development of fatigue in the upper limb. Recent studies have reported that synergy structure remains invariant during the development of fatigue, but these studies did not examine isolated synergies. We propose a novel approach to characterise synergy adaptations to fatigue by taking advantage of the spatial tuning of synergies. This approach allows improved identification of changes to individual synergies that might otherwise be confounded by changing contributions of overlapping synergies. To analyse upper limb synergies, we applied non-negative matrix factorization to 14 EMG signals from muscles of 11 participants performing isometric contractions. A preliminary multidirectional task was used to identify synergy directional tuning. A subsequent fatiguing task was designed to fatigue the participants in their synergies' preferred directions. Both tasks provided virtual reality feedback of the applied force direction and magnitude, and were performed at 40% of each participant's maximal voluntary force. Five epochs were analysed throughout the fatiguing task to identify progressive changes of EMG amplitude, median frequency, synergy structure, and activation coefficients. Three to four synergies were sufficient to account for the variability contained in the original data. Synergy structure was conserved with fatigue, but interestingly synergy activation coefficients decreased on average by 24.5% with fatigue development. EMG amplitude did not change systematically with fatigue, whereas EMG median frequency consistently decreased across all muscles. These results support the notion of a neuromuscular modular organisation as the building blocks of human movement, with adaptations to synergy recruitment occurring with fatigue. When synergy tuning properties are considered, the reduction of activation of muscle synergies may be a reliable marker to identify fatigue.

An Activation Threshold Model for Response Inhibition.

Reactive response inhibition (RI) is the cancellation of a prepared response when it is no longer appropriate. Selectivity of RI can be examined by cueing the cancellation of one component of a prepared multi-component response. This substantially delays execution of other components. There is debate regarding whether this response delay is due to a selective neural mechanism. Here we propose a computational activation threshold model (ATM) and test it against a classical "horse-race" model using behavioural and neurophysiological data from partial RI experiments. The models comprise both facilitatory and inhibitory processes that compete upstream of motor output regions. Summary statistics (means and standard deviations) of predicted muscular and neurophysiological data were fit in both models to equivalent experimental measures by minimizing a Pearson Chi-square statistic. The ATM best captured behavioural and neurophysiological dynamics of partial RI. The ATM demonstrated that the observed modulation of corticomotor excitability during partial RI can be explained by nonselective inhibition of the prepared response. The inhibition raised the activation threshold to a level that could not be reached by the original response. This was necessarily followed by an additional phase of facilitation representing a secondary activation process in order to reach the new inhibition threshold and initiate the executed component of the response. The ATM offers a mechanistic description of the neural events underlying RI, in which partial movement cancellation results from a nonselective inhibitory event followed by subsequent initiation of a new response. The ATM provides a framework for considering and exploring the neuroanatomical constraints that underlie RI.

Stance limb ground reaction forces in high functioning stroke and healthy subjects during gait initiation.

BACKGROUND: Following stroke, little is known about ground reaction forces during gait initiation. OBJECTIVE: To compare stroke patients' with healthy subjects' anterior, medial, and lateral ground reaction forces generated during gait initiation. METHODS: Patients with left paresis, right paresis, and age-similar healthy subjects were recruited. During gait initiation the average peak anterior, medial, and lateral ground reaction forces acting on each lower limb were calculated when it was the stance limb. FINDINGS: Anterior ground reaction forces acting on the right and left stance limbs of healthy subjects were greater than anterior forces acting on the nonparetic and paretic limbs of stroke patients. Medial ground reaction forces for the nonparetic and paretic limbs of stroke patients and for the right and left stance limbs of healthy subjects were equivalent. While lateral ground reaction forces acting on the nonparetic and paretic limbs were equivalent for left paretic patients, for right paretic patients lateral forces acting on the nonparetic limb were greater compared to the paretic limb and also greater compared to the left limb of healthy subjects. INTERPRETATION: An effect of side-of-lesion was revealed in average peak lateral ground reaction force data. Larger lateral ground reaction forces acting on the left nonparetic stance limb of right paretic patients compared to the right nonparetic stance limb of left paretic patients during gait initiation may be an indication of differing adaptations that depend on the side-of-lesion.

A neuroanatomical framework for upper limb synergies after stroke.

Muscle synergies describe common patterns of co- or reciprocal activation that occur during movement. After stroke, these synergies change, often in stereotypical ways. The mechanism underlying this change reflects damage to key motor pathways as a result of the stroke lesion, and the subsequent reorganization along the neuroaxis, which may be further detrimental or restorative to motor function. The time course of abnormal synergy formation seems to lag spontaneous recovery that occurs in the initial weeks after stroke. In healthy individuals, motor cortical activity, descending via the corticospinal tract (CST) is the predominant driver of voluntary behavior. When the CST is damaged after stroke, other descending pathways may be up-regulated to compensate. The contribution of these pathways may emerge as new synergies take shape at the chronic stage after stroke, as a result of plasticity along the neuroaxis. The location of the stroke lesion and properties of the secondary descending pathways and their regulation are then critical for shaping the synergies in the remaining motor behavior. A consideration of the integrity of remaining descending motor pathways may aid in the design of new rehabilitation therapies.

Collaborative approach in the development of high-performance brain-computer interfaces for a neuroprosthetic arm: translation from animal models to human control.

Our research group recently demonstrated that a person with tetraplegia could use a brain-computer interface (BCI) to control a sophisticated anthropomorphic robotic arm with skill and speed approaching that of an able-bodied person. This multiyear study exemplifies important principles in translating research from foundational theory and animal experiments into a clinical study. We present a roadmap that may serve as an example for other areas of clinical device research as well as an update on study results. Prior to conducting a multiyear clinical trial, years of animal research preceded BCI testing in an epilepsy monitoring unit, and then in a short-term (28 days) clinical investigation. Scientists and engineers developed the necessary robotic and surgical hardware, software environment, data analysis techniques, and training paradigms. Coordination among researchers, funding institutes, and regulatory bodies ensured that the study would provide valuable scientific information in a safe environment for the study participant. Finally, clinicians from neurosurgery, anesthesiology, physiatry, psychology, and occupational therapy all worked in a multidisciplinary team along with the other researchers to conduct a multiyear BCI clinical study. This teamwork and coordination can be used as a model for others attempting to translate basic science into real-world clinical situations.

Baseplate for two-stage cranial mounting of BMI connectors.

OBJECTIVE: Intracortical electrode arrays provide the best spatial and temporal resolution signals for brain-machine interfaces. Wireless technologies are being developed to handle this information capacity, but currently the only means to deliver neural information from the implant to a signal processing unit is by a physical connection starting at a skull-mounted connector. The failure rate of the attachment of these connectors is significant. In this study we report an improvement to the traditional connectors. APPROACH: We have designed and applied an intermediary mounting plate that incorporates several features that provide better, more stable fixation to the skull: (1) wide legs allowing distribution of loading forces and distancing the intracranial screws from the skin interface, (2) a thin shelf to allow early osseointegration, (3) a concave interior to accommodate the curvature of the cranium, and (4) two-stage fixation process providing time for osseointegration prior to the application of loading forces from the connector. MAIN RESULTS: Six baseplates, over four design iterations, have now been tested in three non-human primates. The baseplates are associated with a substantially lower attachment failure rate. SIGNIFICANCE: Our baseplate design improves on the current skull-mounted connectors, leading to better outcomes for subjects and fewer catastrophic failure events that can terminate resource intensive intracortical recording experiments.