Dataset Information

Invasive neurostimulation in stroke rehabilitation.

ABSTRACT: The last decade has seen a growing interest in adjuvant treatments that synergistically influence mechanisms underlying rehabilitation of paretic upper limb in stroke. One such approach is invasive neurostimulation of spared cortices at the periphery of a lesion. Studies in animals have shown that during training of paretic limb, adjuvant stimulation targeting the peri-infarct circuitry enhances mechanisms of its reorganization, generating functional advantage. Success of early animal studies and clinical reports, however, failed to translate to a phase III clinical trial. As lesions in humans are diffuse, unlike many animal models, peri-infarct circuitry may not be a feasible, or consistent target across most. Instead, alternate mechanisms, such as changing transcallosal inhibition between hemispheres, or reorganization of other viable regions in motor control, may hold greater potential. Here, we review comprehensive mechanisms of clinical recovery and factors that govern which mechanism(s) become operative when. We suggest novel approaches that take into account a patient's initial clinical-functional state, and findings from neuroimaging and neurophysiology to guide to their most suitable mechanism for ideal targeting. Further, we suggest new localization schemes, and bypass strategies that indirectly target peri-lesional circuitry, and methods that serve to counter technical and theoretical challenge in identifying and stimulating such targets at the periphery of infarcts in humans. Last, we describe how stimulation may modulate mechanisms differentially across varying phases of recovery- a temporal effect that may explain missed advantage in clinical trials and help plan for the next stage. With information presented here, future trials would effectively be able to target patient's specific mechanism(s) with invasive (or noninvasive) neurostimulation for the greatest, most consistent benefit.

SUBMITTER: Plow EB

PROVIDER: S-EPMC4121447 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Invasive neurostimulation in stroke rehabilitation.

Plow Ela B EB Machado Andre A

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 20140701 3

The last decade has seen a growing interest in adjuvant treatments that synergistically influence mechanisms underlying rehabilitation of paretic upper limb in stroke. One such approach is invasive neurostimulation of spared cortices at the periphery of a lesion. Studies in animals have shown that during training of paretic limb, adjuvant stimulation targeting the peri-infarct circuitry enhances mechanisms of its reorganization, generating functional advantage. Success of early animal studies an ...[more]

PMID: 24353109

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Project description:Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is "in vain": there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train-wait-train paradigm: if spontaneous arm use has increased in the "wait" period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided.

Project description:We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper extremity stroke rehabilitation at the home. We propose a hierarchical model for automatically segmenting stroke survivor's movements and generating training task performance assessment scores during rehabilitation. The hierarchical model fuses expert therapist knowledge-based approaches with data-driven techniques. The expert knowledge is more observable in the higher layers of the hierarchy (task and segment) and therefore more accessible to algorithms incorporating high level constraints relating to activity structure (i.e., type and order of segments per task). We utilize an HMM and a Decision Tree model to connect these high level priors to data driven analysis. The lower layers (RGB images and raw kinematics) need to be addressed primarily through data driven techniques. We use a transformer based architecture operating on low-level action features (tracking of individual body joints and objects) and a Multi-Stage Temporal Convolutional Network(MS-TCN) operating on raw RGB images. We develop a sequence combining these complimentary algorithms effectively, thus encoding the information from different layers of the movement hierarchy. Through this combination, we produce a robust segmentation and task assessment results on noisy, variable and limited data, which is characteristic of low cost video capture of rehabilitation at the home. Our proposed approach achieves 85% accuracy in per-frame labeling, 99% accuracy in segment classification and 93% accuracy in task completion assessment. Although the methodology proposed in this paper applies to upper extremity rehabilitation using the SARAH system, it can potentially be used, with minor alterations, to assist automation in many other movement rehabilitation contexts (i.e., lower extremity training for neurological accidents).

Project description:Locomotor training, including the use of body-weight support in treadmill stepping, is a physical therapy intervention used to improve recovery of the ability to walk after stroke. The effectiveness and appropriate timing of this intervention have not been established.We stratified 408 participants who had had a stroke 2 months earlier according to the extent of walking impairment--moderate (able to walk 0.4 to <0.8 m per second) or severe (able to walk <0.4 m per second)--and randomly assigned them to one of three training groups. One group received training on a treadmill with the use of body-weight support 2 months after the stroke had occurred (early locomotor training), the second group received this training 6 months after the stroke had occurred (late locomotor training), and the third group participated in an exercise program at home managed by a physical therapist 2 months after the stroke (home-exercise program). Each intervention included 36 sessions of 90 minutes each for 12 to 16 weeks. The primary outcome was the proportion of participants in each group who had an improvement in functional walking ability 1 year after the stroke.At 1 year, 52.0% of all participants had increased functional walking ability. No significant differences in improvement were found between early locomotor training and home exercise (adjusted odds ratio for the primary outcome, 0.83; 95% confidence interval [CI], 0.50 to 1.39) or between late locomotor training and home exercise (adjusted odds ratio, 1.19; 95% CI, 0.72 to 1.99). All groups had similar improvements in walking speed, motor recovery, balance, functional status, and quality of life. Neither the delay in initiating the late locomotor training nor the severity of the initial impairment affected the outcome at 1 year. Ten related serious adverse events were reported (occurring in 2.2% of participants undergoing early locomotor training, 3.5% of those undergoing late locomotor training, and 1.6% of those engaging in home exercise). As compared with the home-exercise group, each of the groups receiving locomotor training had a higher frequency of dizziness or faintness during treatment (P=0.008). Among patients with severe walking impairment, multiple falls were more common in the group receiving early locomotor training than in the other two groups (P=0.02).Locomotor training, including the use of body-weight support in stepping on a treadmill, was not shown to be superior to progressive exercise at home managed by a physical therapist. (Funded by the National Institute of Neurological Disorders and Stroke and the National Center for Medical Rehabilitation Research; LEAPS ClinicalTrials.gov number, NCT00243919.).

Dataset Information

Invasive neurostimulation in stroke rehabilitation.

Publications

Invasive neurostimulation in stroke rehabilitation.

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