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[WEB PAGE] The Use of Noninvasive Brain Stimulation, Specifically Transcranial Direct Current Stimulation After Stroke

Motor impairment is a leading cause of disability after stroke. Approaches such as noninvasive brain stimulation are being investigated to attempt to increase effectiveness of stroke rehabilitation interventions. There are several types of noninvasive brain stimulation: repetitive transcranial magnetic stimulation, transcranial direct stimulation (tDCS), transcranial alternative current stimulation, and transcranial pulsed ultrasound to name a few. Of the types of noninvasive brain stimulation, repetitive transcranial magnetic stimulation and tDCS have been most extensively tested to modulate brain activity and potentially behavior. These two techniques have distinctive modes of action. Repetitive transcranial magnetic stimulation directly stimulates neurons in the brain and, given the appropriate conditions, leads to new action potentials. On the other hand, tDCS polarizes neuronal tissue including neurons and glia modulating ongoing firing patterns. There are also differences in cost, utility, and knowledge skill required to apply tDCS and repetitive transcranial magnetic stimulation. Transcranial direct stimulation is relatively inexpensive, easy to administer, portable, and may be applied while undergoing therapy, with lasting excitability changes detectable up to 90 minutes after administration. Repetitive transcranial magnetic stimulation equipment is bulkier, expensive, technically more challenging, and a patient’s head must remain still when treatment is being applied therefore needs to be administered before or after a session of rehabilitation. Because of these differences, tDCS has been more accessible and has rapidly grew as a potential tool to be used in neurorehabilitation to facilitate retraining of activities of daily living (ADL) capacity and possibly to improve restoration of neurological function after stroke.

There are three current stimulation approaches using tDCS to modulate corticomotor regions after stroke. In anodal stimulation mode, the anode electrode is placed over the lesioned brain area and a reference electrode is applied over the contralateral orbitofrontal cortex. Anodal tDCS is placed over the ipsilesional hemisphere to improve the responses of perilesional areas to training protocols. In cathodal stimulation, the cathode electrode is placed over the nonlesioned brain area and reference electrode over the contralateral (ipsilesional) orbitofrontal cortex. This approach has been predicated on the hypothesis that the nonstroke hemisphere will be inhibited by tDCS resulting in an increased activation of the ipsilesional hemisphere due to rebalancing of a presumably abnormal interhemispheric interaction. Although some studies have shown this approach to be beneficial, the causative role of interhemispheric interaction imbalance has been recently challenged and refuted.1 Thus, if cathodal stimulation approaches are beneficial, the behavioral effect cannot be explained by a presumed correction of abnormal interhemispheric connectivity. Finally, dual tDCS approach involves simultaneous application of the anode over the ipsilesional and the cathode over the contralesional side. Here again, the intended mechanism of action is to rebalance the presumably abnormal interhemispheric interaction.

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CLINICAL QUESTIONS ADDRESSED

What is the best tDCS type and electrical configuration? What are the effects of tDCS with rehabilitation program for upper limb recovery after stroke?

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RESEARCH FINDINGS OF tDCS

This short article discusses data obtained from a network meta-analysis of randomized controlled trials and a recent meta-analysis. The network meta-analysis included 12 randomized controlled trials including 284 participants examining the effect of tDCS on ADL function in the acute, subacute, and chronic phases after stroke.2 The meta-analysis included 9 studies with 371 participants in any stage after stroke.3

The network meta-analysis found evidence of a significant moderate effect in favor of cathodal tDCS without significant effects of dual tDCS, anodal tDCS, or sham tDCS. There was no difference in safety (as assessed by dropouts and adverse events) between sham tDCS, physical rehabilitation, cathodal tDCS, dual tDCS, and anodal tDCS. Elsner in a previous review of tDCS in 2016 found an effect on improving ADL, as well as function of the arm and lower limb, muscle strength, and cognition. Thus, the findings from the most recent meta-analysis indicating cathodal that tDCS improves ADL capacity are in line with previous meta-analyses. Of note, there was no evidence of an effect of either cathodal or other tDCS stimulation approaches on upper paretic limb impairment after stroke as measured by the Fugl-Meyer scale.

A meta-analysis that included participants in any stage after the stroke showed that tDCS in conjunction with multiple sessions of rehabilitation had no significant effect over delivering therapy alone for upper limb impairment and activity after stroke. This negative finding might be due to patient’s being in an acute, subacute, or chronic stage after stroke as well as variations in the type of therapy performed paired with tDCS (ie, conventional vs. constraint-induced movement therapy vs. robot protocol).

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RECOMMENDATIONS FOR PHYSIATRIC PRACTICE

There seems to be a modest effect supporting the use of tDCS as a co-adjuvant of rehabilitation interventions to improve ADLs after stroke. Cathodal tDCS seems to be the most promising approach, especially when applied early after the stroke. However, the evidence remains preliminary and does not warrant a widespread change in clinical rehabilitation practice at this time.

There is no evidence supporting the use of tDCS to improve motor impairment (as measured by the FMS) at this point.

Importantly, tDCS remains as a very safe intervention, with no differences in safety when real vs. control tDCS is applied.

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REFERENCES

1. Xu J, Branscheidt M, Schambra H, et al: Rethinking interhemispheric imbalance as a target for stroke neurorehabilitation. Ann Neurol 2019;85:502–13

2. Elsner B, Kwakkel G, Kugler J, et al: Transcranial direct current stimulation (tDCS) for improving capacity in activities and arm function after stroke: a network meta-analysis of randomised controlled trials. J Neuroeng Rehabil 2017;14:

3. Tedesco Triccas L, Burridge J, Hughes A, et al: Multiple sessions of transcranial direct current stimulation and upper extremity rehabilitation in stroke: a review and meta-analysis. Clin Neurophysiol2016;127:946–55

via The Use of Noninvasive Brain Stimulation, Specifically Trans… : American Journal of Physical Medicine & Rehabilitation

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[ARTICLE] Searching for the optimal tDCS target for motor rehabilitation – Full Text

Abstract

Background

Transcranial direct current stimulation (tDCS) has been investigated over the years due to its short and also long-term effects on cortical excitability and neuroplasticity. Although its mechanisms to improve motor function are not fully understood, this technique has been suggested as an alternative therapeutic method for motor rehabilitation, especially those with motor function deficits. When applied to the primary motor cortex, tDCS has shown to improve motor function in healthy individuals, as well as in patients with neurological disorders. Based on its potential effects on motor recovery, identifying optimal targets for tDCS stimulation is essential to improve knowledge regarding neuromodulation as well as to advance the use of tDCS in clinical motor rehabilitation.

Methods and results

Therefore, this review discusses the existing evidence on the application of four different tDCS montages to promote and enhance motor rehabilitation: (1) anodal ipsilesional and cathodal contralesional primary motor cortex tDCS, (2) combination of central tDCS and peripheral electrical stimulation, (3) prefrontal tDCS montage and (4) cerebellar tDCS stimulation. Although there is a significant amount of data testing primary motor cortex tDCS for motor recovery, other targets and strategies have not been sufficiently tested. This review then presents the potential mechanisms and available evidence of these other tDCS strategies to promote motor recovery.

Conclusions

In spite of the large amount of data showing that tDCS is a promising adjuvant tool for motor rehabilitation, the diversity of parameters, associated with different characteristics of the clinical populations, has generated studies with heterogeneous methodologies and controversial results. The ideal montage for motor rehabilitation should be based on a patient-tailored approach that takes into account aspects related to the safety of the technique and the quality of the available evidence.

Introduction

Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique which delivers a constant electric current over the scalp to modulate cortical excitability [1,2,3]. Different montages of tDCS may induce diverse effects on brain networks, which are directly dependent on the electrodes positioning and polarity. While anodal tDCS is believed to enhance cortical excitability, cathodal tDCS diminishes the excitation of stimulated areas, and these electrodes montages define the polarity-specific effects of the stimulation [4,5,6]. Due to the effects of tDCS on modulating cortical excitability, especially when applied to the primary motor cortex [2], this method of brain stimulation has been intensively investigated for motor function improvement both in healthy subjects [78] and in various neurological pathologies [910]. Neurological conditions that may obtain benefits from the use of tDCS include Stroke [11,12,13,14], Parkinson’s disease [15], Multiple Sclerosis [1617], among others.

The mechanisms of action underlying the modulation of neuronal activity induced by tDCS are still not completely understood. However, studies have demonstrated that the electric current generated by tDCS interferes in the resting membrane potential of neuronal cells, which modulates spontaneous brain circuits activity [1,2,3]. Some studies have suggested that tDCS could have an effect on neuronal synapsis’ strength, altering the activity of NMDA and GABA receptors, thus triggering plasticity process, such as long-term potentiation (LTP) and long-term depression (LTD) [1819]. The long-term effects of tDCS are also thought to be associated to changes in protein synthesis and gene expression [2021]. Additionally, neuroimaging study showed blood flow changes following stimulation, which may be related to a direct effect of tDCS over blood flow, with an increase in oxygen supply on cortical areas and subsequent enhancement of neuronal excitability [22]. Given these mechanisms, tDCS seems to be a potential valuable tool to stimulate brain activity and plasticity following a brain damage.

The advantages of using tDCS include its low cost, ease of application, and safety. To date, there is no evidence of severe adverse events following tDCS in healthy individuals, as well as in patients with neurological conditions, such as stroke [2324]. Among the potential side effects presented after this type of stimulation, the most common ones consist of burn sensation, itching, transient skin irritation, tingling under the electrode, headache, and low intensity discomfort [25]. As serious and irreversible side effects have not been reported, tDCS is considered a relatively safe and tolerable strategy of non-invasive brain stimulation.

The modifications of physiological and clinical responses induced by tDCS are extremely variable, as this type of stimulation can induce both adaptive or maladaptive plastic changes, and a wide spectrum of tDCS parameters influence the effects of this technique. Electrodes combination, montage and shape can easily interfere in the enhancement or inhibition of cortical excitability [626]. Other parameters that may influence these outcomes include current intensity, current flow direction, skin preparation, and stimulation intervals [32728] . In addition, in clinical populations, the heterogeneity of the brain lesions can also influence the inconsistency in tDCS effects [29]. Despite the goal of tDCS of modulating cortical areas by using different parameters, some studies have showed that, by altering cortical excitability, the electrical field could reach subcortical structures, such as basal ganglia, due to brain connections between cortical and subcortical areas [30,31,32,33]. This potential effect on deeper brain structure has supported the broad investigation of tDCS in various disorders, even if the cortical region under stimulating electrode is not directly linked to the neurological condition being investigated. Indeed, the current variable and moderate effect sizes from clinical tDCS studies in stroke encourage researchers to test alternative targets to promote motor recovery in this condition.

In this review, we discuss evidence on the application of four different tDCS montages to promote and enhance motor rehabilitation: [1] anodal tDCS ipsilateral and cathodal tDCS bilateral, [2] combination of central and peripheral stimulation, [3] prefrontal montage and [4] cerebellar stimulation.[…]

 

Continue —> Searching for the optimal tDCS target for motor rehabilitation | Journal of NeuroEngineering and Rehabilitation | Full Text

figure1

Fig. 1 Motor cortex stimulation in a scenario where the left hemisphere was lesioned. Figure a Anodal stimulation of left primary motor cortex: anode over the left M1 and cathode over the right supraorbital region. Figure b Cathodal stimulation of right primary motor cortex: cathode over the right M1 and anode over the left supraorbital region. Figure c Bilateral stimulation: anode over the affected hemisphere (left) and cathode over the non-affected hemisphere (right)

 

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[ARTICLE] Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling – Full Text

Abstract

Background

Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery.

Methods

We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time.

Results

We demonstrated patients’ control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients.

Conclusions

Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

Background

The ability to walk directly relates to quality of life. Neurological lesions such as those underlying stroke and spinal cord injury (SCI) often result in severe motor impairments (i.e., paresis, spasticity, abnormal joint couplings) that compromise an individual’s motor capacity and health throughout the life span. For several decades, scientific effort in rehabilitation robotics has been directed towards exoskeletons that can help enhance motor capacity in neurologically impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had limited performance when tested in healthy individuals [1] and have achieved only modest clinical impact in neurologically impaired patients [2], e.g., stroke [34], SCI patients [5]. […]

 

Continue —>  Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1

Fig. 1 Enter aSchematic representation of the real-time modeling framework and its communication with the robotic exoskeleton. The whole framework is operated by a Raspberry Pi 3 single-board computer. The framework consists of five main components: a The EMG plugin collects muscle bioelectric signals from wearable active electrodes and transfers them to the EMG-driven model. b The B-spline component computes musculotendon length (Lmt) and moment arm (MA) values from joint angles collected via robotic exoskeleton sensors. c The EMG-driven model uses input EMG, Lmt and MA data to compute the resulting mechanical forces in 12 lower-extremity musculotendon units (Table 1) and joint moment about the degrees of freedom of knee flexion-extension and ankle plantar-dorsiflexion. d The offline calibration procedure identifies internal parameters of the model that vary non-linearly across individuals. These include optimal fiber length and tendon slack length, muscle maximal isometric force, and excitation-to-activation shape factors. eThe exoskeleton plugin converts EMG-driven model-based joint moment estimates into exoskeleton control commands. Please refer to the Methods section for an in-depth description caption

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[WEB SITE] Our Newest Acquisitions – National Rehabilitation Information Center

If you’re not already a subscriber, learn how you can join the FREE REHABDATA-Connection monthly literature awareness service.

The list below highlights 342 document abstracts added within the last 30 days.   Click the new link to read the latest additions for a given topic.   Some abstracts are related to several topics.

These keyword searches were developed specifically for REHABDATA Connection.   They are not a fool-proof method for topic searches, but will give a comprehensive listing of the latest abstract.   You can learn about how these search strategies were created by visiting the Search Strategies document.

Records are organized by when they were added to the database, not their publication date.

Autoimmune disorders 3 new
Blindness/visual impairments 7 new
Brain injuries 32 new
Deafness/hearing impairments 19 new
Developmental disabilities 68 new
Neurological/neuromuscular disorders 68 new
Poliomyelitis
Psychological disabilities 32 new
Spinal cord injury 19 new
Stroke 28 new
ADA 11 new
Advocacy/self help 14 new
Aging 30 new
Any legislation/policy 175 new
Assistive technology/devices 43 new
Attitudes/feelings 15 new
Burn injury 39 new
Caregiving 12 new
Case administration and management/counseling 19 new
Children/youth/infants 78 new
Disability Studies 3 new
Education/school 112 new
Emergency Preparedness
Employment/transition to work 109 new
Evaluation/needs assessment/tests 147 new
Family issues 49 new
Home modification 1 new
Independent living/community integration 99 new
Information resources 50 new
International rehabilitation 22 new
Knowledge translation 1 new
Learning disabilities 2 new
Medical or rehabilitation facilities 38 new
Medical rehabilitation/rehabilitation medicine 56 new
Mental health/self concept 22 new
Mobility issues 46 new
Money I: Organizations 21 new
Money II: Consumers 17 new
Organization management/project administration 48 new
Participatory action research 1 new
Physical/Occupational/Speech Therapy 37 new
Recreation/leisure/sports 45 new
Rehabilitation success/outcome 23 new
Research methodology 27 new
Research utilization 5 new
Self care/daily living 30 new
Service delivery/rehabilitation services 58 new
Special populations: ethnic groups/rural services 9 new
Statistics/demographics/epidemiology 47 new
Surveys/questionnaires 30 new
Transportation/travel 14 new
Universal design 5 new
All NIDILRR documents (by funded and defunded projects) 205 new
Fellowships (H133F) 3 new
Field-Initiated Projects (H133G) 1 new
Model Spinal Cord Injury Systems (H133N) 4 new
NIDILRR Contracts (HN)
Rehabilitation Engineering Research Centers (H133E) 9 new
Rehabilitation Research and Training Centers (H133B) 38 new
Research and Demonstration Projects (H133A) 76 new
Research Training Grants (H133P) 14 new
Small Business Innovative Research (RW) 1 new
State Technology Assistance (H224A)
Utilization Projects/ADA projects (H133D) 9 new

via Our Newest Acquisitions | National Rehabilitation Information Center

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[Abstract + References] Electromyography as a Suitable Input for Virtual Reality-Based Biofeedback in Stroke Rehabilitation – Conference paper

Abstract

Virtual reality (VR)-based biofeedback of brain signals using electroencephalography (EEG) has been utilized to encourage the recovery of brain-to-muscle pathways following a stroke. Such models incorporate principles of action observation with neurofeedback of motor-related brain activity to increase sensorimotor activity on the lesioned hemisphere. However, for individuals with existing muscle activity in the hemiparetic arm, we hypothesize that providing biofeedback of muscle signals, to strengthen already established brain-to-muscle pathways, may be more effective. In this project, we aimed to understand whether and when feedback of muscle activity (measured using surface electromyography (EMG)) might more effective compared to EEG biofeedback. To do so, we used a virtual reality (VR) training paradigm we developed for stroke rehabilitation (REINVENT), which provides EEG biofeedback of ipsilesional sensorimotor brain activity and simultaneously records EMG signals. We acquired 640 trials over eight 1.5-h sessions in four stroke participants with varying levels of motor impairment. For each trial, participants attempted to move their affected arm. Successful trials, defined as when their EEG sensorimotor desynchronization (8–24 Hz) during a time-limited movement attempt exceeded their baseline activity, drove a virtual arm towards a target. Here, EMG signals were analyzed offline to see (1) whether EMG amplitude could be significantly differentiated between active trials compared to baseline, and (2) whether using EMG would have led to more successful VR biofeedback control than EEG. Our current results show a significant increase in EMG amplitude across all four participants for active versus baseline trials, suggesting that EMG biofeedback is feasible for stroke participants across a range of impairments. However, we observed significantly better performance with EMG than EEG for only the three individuals with higher motor abilities, suggesting that EMG biofeedback may be best suited for those with better motor abilities.

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via Electromyography as a Suitable Input for Virtual Reality-Based Biofeedback in Stroke Rehabilitation | SpringerLink

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[Abstract + References] Multimodal Head-Mounted Virtual-Reality Brain-Computer Interface for Stroke Rehabilitation – Conference paper

Abstract

Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with severe stroke cannot benefit from many training solutions since they have paresis and/or spasticity, limiting volitional movement. Nonetheless, research has shown that individuals with severe stroke may have modest benefits from action observation, virtual reality, and neurofeedback from brain-computer interfaces (BCIs). In this study, we combined the principles of action observation in VR together with BCI neurofeedback for stroke rehabilitation to try to elicit optimal rehabilitation gains. Here, we illustrate the development of the REINVENT platform, which takes post-stroke brain signals indicating an attempt to move and drives a virtual avatar arm, providing patient-driven action observation in head-mounted VR. We also present a longitudinal case study with a single individual to demonstrate the feasibility and potentially efficacy of the REINVENT system.

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[Infographic] Traumatic Brain Injury

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[Abstract + References] Preliminary Design of Soft Exo-Suit for Arm Rehabilitation – Conference paper

Abstract

Every year, millions of people experience a stroke but only a few of them fully recover. Recovery requires a working staff, which is time consuming and inefficient. Therefore, over the past few years rehabilitation robots like Exoskeletons have been used in the recuperation process for patients. In this paper we have designed an Exosuit which takes into considerations of the rigid Exo-Skeleton and its limitations for patients suffering from loss of function of the arm. This paper concentrates on enabling a stroke affected person to perform flexion-extension at elbow joint. Validation of the developed model on general population is still needed.

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[ARTICLE] Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-Driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report – Full Text

To maximize brain plasticity after stroke, a plethora of rehabilitation strategies have been explored. These include the use of intensive motor training, motor-imagery (MI), and action-observation (AO). Growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has been shown. However, most VR tools are designed to exploit active movement, and hence patients with low level of motor control cannot fully benefit from them. Consequently, the idea of directly training the central nervous system has been promoted by utilizing MI with electroencephalography (EEG)-based brain-computer interfaces (BCIs). To date, detailed information on which VR strategies lead to successful functional recovery is still largely missing and very little is known on how to optimally integrate EEG-based BCIs and VR paradigms for stroke rehabilitation. The purpose of this study was to examine the efficacy of an EEG-based BCI-VR system using a MI paradigm for post-stroke upper limb rehabilitation on functional assessments, and related changes in MI ability and brain imaging. To achieve this, a 60 years old male chronic stroke patient was recruited. The patient underwent a 3-week intervention in a clinical environment, resulting in 10 BCI-VR training sessions. The patient was assessed before and after intervention, as well as on a one-month follow-up, in terms of clinical scales and brain imaging using functional MRI (fMRI). Consistent with prior research, we found important improvements in upper extremity scores (Fugl-Meyer) and identified increases in brain activation measured by fMRI that suggest neuroplastic changes in brain motor networks. This study expands on the current body of evidence, as more data are needed on the effect of this type of interventions not only on functional improvement but also on the effect of the intervention on plasticity through brain imaging.

Introduction

Worldwide, stroke is a leading cause of adult long-term disability (Mozaffarian et al., 2015). From those who survive, an increased number is suffering with severe cognitive and motor impairments, resulting in loss of independence in their daily life such as self-care tasks and participation in social activities (Miller et al., 2010). Rehabilitation following stroke is a multidisciplinary approach to disability which focuses on recovery of independence. There is increasing evidence that chronic stoke patients maintain brain plasticity, meaning that there is still potential for additional recovery (Page et al., 2004). Traditional motor rehabilitation is applied through physical therapy and/or occupational therapy. Current approaches of motor rehabilitation include functional training, strengthening exercises, and range of movement exercises. In addition, techniques based on postural control, stages of motor learning, and movement patterns have been proposed such as in the Bobath concept and Bunnstrom approach (amongst others) (Bobath, 1990). After patients complete subacute rehabilitation programs, many still show significant upper limb motor impairment. This has important functional implications that ultimately reduce their quality of life. Therefore, alternative methods to maximize brain plasticity after stroke need to be developed.

So far, there is growing evidence that action observation (AO) (Celnik et al., 2008) and motor imagery (MI) improve motor function (Mizuguchi and Kanosue, 2017) but techniques based on this paradigm are not widespread in clinical settings. As motor recovery is a learning process, the potential of MI as a training paradigm relies on the availability of an efficient feedback system. To date, a number of studies have demonstrated the positive impact of virtual-reality (VR) based on neuroscientific grounds on recovery, with proven effectiveness in the stroke population (Bermúdez i Badia et al., 2016). However, patients with no active movement cannot benefit from current VR tools due to low range of motion, pain, fatigue, etc. (Trompetto et al., 2014). Consequently, the idea of directly training the central nervous system was promoted by establishing an alternative pathway between the user’s brain and a computer system.

This is possible by using electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs), since they can provide an alternative non-muscular channel for communication and control to the external world (Wolpaw et al., 2002), while they could also provide a cost-effective solution for training (Vourvopoulos and Bermúdez, 2016b). In rehabilitation, BCIs could offer a unique tool for rehabilitation since they can stimulate neural networks through the activation of mirror neurons (Rizzolatti and Craighero, 2004) by means of action-observation (Kim et al., 2016), motor-intent and motor-imagery (Neuper et al., 2009), that could potentially lead to post-stroke motor recovery. Thus, BCIs could provide a backdoor to the activation of motor neural circuits that are not stimulated through traditional rehabilitation techniques.

In EEG-based BCI systems for motor rehabilitation, Alpha (8–12 Hz) and Beta (12–30 Hz) EEG rhythms are utilized since they are related to motor planning and execution (McFarland et al., 2000). During a motor attempt or motor imagery, the temporal pattern of the Alpha rhythms desynchronizes. This rhythm is also named Rolandic Mu-rhythm or the sensorimotor rhythm (SMR) because of its localization over the sensorimotor cortices. Mu-rhythms are considered indirect indications of functioning of the mirror neuron system and general sensorimotor activity (Kropotov, 2016). These are often detected together with Beta rhythm changes in the form of an event-related desynchronization (ERD) when a motor action is executed (Pfurtscheller and Lopes da Silva, 1999). These EEG patterns are primarily detected during task-based EEG (e.g., when the participant is actively moving or imagining movement) and they are of high importance in MI-BCIs for motor rehabilitation.

A meta-analysis of nine studies (combined N = 235, sample size variation 14 to 47) evaluated the clinical effectiveness of BCI-based rehabilitation of patients with post-stroke hemiparesis/hemiplegia and concluded that BCI technology could be effective compared to conventional treatment (Cervera et al., 2018). This included ischemic and hemorrhagic stroke in both subacute and chronic stages of stoke, between 2 to 8 weeks. Moreover, there is evidence that BCI-based rehabilitation promotes long-lasting improvements in motor function of chronic stroke patients with severe paresis (Ramos-Murguialday et al., 2019), while overall BCI’s are starting to prove their efficacy as rehabilitative technologies in patients with severe motor impairments (Chaudhary et al., 2016).

The feedback modalities used for BCI motor rehabilitation include: non-embodied simple two-dimensional tariffs on a screen (Prasad et al., 2010Mihara et al., 2013), embodied avatar representation of the patient on a screen or with augmented reality (Holper et al., 2010Pichiorri et al., 2015), neuromuscular electrical stimulation (NMES) (Kim et al., 2016Biasiucci et al., 2018). and robotic exoskeletal orthotic movement facilitation (Ramos-Murguialday et al., 2013Várkuti et al., 2013Ang et al., 2015). In addition, it has been shown that multimodal feedback lead to a significantly better performance in motor-imagery (Sollfrank et al., 2016) but also multimodal feedback combined with motor-priming, (Vourvopoulos and Bermúdez, 2016a). However, there is no evidence which modalities are more efficient in stroke rehabilitation are.

Taking into account all previous findings in the effects of multimodal feedback in MI training, the purpose of this case study is to examine the effect of the MI paradigm as a treatment for post-stroke upper limb motor dysfunction using the NeuRow BCI-VR system. This is achieved through the acquisition of clinical scales, dynamics of EEG during the BCI treatment, and brain activation as measured by functional MRI (fMRI). NeuRow is an immersive VR environment for MI-BCI training that uses an embodied avatar representation of the patient arms and haptic feedback. The combination of MI-BCIs with VR can reinforce activation of motor brain areas, by promoting the illusion of physical movement and the sense of embodiment in VR (Slater, 2017), and hence further engaging specific neural networks and mobilizing the desired neuroplastic changes. Virtual representation of body parts paves the way to include action observation during treatment. Moreover, haptic feedback is added since a combination of feedback modalities could prove to be more effective in terms of motor-learning (Sigrist et al., 2013). Therefore, the target of this system is to be used by patients with low or no levels of motor control. With this integrated BCI-VR approach, severe cases of stroke survivors may be admitted to a VR rehabilitation program, complementing traditional treatment.

Methodology

Patient Profile

In this pilot study we recruited a 60 years old male patient with left hemiparesis following cerebral infarct in the right temporoparietal region 10 months before. The participant had corrected vision through eyewear, he had 4 years of schooling and his experience with computers was reported as low. Moreover, the patient was on a low dose of diazepam (5 mg at night to help sleep), dual antiplatelet therapy, anti-hypertensive drug and metformin. Hemiparesis was associated with reduced dexterity and fine motor function; however, sensitivity was not affected. Other sequelae of the stroke included hemiparetic gait and dysarthria. Moreover, a mild cognitive impairment was identified which did not interfere with his ability to perform the BCI-VR training. The patient had no other relevant comorbidities. Finally, the patient was undergoing physiotherapy and occupational therapy at the time of recruitment and had been treated with botulinum toxin infiltration 2 months before due to focal spasticity of the biceps brachii.

Intervention Protocol

The patient underwent a 3-weeks intervention with NeuRow, resulting in 10 BCI sessions of a 15 min of exposure in VR training per session. Clinical scales, motor imagery capability assessment, and functional -together with structural- MRI data had been gathered in three time-periods: (1) before (serving as baseline), (2) shortly after the intervention and (3) one-month after the intervention (to assess the presence of long-term changes). Finally, electroencephalographic (EEG) data had been gathered during all sessions, resulting in more than 20 datasets of brain electrical activity.

The experimental protocol was designed in collaboration with the local healthcare system of Madeira, Portugal (SESARAM) and approved by the scientific and ethic committees of the Central Hospital of Funchal. Finally, written informed consent was obtained from the participant upon recruitment for participating to the study but also for the publication of the case report in accordance with the 1964 Declaration of Helsinki.

Assessment Tools

A set of clinical scales were acquired including the following:

1. Montreal Cognitive Assessment (MoCA). MoCA is a cognitive screening tool, with a score range between 0 and 30 (a score greater than 26 is considered to be normal) validated also for the Portuguese population, (Nasreddine et al., 2005).

2. Modified Ashworth scale (MAS). MAS is a 6-point rating scale for measuring spasticity. The score range is 0, 1, 1+, 2, 3, and 4 (Ansari et al., 2008).

3. Fugl-Meyer Assessment (FMA). FMA is a stroke specific scale that assesses motor function, sensation, balance, joint range of motion and joint pain. The motor domain for the upper limb has a maximum score of 66 (Fugl-Meyer et al., 1975).

4. Stroke Impact Scale (SIS). SIS is a subjective scale of the perceived stroke impact and recovery as reported by the patient, validated for the Portuguese population. The score of each domain of the questionnaire ranges from 0 to 100 (Duncan et al., 1999).

5. Vividness of Movement Imagery Questionnaire (VMIQ2). VMIQ2 is an instrument that assess the capability of the participant to perform imagined movements from external perspective (EVI), internal perspective imagined movements (IVI) and finally, kinesthetic imagery (KI) (Roberts et al., 2008).

NeuRow BCI-VR System

EEG Acquisition

For EEG data acquisition, the Enobio 8 (Neuroelectrics, Barcelona, Spain) system was used. Enobio is a wearable wireless EEG sensor with 8 EEG channels for the recording and visualization of 24-bit EEG data at 500 Hz and a triaxial accelerometer. The spatial distribution of the electrodes followed the 10–20 system configuration (Klem et al., 1999) with the following electrodes over the somatosensory and motor areas: Frontal-Central (FC5, FC6), Central (C1, C2, C3, C4), and Central-Parietal (CP5, CP6) (Figure 1A). The EEG system was connected via Bluetooth to a dedicated desktop computer, responsible for the EEG signal processing and classification, streaming the data via UDP through the Reh@Panel (RehabNet Control Panel) for controlling the virtual environment. The Reh@Panel is a free tool that acts as a middleware between multiple interfaces and virtual environments (Vourvopoulos et al., 2013).

FIGURE 1

Figure 1. Experimental setup, including: (A) the wireless EEG system; (B) the Oculus HMD, together with headphones reproducing the ambient sound from the virtual environment; (C) the vibrotactile modules supported by a custom-made table-tray, similar to the wheelchair trays used for support; (D) the visual feedback with NeuRow game. A written informed consent was obtained for the publication of this image.

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[ARTICLE] Cell-Based Therapies for Stroke: Are We There Yet? – Full Text

Stroke is the second leading cause of death and physical disability, with a global lifetime incidence rate of 1 in 6. Currently, the only FDA approved treatment for ischemic stroke is the administration of tissue plasminogen activator (tPA). Stem cell clinical trials for stroke have been underway for close to two decades, with data suggesting that cell therapies are safe, feasible, and potentially efficacious. However, clinical trials for stroke account for <1% of all stem cell trials. Nevertheless, the resources devoted to clinical research to identify new treatments for stroke is still significant (53–64 million US$, Phase 1–4). Notably, a quarter of cell therapy clinical trials for stroke have been withdrawn (15.2%) or terminated (6.8%) to date. This review discusses the bottlenecks in delivering a successful cell therapy for stroke, and the cost-to-benefit ratio necessary to justify these expensive trials. Further, this review will critically assess the currently available data from completed stroke trials, the importance of standardization in outcome reporting, and the role of industry-led research in the development of cell therapies for stroke.

Introduction

Background

Stroke has a devastating effect on the society worldwide. In addition to its significant mortality rate of 50% as reported in 5-year survival studies (1), it affects as many as 1 in 6 people in their lifetimes, and is the leading cause of disability worldwide (2). A stroke results in a complex interplay of inflammation and repair with effects on neural, vascular, and connective tissue in and around the affected areas of the brain (3). Therefore, sequelae of stroke such as paralysis, chronic pain, and seizures can persist long term and prevent the patient from fully reintegrating into society. Stroke therefore remains the costliest healthcare burden as a whole (4). In 2012, the total cost of stroke in Australia was estimated to be about $5 billion with direct health care costs attributing to $881 million of the total (5).

Unfortunately, treatment options for stroke are still greatly limited. Intravenous recombinant tissue plasminogen activator (tPA) and endovascular thrombectomy (EVT) are currently the only effective treatments available for acute stroke. However, there is only a brief window of opportunity where they can be successfully applied. EVT is performed until up to 24 h of stroke onset (6), while tPA is applied within 4.5 h of stroke onset. Notably, the recent WAKE-UP (NCT01525290) (7) and EXTEND (NCT01580839) trials have shown that this therapeutic window can be safely extended to 9 h from stroke onset. Furthermore, advancements in acute stroke care and neurorehabilitation have shown to be effective in improving neurological function (8). However, there are no treatments that offer restoration of function and as a result, many patients are left with residual deficits following a stroke. Cell-based therapies have shown promising results in animal models addressing the recovery phase following stroke (9). This is encouraging as currently, there are no approved treatment options addressing the reversal of neurological damages once a stroke has occurred (10).

The majority of data from animal studies and clinical trials demonstrate the therapeutic potential of stem cells in the restoration of central nervous system (CNS) function (1112), applicable to neurodegenerative diseases as well as traumatic brain injury. Transplanted stem cells were reportedly able to differentiate into neurons and glial cells, whilst supporting neural reconstruction and angiogenesis in the ischemic region of the brain (13). Previous work demonstrated the ability of mesenchymal stem cells (MSCs) to differentiate into neurons, astrocytes (14), endothelial cells (1516), and oligodendrocyte lineage cells (17) such as NG2-positive cells (18in vitro, and undergo neuronal or glial differentiation in vivo (19). Bone marrow-derived mesenchymal stem cells (BMSCs) have shown potential to differentiate into endothelial cells in vitro (20). Additionally, both BMSCs and adipose stem cells (ASCs) have been shown to demonstrate neural lineage differentiation potential in vitro (2123). Furthermore, stem cells are able to modulate multiple cell signaling pathways involved in endogenous neurogenesis, angiogenesis, immune modulation and neural plasticity, sometimes in addition to cell replacement (3). The delivery of stem cells from the brain, bone marrow, umbilical cord, and adipose tissue, have been reported to reduce infarct size and improve functional outcomes regardless of tissue source (9). While these were initially exciting reports, they raise the question as to the validity of the findings to date since these preclinical reports are almost uniformly positive. The absence of scientific skepticism and robust debate may in fact have negated progress in this field.

Cell-based therapies have been investigated as a clinical option since the 1990s. The first pilot stroke studies in 2005 investigated the safety of intracranial delivery of stem cells (including porcine neural stem cells) to patients with chronic basal ganglia infarcts or subcortical motor strokes (2425). However, since the publication of these reports, hundreds of preclinical studies have shown that a variety of cell types including those derived from non-neural tissues can enhance structural and functional recovery in stroke. Cell therapy trials, mainly targeted at small cohorts of patients with chronic stroke, completed in the 2000s, showed satisfactory safety profiles and suggestions of efficacy (10). Current treatments such as tPA and EVT only have a narrow therapeutic window, limited efficacy in severe stroke and may be accompanied by severe side effects. Specifically, the side effects of EVT include intracranial hemorrhage, vessel dissection, emboli to new vascular territories, and vasospasm (26). The benefit of tPA for patients with a severe stroke with a large artery occlusion can vary significantly (27). This is mainly due to the failure (<30%) of early recanalisation of the occlusion. Thus, despite the treatment options stroke is still a major cause of mortality and morbidity, and there is need for new and improved therapies.

Stem cells have been postulated to significantly extend the period of intervention and target subacute as well as the chronic phase of stroke. Numerous neurological disorders such as Parkinson’s disease (1228), Alzheimer’s disease (29), age-related macular degeneration (30), traumatic brain injury (31), and malignant gliomas (32) have been investigated for the applicability of stem cell therapy. These studies have partly influenced the investigation of stem cell therapies for stroke. A small fraction of stem cell research has been successfully translated to clinical trials. As detailed in Table 1, most currently active trials use neuronal stem cells (NSCs), MSCs or BMSCs (3537), including conditionally immortalized neural stem-cell line (CTX-DP) CTX0E03 (38), neural stem/progenitor cells (NSCs/NPSCs) (e.g., NCT03296618), umbilical cord blood (CoBis2, NCT03004976), adipose (NCT02813512), or amnion epithelial cells (hAECs, ACTRN 1261800076279) (39).

Table 1. Challenges and bottlenecks of stem cell therapy and clinical trials using stem cells (3334).

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