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Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. Electromyography (EMG) was recorded from eight hand-forearm muscles in eight healthy individuals. Modularity was defined using non-negative matrix factorization to identify low-rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high-density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both data sets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest that corticospinal connectivity to individual intrinsic hand muscles may be combined with modular multimuscle activation via synergies in the formation of hand postures.bNEWamp; NOTEWORTHY/bThis is the first work to examine the similarity of modularity in hand muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex and that derived from voluntary hand movement. We show that TMS-elicited muscle synergies of the hand, measured at rest, reflect those found in voluntary behavior involving finger fractionation. This work provides a basis for future work using TMS to investigate muscle activation modularity in the human motor system.

Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventional therapy. Nevertheless, robots have value in reducing the manual effort required for physical therapists to provide high-intensity, high-dose interventions. In most robotic systems, therapists remain outside the control loop to act as high-level supervisors, selecting and initiating robot control algorithms to achieve a therapeutic goal. The low-level physical interactions between the robot and the patient are handled by adaptive algorithms that can provide progressive therapy. In this perspective, we examine the physical therapist's role in the control of rehabilitation robotics and whether embedding therapists in lower-level robot control loops could enhance rehabilitation outcomes. We discuss how the features of many automated robotic systems, which can provide repeatable patterns of physical interaction, may work against the goal of driving neuroplastic changes that promote retention and generalization of sensorimotor learning in patients. We highlight the benefits and limitations of letting therapists physically interact with patients through online control of robotic rehabilitation systems, and explore the concept of trust in human-robot interaction as it applies to patient-robot-therapist relationships. We conclude by highlighting several open questions to guide the future of therapist-in-the-loop rehabilitation robotics, including how much control to give therapists and possible approaches for having the robotic system learn from therapist-patient interactions.

Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.

Transcranial magnetic stimulation (TMS) is often applied to the motor cortex to stimulate a collection of motor evoked potentials (MEPs) in groups of peripheral muscles. The causal interface between TMS and MEP is the selective activation of the neurons in the motor cortex; moving the TMS ‘spot’ around over the motor cortex causes different MEP responses. A question of interest is whether a collection of MEP responses can be used to identify the stimulated locations on the cortex, which could potentially be used to then place the TMS coil to produce chosen sets of MEPs. In this work we leverage our previous report on a 3D convolutional neural network (CNN) architecture that predicted MEPs from the induced electric field, to tackle an inverse imaging task in which we start with the MEPs and estimate the stimulated regions on the motor cortex. We present and evaluate five different inverse imaging CNN architectures, both conventional and variational, in terms of several measures of reconstruction accuracy. We found that one architecture, which we denote as M2M-InvNet, consistently achieved the best performance.

This study examines longitudinal data of subjects initially examined in the early subacute period of recovery following a stroke with a test of reach to grasp (RTG) kinematics in an attempt to identify changes in movement patterns during the period of heightened neural recovery following a stroke. Subjects (n=8) were a convenience sample of persons with stroke that participated in an intervention trial. Baseline Upper Extremity Fugl Meyer Assessment (UEFMA) scores ranged between 31 and 52 and ages were between 49 and 83. The UEFMA and RTG test were collected prior to intervention, immediately after the intervention (approximately 18 days later post baseline) and one month after the intervention. RTG data for the uninvolved UE was collected at the one-month session. Subjects reached for objects placed on a table 10 cm from their sternums, picking them up and placing them on a target 30 cm from their acromioclavicular joints. Data was collected using an optical motion capture system. Active makers were placed on each fingertip, metacarpophalangeal, and proximal interphalangeal joint. Four additional passive markers were placed on the dorsum of the hand, the elbow, the shoulder, and the sternum. Subjects demonstrated statistically significant improvements in reaching duration, reaching trajectory smoothness, time after peak velocity and peak grip aperture. All of these measures correlated significantly with improvements in UEFMA. CLINICAL RELEVANCE—: Kinematic measures of reaching and grasping collected early in the subacute period of recovery from stroke may offer insight into specific aspects of the recovery of upper extremity motor function that differ from the information gleaned from clinical scales.

Transcranial Magnetic Stimulation (TMS) can be used to map cortical motor topography by spatially sampling the sensorimotor cortex while recording Motor Evoked Potentials (MEP) with surface electromyography (EMG). Traditional sampling strategies are time-consuming and inefficient, as they ignore the fact that responsive sites are typically sparse and highly spatially correlated. An alternative approach, commonly employed when TMS mapping is used for presurgical planning, is to leverage the expertise of the coil operator to use MEPs elicited by previous stimuli as feedback to decide which loci to stimulate next. In this paper, we propose to automatically infer optimal future stimulus loci using active learning Gaussian Process-based sampling in place of user expertise. We first compare the user-guided (USRG) method to the traditional grid selection method and randomized sampling to verify that the USRG approach has superior performance. We then compare several novel active Gaussian Process (GP) strategies with the USRG approach. Experimental results using real data show that, as expected, the USRG method is superior to the grid and random approach in both time efficiency and MEP map accuracy. We also found that an active warped GP entropy and a GP random-based strategy performed equally as well as, or even better than, the USRG method. These methods were completely automatic, and succeeded in efficiently sampling the regions in which the MEP response variations are largely confined. This work provides the foundation for highly efficient, fully automatized TMS mapping, especially when considered in the context of advances in robotic coil operation.

Predictive processing is emerging as a common computational hypothesis to account for diverse psychological functions subserved by a brain, providing a systems-level framework for characterizing structure-function relationships of its distinct substructures. Here, we contribute to this framework by examining gradients of functional connectivity as a low dimensional spatial representation of functional variation in the brain and demonstrating their computational implications for predictive processing. Specifically, we investigated functional connectivity gradients in the cerebral cortex, the cerebellum, and the hippocampus using resting-state functional MRI data collected from large samples of healthy young adults. We then evaluated the degree to which these structures share common principles of functional organization by assessing the correspondence of their gradients. We show that the organizing principles of these structures primarily follow two functional gradients consistent with the existing hierarchical accounts of predictive processing: A model-error gradient that describes the flow of prediction and prediction error signals, and a model-precision gradient that differentiates regions involved in the representation and attentional modulation of such signals in the cerebral cortex. Using these gradients, we also demonstrated triangulation of functional connectivity involving distinct subregions of the three structures, which allows characterization of distinct ways in which these structures functionally interact with each other, possibly subserving unique and complementary aspects of predictive processing. These findings support the viability of computational hypotheses about the functional relationships between the cerebral cortex, the cerebellum, and the hippocampus that may be instrumental for understanding the brain’s dynamics within its large-scale predictive architecture.

Handedness has been associated with behavioral asymmetries between limbs that suggest specialized function of dominant and non-dominant hand. Whether patterns of muscle co-activation, representing muscle synergies, also differ between the limbs remains an open question. Previous investigations of proximal upper limb muscle synergies have reported little evidence of limb asymmetry; however, whether the same is true of the distal upper limb and hand remains unknown. This study compared forearm and hand muscle synergies between the dominant and non-dominant limb of left-handed and right-handed participants. Participants formed their hands into the postures of the American Sign Language (ASL) alphabet, while EMG was recorded from hand and forearm muscles. Muscle synergies were extracted for each limb individually by applying non-negative-matrix-factorization (NMF). Extracted synergies were compared between limbs for each individual, and between individuals to assess within and across participant differences. Results indicate no difference between the limbs for individuals, but differences in limb synergies at the population level. Left limb synergies were found to be more similar than right limb synergies across left- and right-handed individuals. Synergies of the left hand of left dominant individuals were found to have greater population level similarity than the other limbs tested. Results are interpreted with respect to known differences in the neuroanatomy and neurophysiology of proximal and distal upper limb motor control. Implications for skill training in sports requiring dexterous control of the hand are discussed.

Introduction: Innovative motor therapies have attempted to reduce upper extremity impairment after stroke but have not made substantial improvement as over 50% of people post-stroke continue to have sensorimotor deficits affecting their self-care and participation in daily activities. Intervention studies have focused on the role of increased dosing, however recent studies have indicated that timing of rehabilitation interventions may be as important as dosing and importantly, that dosing and timing interact in mediating effectiveness. This study is designed to empirically test dosing and timing.Methods and Analysis: In this single-blinded, interventional study, subjects will be stratified on two dimensions, impairment level (Fugl-Meyer Upper Extremity Assessment (FM) and presence or absence of Motor Evoked Potentials (MEPs) as follows; (1) Severe, FM score 10–19, MEP+, (2) Severe, FM score 10–19, MEP–, (3) Moderate, FM score 20–49, MEP+, (4) Moderate, FM score 20–49, MEP–. Subjects not eligible for TMS will be assigned to either group 2 (if severe) or group 3 (if moderate). Stratified block randomization will then be used to achieve a balanced assignment. Early Robotic/VR Therapy (EVR) experimental group will receive in-patient usual care therapy plus an extra 10 h of intensive upper extremity therapy focusing on the hand using robotically facilitated rehabilitation interventions presented in virtual environments and initiated 5–30 days post-stroke. Delayed Robotic/VR Therapy (DVR) experimental group will receive the same intervention but initiated 30–60 days post-stroke. Dose-matched usual care group (DMUC) will receive an extra 10 h of usual care initiated 5–30 days post-stroke. Usual Care Group (UC) will receive the usual amount of physical/occupational therapy.Outcomes: There are clinical, neurophysiological, and kinematic/kinetic measures, plus measures of daily arm use and quality of life. Primary outcome is the Action Research Arm Test (ARAT) measured at 4 months post-stroke.Discussion: Outcome measures will be assessed to determine whether there is an early time period in which rehabilitation will be most effective, and whether there is a difference in the recapture of premorbid patterns of movement vs. the development of an efficient, but compensatory movement strategy.Ethical Considerations: The IRBs of New Jersey Institute of Technology, Rutgers University, Northeastern University, and Kessler Foundation reviewed and approved all study protocols. Study was registered in https://ClinicalTrials.gov (NCT03569059) prior to recruitment. Dissemination will include submission to peer-reviewed journals and professional presentations.

Current knowledge of coordinated motor control of multiple muscles is derived primarily from invasive stimulation-recording techniques in animal models. Similar studies are not generally feasible in humans, so a modeling framework is needed to facilitate knowledge transfer from animal studies. We describe such a framework that uses a deep neural network model to map finite element simulation of transcranial magnetic stimulation induced electric fields (E-fields) in motor cortex to recordings of multi-muscle activation. Critically, we show that model generalization is improved when we incorporate empirically derived physiological models for E-field to neuron firing rate and low-dimensional control via muscle synergies.

Virtual reality (VR) has garnered much interest as a training environment for motor skill acquisition, including for neurological rehabilitation of upper extremities. While the focus has been on gross upper limb motion, VR applications that involve reaching for, and interacting with, virtual objects are growing. The absence of true haptics in VR when it comes to hand-object interactions raises a fundamentally important question: can haptic-free immersive virtual environments (hf-VEs) support naturalistic coordination of reach-to-grasp movements? This issue has been grossly understudied, and yet is of significant importance in the development and application of VR across a number of sectors. In a previous study (Furmanek et al. 2019), we reported that reach-to-grasp movements are similarly coordinated in both the physical environment (PE) and hf-VE. The most noteworthy difference was that the closure phase—which begins at maximum aperture and lasts through the end of the movement—was longer in hf-VE than in PE, suggesting that different control laws might govern the initiation of closure between the two environments. To do so, we reanalyzed data from Furmanek et al. (2019), in which the participants reached to grasp three differently sized physical objects, and matching 3D virtual object renderings, placed at three different locations. Our analysis revealed two key findings pertaining to the initiation of closure in PE and hf-VE. First, the respective control laws governing the initiation of aperture closure in PE and hf-VE both included state estimates of transport velocity and acceleration, supporting a general unified control policy for implementing reach-to-grasp across physical and virtual environments. Second, aperture was less informative to the control law in hf-VE. We suggest that the latter was likely because transport velocity at closure onset and aperture at closure onset were less independent in hf-VE than in PE, ultimately resulting in aperture at closure onset having a weaker influence on the initiation of closure. In this way, the excess time and muscular effort needed to actively bring the fingers to a stop at the interface of a virtual object was factored into the control law governing the initiation of closure in hf-VE. Critically, this control law remained applicable, albeit with different weights in hf-VE, despite the absence of terminal haptic feedback and potential perceptual differences.

One important application of transcranial magnetic stimulation (TMS) is to map cortical motor topography by spatially sampling the motor cortex, and recording motor evoked potentials (MEP) with surface electromyography. Standard approaches to TMS mapping involve repetitive stimulations at different loci spaced on a (typically 1 cm) grid on the scalp. These mappings strategies are time consuming and responsive sites are typically sparse. Furthermore, the long time scale prevents measurement of transient cortical changes, and is poorly tolerated in clinical populations. An alternative approach involves using the TMS mapper expertise to exploit the map's sparsity through the use of feedback of MEPs to decide which loci to stimulate. In this investigation, we propose a novel active learning method to automatically infer optimal future stimulus loci in place of user expertise. Specifically, we propose an active Gaussian Process (GP) strategy with loci selection criteria such as entropy and mutual information (MI). The proposed method twists the usual entropy- and MI-based selection criteria by modeling the estimated MEP field, i.e., the GP mean, as a Gaussian random variable itself. By doing so, we include MEP amplitudes in the loci selection criteria which would be otherwise completely independent of the MEP values. Experimental results using real data shows that the proposed strategy can greatly outperform competing methods when the MEP variations are mostly confined in a sub-region of the space.

Background There is conflict regarding the benefits of greater amounts of intensive upper limb rehabilitation in the early period post-stroke. This study was conducted to test the feasibility of providing intensive therapy during the early period post-stroke and to develop a randomized control trial that is currently in process. Specifically, the study investigated whether an additional 8 h of specialized, intensive (200–300 separate hand or arm movements per hour) virtual reality (VR)/robotic based upper limb training introduced within 1-month post-stroke resulted in greater improvement in impairment and behavior, and distinct changes in cortical reorganization measured via Transcranial Magnetic Stimulation (TMS), compared to that of a control group. Methods Seven subjects received 8–1 h sessions of upper limb VR/robotic training in addition to their inpatient therapy (PT, OT, ST). Six subjects only received their inpatient therapy. All were tested on measures of impairment [Upper Extremity Fugl-Meyer Assessment (UEFMA), Wrist AROM, Maximum Pinch Force], behavior [Wolf Motor Function Test (WMFT)], and also received TMS mapping until 6 months post training. ANOVAs were conducted to measure differences between groups across time for all outcome measures. Associations between changes in ipsilesional cortical maps during the early period of enhanced neuroplasticity and long-term changes in upper limb impairment and behavior measures were evaluated. Results The VR/robotic group made significantly greater improvements on UEFMA and Wrist AROM scores compared to the usual care group. There was also less variability in the association between changes in the First Dorsal Interosseus (FDI) muscle map area and WMFT and Maximum Force change scores for the VR/robotic group. Conclusions An additional 8 h of intensive VR/robotic based upper limb training initiated within the first month post-stroke may promote greater gains in impairment compared to usual care alone. Importantly, the data presented demonstrated the feasibility of conducting this intervention and multiple outcome measures (impairment, behavioral, neurophysiological) in the early period post-stroke.

Transcranial alternating current stimulation (tACS) is a noninvasive method used to modulate activity of superficial brain regions. Deeper and more steerable stimulation could potentially be achieved using transcranial temporal interference stimulation (tTIS): two high-frequency alternating fields interact to produce a wave with an envelope frequency in the range thought to modulate neural activity. Promising initial results have been reported for experiments with mice. In this study we aim to better understand the electric fields produced with tTIS and examine its prospects in humans through simulations with murine and human head models. A murine head finite element model was used to simulate previously published experiments of tTIS in mice. With a total current of 0.776 mA, tTIS electric field strengths up to 383 V/m were reached in the modeled mouse brain, affirming experimental results indicating that suprathreshold stimulation is possible in mice. Using a detailed anisotropic human head model, tTIS was simulated with systematically varied electrode configurations and input currents to investigate how these parameters influence the electric fields. An exhaustive search with 88 electrode locations covering the entire head (146M current patterns) was employed to optimize tTIS for target field strength and focality. In all analyses, we investigated maximal effects and effects along the predominant orientation of local neurons. Our results showed that it was possible to steer the peak tTIS field by manipulating the relative strength of the two input fields. Deep brain areas received field strengths similar to conventional tACS, but with less stimulation in superficial areas. Maximum field strengths in the human model were much lower than in the murine model, too low to expect direct stimulation effects. While field strengths from tACS were slightly higher, our results suggest that tTIS is capable of producing more focal fields and allows for better steerability. Finally, we present optimal four-electrode current patterns to maximize tTIS in regions of the pallidum (0.37 V/m), hippocampus (0.24 V/m) and motor cortex (0.57 V/m).

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) provides a direct means of assessing focal and distributed cortical behavior such as excitation/inhibition, intrinsic oscillatory activity and connectivity. However, TMS-EEG poses a number of technical challenges, foremost of which is removal of stimulation-induced artifacts that are several orders of magnitude larger than the neural signals of interest and typically obscure critical early neural responses to the stimulation. Here we describe a non-linear non-causal neural network predictor, built using a Gated Recurrent Unit architecture, and demonstrate its use to remove TMS artifacts from EEG recorded on a phantom, as well as real EEG synthetically contaminated by artifacts from the phantom experiment. Our results indicate that this artifact removal algorithm may decontaminate EEG signals as early as 6ms following stimulation. Given this result we discuss the future development of neural network based predictors for TMS artifact rejection.

Explore the potential benefits of using priming methods prior to an active hand task in the acute phase post-stroke in persons with severe upper extremity hemiparesis.Five individuals were trained using priming techniques including virtual reality (VR) based visual mirror feedback and contralaterally controlled passive movement strategies prior to training with an active pinch force modulation task. Clinical, kinetic, and neurophysiological measurements were taken pre and post the training period. Clinical measures were taken at six months post training.The two priming simulations and active training were well tolerated early after stroke. Priming effects were suggested by increased maximal pinch force immediately after visual and movement based priming. Despite having no clinically observable movement distally, the subjects were able to volitionally coordinate isometric force and muscle activity (EMG) in a pinch tracing task. The Root Mean Square Error (RMSE) of force during the pinch trace task gradually decreased over the training period suggesting learning may have occurred. Changes in motor cortical neurophysiology were seen in the unaffected hemisphere using Transcranial Magnetic Stimulation (TMS) mapping. Significant improvements in motor recovery as measured by the Action Research Arm Test (ARAT) and the Upper Extremity Fugl Meyer Assessment (UEFMA) were demonstrated at six months post training by three of the five subjects.This study suggests that an early hand-based intervention using visual and movement based priming activities and a scaled motor task allows participation by persons without the motor control required for traditionally presented rehabilitation and testing. Implications for Rehabilitation Rehabilitation of individuals with severely paretic upper extremities after stroke is challenging due to limited movement capacity and few options for therapeutic training. Long-term functional recovery of the arm after stroke depends on early return of active hand control, establishing a need for acute training methods focused distally. This study demonstrates the feasibility of an early hand-based intervention using virtual reality based priming and scaled motor activities which can allow for participation by persons without the motor control required for traditionally presented rehabilitation and testing.

Background Virtual reality (VR) offers unprecedented opportunity as a scientific tool to study visuomotor interactions, training, and rehabilitation applications. However, it remains unclear if haptic-free hand-object interactions in a virtual environment (VE) may differ from those performed in the physical environment (PE). We therefore sought to establish if the coordination structure between the transport and grasp components remain similar whether a reach-to-grasp movement is performed in PE and VE. Method Reach-to-grasp kinematics were examined in 13 healthy right-handed young adults. Subjects were instructed to reach-to-grasp-to-lift three differently sized rectangular objects located at three different distances from the starting position. Object size and location were matched between the two environments. Contact with the virtual objects was based on a custom collision detection algorithm. Differences between the environments were evaluated by comparing movement kinematics of the transport and grasp components. Results Correlation coefficients, and the slope of the regression lines, between the reach and grasp components were similar for the two environments. Likewise, the kinematic profiles of the transport velocity and grasp aperture were strongly correlated across the two environments. A rmANOVA further identified some similarities and differences in the movement kinematics between the two environments - most prominently that the closure phase of reach-to-grasp movement was prolonged when movements were performed in VE. Conclusions Reach-to-grasp movement patterns performed in a VE showed both similarities and specific differences compared to those performed in PE. Additionally, we demonstrate a novel approach for parsing the reach-to-grasp movement into three phases- initiation, shaping, closure- based on established kinematic variables, and demonstrate that the differences in performance between the environments are attributed to the closure phase. We discuss this in the context of how collision detection parameters may modify hand-object interactions in VE. Our study shows that haptic-free VE may be a useful platform to study reach-to-grasp movements, with potential implications for haptic-free VR in neurorehabilitation. Electronic supplementary material The online version of this article (10.1186/s12984-019-0525-9) contains supplementary material, which is available to authorized users.

Current research shows promise in restoring impaired hand function after stroke with the help of Mirror Visual Feedback (MVF), putatively by facilitating activation of sensorimotor areas of the brain ipsilateral to the moving limb. However, the MVF related clinical effects show variability across studies. MVF tasks that have been used place varying amounts of visuomotor demand on one’s ability to complete the task. Therefore, we ask here whether varying visuomotor demand during MVF may translate to differences in brain activation patterns. If so, we argue that this may provide a mechanistic explanation for variable clinical effects. To address this, we used functional magnetic resonance imaging (fMRI) to investigate the interaction of target directed movement and MVF on the activation of, and functional connectivity between, regions within the visuomotor network. In an event-related fMRI design, twenty healthy subjects performed finger flexion movements using their dominant right hand, with feedback presented in a virtual reality (VR) environment. Visual feedback was presented in real time VR as either veridical feedback with and without a target (VT+ and VT-, respectively), or MVF with and without a target (MT+ and MT-, respectively). fMRI contrasts revealed predominantly activation in the ipsilateral intraparietal sulcus for the main effect of MVF and bilateral superior parietal activation for the main effect of target. Importantly, we noted significant and robust activation lateralized to the ipsilateral parietal cortex alone in the MT+ contrast with respect to the other conditions. This suggests that combining MVF with targeted movements performed using the right hand may redirect enhanced bilateral parietal activation due to target presentation to the ipsilateral cortex. Moreover, functional connectivity analysis revealed that the interaction between the ipsilateral parietal lobe and the motor cortex was significantly greater during target-directed movements with mirror feedback compared to veridical feedback. These findings provide a normative basis to investigate the integrity of these networks in patient populations. Identification of the brain regions involved in target directed movement with MVF in stroke may have important implications for optimal delivery of MVF based therapy.

Paired associative stimulation (PAS) has been shown to increase corticospinal excitability (CSE) providing a promising adjuvant therapeutic approach for stroke. Combining PAS with movement of the stimulated limb may further increase enhancement of CSE, however, individuals with moderate to severe stroke may not be able to engage in the necessary repetitive voluntary movements of the paretic limb. The objective of this study was to investigate the feasibility of contralaterally coordinated PAS (ccPAS) applied to the resting hand extensors during fast extension of the contralateral hand. A potential dependency of CSE modulation on the phase of the movement of the opposite hand was evaluated. Eleven participants each completed three session: PAS applied to the resting right hand during the preparation phase of the extension of the contralateral (left) hand; PAS applied during the execution phase of the left hand extension; and PAS applied with both hands at rest. Motor evoked potentials (MEPs) were evoked from the right extensor digitorum communis (EDC) and flexor digitorum superficialis (FDS) muscles prior and immediately after each session. PAS delivered during the muscle contraction of the left hand and PAS delivered at rest both increased the MEP amplitude in the right EDC. PAS delivered before the left hand movement onset led to a decrease in the MEP amplitude measured in the right EDC muscle. We conclude that PAS induced bidirectional changes in the amplitude of MEPs that were dependent on the phase of the movement of the opposite hand.

Transcranial magnetic stimulation (TMS) induced motor evoked potentials (MEPs) are an established proxy of corticospinal excitability. As a binary measure, the presence (MEP+) or absence (MEP-) of ipsilesional hemisphere MEPs early following stroke is a robust indicator of long-term recovery, however this measure does not provide information about spatial cortical reorganization. MEPs have been systematically acquired over the sensorimotor cortex to “map” motor topography. In this investigation we compared the degree to which functional improvements resulting from early (

Background Center of pressure measured during gait can provide information about underlying control mechanisms and the efficacy of a foot drop stimulator. This investigation evaluated changes in center of pressure displacement in individuals with stroke with and without a foot drop stimulator. Methods Individuals with stroke-related foot drop (n = 11) using a foot drop stimulator and healthy controls (n = 11). Walking speed and bilateral center of pressure variables: 1) net displacement; 2) position and maximum displacement; and 3) mean velocity during walking. Findings On the affected limb with the foot drop stimulator as compared to the affected limb without the foot drop stimulator: 1) increased anterior/posterior maximum center of pressure excursion 8% during stance; 2) center of pressure at initial contact was 6% more posterior; 3) medial/lateral mean, maximum and minimum center of pressure position during stance all significantly decreased; 4) anterior/posterior net displacement increased during stance and single support; and 5) anterior/posterior velocity of the center of pressure increased during stance. Interpretation Individuals with stroke using a foot drop stimulator contacted the ground more posterior at initial contact and utilized more of the anterior/posterior plantar surface of the foot on the affected limb during stance. With the foot drop stimulator there was a shift in center of pressure toward the medial side possibly indicating an improvement in equinovarus gait where there is a tendency to load the lateral foot throughout stance. For individuals with stroke a foot drop stimulator can improve displacement of the center of pressure which indicates improved forward progression and stability during walking.

Reliability and validity study. This study investigates the responsiveness and reliability of the brain motor control assessment (BMCA) as a standardized neurophysiological assessment tool to: (i) characterize trunk neural activity in neurologically-intact controls; (ii) measure and quantify neurorecovery of trunk after spinal cord injury (SCI). Kessler Foundation Research Center, West Orange, NJ. A standardized BMCA protocol was performed to measure surface electromyography (sEMG) recordings for seven bilateral trunk muscles on 15 able-bodied controls during six maneuvers (inhalation, exhalation, neck flexion, jendrassik, unilateral grip). Additionally, sEMG recordings were analyzed for one chronic SCI individual before electrical stimulation (ES), after ES of the lower extremities while supine, and after active stand training using body-weight support with bilateral ES. sEMG recordings were collected on bilateral erector spinae, internal and external obliques, upper and middle trapezius, biceps and triceps. For each maneuver a voluntary response index was calculated: incorporating the magnitude of sEMG signal and a similarity index (SI), which quantifies the distribution of activity across all muscles. Among all maneuvers, the SI presented reproducible assessment of trunk-motor function within (ICC: 0.860–0.997) and among (P⩾0.22) able-bodied individuals. In addition, potential changes were measured in a chronic SCI individual after undergoing two intensive ES protocols. The BMCA provides reproducible characterization of trunk activity in able-bodied individuals, lending credence for its use in neurophysiological assessment of motor control. Additionally, the BMCA as an assessment tool to measure neurorecovery in an individual with chronic SCI after intense ES interventions was demonstrated.

Background Functional Electrical Stimulation (FES) applied through a foot drop stimulator (FDS) is a rehabilitation intervention that can stimulate the common peroneal nerve to provide dorsiflexion at the correct timing during gait. Objective To determine if FES applied to the peroneal nerve during walking through a FDS would effectively retrain the electromyographic temporal activation of the tibialis anterior in individuals with stroke. Methods Surface electromyography (EMG) were collected bilaterally from the tibialis anterior (TA) while participants (n = 4) walked with and without the FDS at baseline and 4 weeks. Comparisons were made between stimulation timing and EMG activation timing to produce a burst duration similarity index (BDSI). Results At baseline, participants displayed variable temporal activation of the TA. At 4 weeks, TA activation during walking without the FDS more closely resembled the pre-programmed FDS timing demonstrated by an increase in BDSI scores in all participants (P = 0.05). Conclusions Continuous use of FDS during a task specific movement can re-train the neuromuscular system. After 4 weeks of utilization the FDS trained the TA to replicate the programmed temporal activation patterns. These findings begin to establish the FDS as a rehabilitation intervention that may facilitate recovery rather than just compensate for stroke related gait impairments due to foot drop.

This review discusses challenges faced by clinicians and researchers when measuring ambulation in individuals with central neurologic disorders within 3 distinct environments: clinical, laboratory, and community. Even the most robust measure of ambulation is affected by the environment in which it is implemented and by the clinical or research question and the specificity of the hypothesis being investigated. The ability to accurately measure ambulation (one of the most important metrics used to show transition into a community environment) is essential to measure treatment effectiveness and rehabilitation outcomes in populations with central neurologic disorders.

Mirror visual feedback (MVF) training is a promising technique to promote activation in the lesioned hemisphere following stroke, and aid recovery. However, current outcomes of MVF training are mixed, in part, due to variability in the task undertaken during MVF. The present study investigated the hypothesis that movements directed toward visual targets may enhance MVF modulation of motor cortex (M1) excitability ipsilateral to the trained hand compared to movements without visual targets. Ten healthy subjects participated in a 2 × 2 factorial design in which feedback (veridical, mirror) and presence of a visual target (target present, target absent) for a right index-finger flexion task were systematically manipulated in a virtual environment. To measure M1 excitability, transcranial magnetic stimulation (TMS) was applied to the hemisphere ipsilateral to the trained hand to elicit motor evoked potentials (MEPs) in the untrained first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles at rest prior to and following each of four 2-min blocks of 30 movements (B1–B4). Targeted movement kinematics without visual feedback was measured before and after training to assess learning and transfer. FDI MEPs were decreased in B1 and B2 when movements were made with veridical feedback and visual targets were absent. FDI MEPs were decreased in B2 and B3 when movements were made with mirror feedback and visual targets were absent. FDI MEPs were increased in B3 when movements were made with mirror feedback and visual targets were present. Significant MEP changes were not present for the uninvolved ADM, suggesting a task-specific effect. Analysis of kinematics revealed learning occurred in visual target-directed conditions, but transfer was not sensitive to mirror feedback. Results are discussed with respect to current theoretical mechanisms underlying MVF-induced changes in ipsilateral excitability.

The goal of this paper is to demonstrate a novel approach that combines Empirical Mode Decomposition (EMD) with Notch filtering to remove the electrical stimulation (ES) artifact from surface electromyogram (EMG) data for interpretation of muscle responses during functional electrical stimulation (FES) experiments. FES was applied to the rectus femoris (RF) muscle unilaterally of six able bodied (AB) and one individual with spinal cord injury (SCI). Each trial consisted of three repetitions of ES. We hypothesized that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic mode functions (IMFs) which can be further used to isolate electrical stimulation (ES) artifact. A basic EMD algorithm was used to decompose the EMG signals collected during FES into IMFs for each repetition separately. IMFs most contaminated by ES were identified based on the standard deviation (SD) of each IMF. Each artifact IMF was Notch filtered to filter ES harmonics and added to remaining IMFs containing pure EMG data to get a version of a filtered EMG signal. Of all such versions of filtered signals generated from each artifact IMF, the one with maximum signal to noise ratio (SNR) was chosen as the final output. The validity of the filtered signal was assessed by quantitative metrics, 1) root mean squared error (RMSE) and signal to noise (SNR) ratio values obtained by comparing a clean EMG and EMD-Notch filtered signal from the combination of simulated ES and clean EMG and, 2) using EMG-force correlation analysis on the data collected from AB individuals. Finally, the potential applicability of this algorithm on a neurologically impaired population was shown by applying the algorithm on EMG data collected from an individual with SCI. EMD combined with Notch filtering successfully extracted the EMG signal buried under ES artifact. Filtering performance was validated by smaller RMSE values and greater SNR post filtering. The amplitude values of the filtered EMG signal were seen to be consistent for three repetitions of ES and there was no significant difference among the repetition for all subjects. For the individual with a SCI the algorithm was shown to successfully isolate the underlying bursts of muscle activations during FES. The data driven nature of EMD algorithm and its ability to act as a filter bank at different bandwidths make this method extremely suitable for dissecting ES induced EMG into IMFs. Such IMFs clearly show the presence of ES artifact at different intensities as well as pure artifact free EMG. This allows the application of Notch filters to IMFs containing ES artifact to further isolate the EMG. As a result of such stepwise approach, the extraction of EMG is achieved with minimal data loss. This study provides a unique approach to dissect and interpret the EMG signal during FES applications.

Current service delivery models limit treatment time and length of hospital stay during the period of post-ischemic heightened neuronal plasticity when intensive training may optimally affect recovery. Prioritization for rehabilitation of independence in transfers and ambulation, negatively impacts the provision of intensive hand and upper extremity therapy. Our pilot data show that we are able to integrate intensive, targeted hand therapy that uses robotics and a library of gaming activities into the routine of an acute rehabilitation setting. Our system has been specifically designed to deliver hand training when motion and strength are limited. The system uses adaptive algorithms to drive individual finger movement, gain adaptation and workspace modification, and haptic and visual feedback from mirrored movements. The data establishes a foundation for a future clinical trial to investigate the potential benefits of robot-assisted gaming during the early phase of recovery.

Mirror visual feedback (MVF) is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical) or opposite (mirror) hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional) action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with non-invasive brain stimulation as a means of potentiating the effects of mirror training.

Identifying and understanding the changes in transfer of momentum that are directly affected by orthotic intervention are significant factors related to the improvement of mobility in individuals with hemiplegia.The purpose of this investigation was to use a novel analysis technique to objectively measure weight transfer during double support (DS) in healthy individuals and individuals with hemiplegia secondary to stroke with and without an ankle foot orthosis.Prospective, Repeated measures, case-controlled trial.Participants included 25 adults with stroke-related hemiplegia6 months using a prescribed ankle foot orthosis and 12 age-matched healthy controls. Main outcome measures included the weight transfer point timing (WTP, %DS), maximum total force timing (MTF, %DS), timing difference between WTP and MTF (MTF-WTP, %DS) and the linearity of loading (LOL, R(2)) during the DS phase of the gait cycle.The WTP and LOL were significantly different between conditions with and without the ankle foot orthosis for the affected and unaffected limb in post-stroke individuals, p ≤ 0.01. The MTF and difference in timing between MTF-WTP were significantly different during affected limb loading with and without the ankle foot orthosis in the stroke group, p ≤ 0.0001 and p = 0.03, respectively. MTF, MTF-WTP and LOL were significantly different between individuals with stroke (during affected limb loading) and healthy controls (during right limb loading).This research established a systematic method for analysing weight transfer during walking to evaluate the effect of an ankle foot orthosis on loading during double support in hemiplegic gait. This novel method can be used to elucidate biomechanical mechanisms behind orthosis-mediated changes in gait patterns and quantify functional mobility outcomes in rehabilitation.This novel approach to orthotic assessment will provide the clinician with needed objective evidence to select the most effective orthotic intervention to maximize functional recovery for individuals with hemiplegia secondary to stroke.

Replanning ongoing movements following perturbations requires the accurate and immediate estimation of the motor response based on sensory input. Previous studies have used transcranial magnetic stimulation (TMS) in humans to demonstrate the participation of the anterior intraparietal sulcus (aIPS) and ventral premotor cortex (PMv) in visually mediated state estimation for grasping. Here, we test the role of parietofrontal circuits in processing the corrective responses to haptic perturbations of the finger during prehension. Subjects reached to grasp an object while having to compensate for a novel and unpredictable haptic perturbation of finger extension. TMS-based transient disruptions to the PMv and aIPS were delivered 0, 50, or 100 ms after the perturbation. TMS to the PMv delivered 50 ms after the perturbation (but not 0 or 100 ms, or in unperturbed trials) led to an overestimation of grasp aperture. No effects on grasp aperture were noted for the aIPS. Our results indicate that the PMv (but not aIPS) is involved in the deployment of the compensatory response in the presence of haptic perturbations during prehension. Our data also identify the time window of neural processing in the PMv when reprogramming occurs to be 50–100 ms following the perturbation onset.

The integrity of the corticospinal system is an important biomarker for recovery from stroke. However, mapping the topography of the corticospinal system in subacute stroke is not trivial and how it changes over the course of recovery is poorly understood. We intend to use a transcranial magnetic stimulation (TMS) based mapping approach to quantify the topographic landscape of corticospinal activation in the ipsi- and contralesional sensorimotor cortices in the subacute and chronic phase of stroke. Mapping was conducted before (PRE) and after (POST), intervention in 10 chronic subjects and 8 subacute subjects. Reorganization was quantified in a unique way by dissociating reorganization attributed to changes in the expanse (area) of the sensorimotor territory, from that attributed to changes in the robustness of the activation (amplitude). In doing so, we observed differences in reorganization in the subacute and chronic stages indicating that recovery in different stages may not be guided by similar neurophysiological mechanisms of neuroplasticity.

Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.

article i nfo Background: Changes in impulse during the first rocker (braking force) and third rocker (propulsion force) may affect changes in gait speed after orthotic intervention. The purpose of this investigation was to objectively measure changes in impulse during double support and correlate those findings to changes in gait speed with and without ankle foot orthosis in individuals with hemiplegia. Methods: Fifteen adults with stroke-related hemiplegia walked with and without ankle foot orthosis while foot pressure data was collected bilaterally. Outcome measures included: gait cycle time (s), mean force (N), and impulse (Ns) in the wholefoot, hindfoot, forefoot, and toe box during initial double support and terminal double support. Findings: Time significantly decreased during the entire gait cycle, initial double support, and terminal double support, with the ankle foot orthosis. During initial double support, affected limb impulse significantly decreased with the ankle foot orthosis in the wholefoot (P=0.016), and hindfoot (P=0.006), and hindfoot impulse % change and gait speed % change were significantly correlated (P=0.007). During terminal double support, affected limb impulse was not significantly different in the wholefoot or forefoot and these changes were not significantly correlated to gait speed. Interpretation: Previous research found that orthotics increase gait speed in individuals with hemiplegia. This research suggests that the increase in speed is not due to increased propulsive forces at the end of terminal double support, but due to decreased braking forces during initial double support. Therefore, the orthosis preserved the first ankle rocker and provided a more efficient weight acceptance which positively affected gait speed.

Kwarciak AM, Sisto SA, Yarossi M, Price R, Komaroff E, Boninger ML. Redefining the manual wheelchair stroke cycle: identification and impact of nonpropulsive pushrim contact. Objectives To create a comprehensive definition of the manual wheelchair stroke cycle, which includes multiple periods of pushrim contact, and to show its improved clinical benefit to wheelchair propulsion analyses. Design Cross-sectional biomechanics study. Setting Three motion analysis laboratories. Participants Persons (N=54) with paraplegia who use a manual wheelchair. Interventions Not applicable. Main Outcome Measures Pushrim forces, axle moments, and contact angles measured during wheelchair propulsion. Results Total force on the pushrim was used to define pushrim contact and positive axle moment was used to identify the included period of propulsive contact. During most strokes, periods of nonpropulsive contact existed before and after propulsive contact. Within these periods, braking moments were applied to the pushrim, resulting in negative power output, or power loss. Including nonpropulsive data decreased mean stroke moment and power. The magnitude and the angle over which braking moments and power loss occurred increased with wheel speed. Mean braking moment and power loss within the initial contact period were significantly ( P Conclusions The proposed definition of the stroke cycle provides a thorough and practical description of wheelchair propulsion. Researchers and clinicians should use this definition to understand and minimize the impact of nonpropulsive contact throughout the stroke.