Brain plasticity following MI-BCI training combined with tDCS in a randomized trial in chronic subcortical stroke subjects: a preliminary study

Noninvasive brain stimulation during EEG improves machine learning classification in chronic stroke

BACKGROUND

In individuals with chronic stroke and hemiparesis, noninvasive brain stimulation (NIBS) may be used as an adjunct to therapy for improving motor recovery. Specific states of movement during motor recovery are more responsive to brain stimulation than others, thus a system that could auto-detect movement state would be useful in correctly identifying the most effective stimulation periods. The aim of this study was to compare the performance of different machine learning models in classifying movement periods during EEG recordings of hemiparetic individuals receiving noninvasive brain stimulation. We hypothesized that transcranial direct current stimulation, a form of NIBS, would modulate brain recordings correlating with movement state and improve classification accuracies above those receiving sham stimulation.

METHODS

Electroencephalogram data were obtained from 10 participants with chronic stroke and 11 healthy individuals performing a motor task while undergoing transcranial direct current stimulation. Eight traditional machine learning algorithms and five ensemble methods were used to classify two movement states (a hold posture and an arm reaching movement) before, during and after stimulation. To minimize compute times, preprocessing and feature extraction were limited to z-score normalization and power binning into five frequency bands (delta through gamma).

RESULTS

Classification of disease state produced significantly higher accuracies in the stimulation (versus sham) group at 78.9% (versus 55.6%, p < 0.000002). We observed significantly higher accuracies when classifying stimulation state in the chronic stroke group (77.6%) relative to healthy controls (64.1%, p < 0.0095). In the chronic stroke cohort, classification of hold versus reach was highest during the stimulation period (75.2%) as opposed to the pre- and post-stimulation periods. Linear discriminant analysis, logistic regression, and decision tree algorithms classified movement state most accurately in participants with chronic stroke during the stimulation period (76.1%). For the ensemble methods, the highest classification accuracy for hold versus reach was achieved using low gamma frequency (30-50 Hz) as a feature (74.5%), although this result did not achieve statistical significance.

CONCLUSIONS

Machine learning algorithms demonstrated sufficiently high movement state classification accuracy in participants with chronic stroke performing functional tasks during noninvasive brain stimulation. tDCS improved disease state and movement state classification in participants with chronic stroke.

Transcranial Direct Current Stimulation and Brain-Computer Interfaces for Improving Post-Stroke Recovery: A Systematic Review and Meta-Analysis

OBJECTIVE

This study aimed to evaluate the effectiveness of transcranial direct current stimulation associated with brain-computer interface in stroke patients.

DATA SOURCES

The PubMed, Central, PEDro, Web of Science, SCOPUS, PsycINFO Ovid, CINAHL EBSCO, EMBASE, and ScienceDirect databases were searched from inception to April 2023 for randomized controlled studies reporting the effects of active transcranial direct current stimulation associated with brain-computer interface to a transcranial direct current stimulation sham associated with brain-computer interface condition on the outcome measure (motor performance and functional independence).

REVIEW METHODS

We searched for full-text articles which had investigated the effect of transcranial direct current stimulation associated with brain-computer interface on motor performance in the upper extremities in stroke patients. The standardized mean differences derived from the change in scores between pretreatment and post-treatment were adopted as the effect size measure, with a 95% confidence interval. Possible sources of heterogeneity were analyzed by performing subgroup analyses in order to examine the moderating effects for one variable: the level of injury severity.

RESULTS

Nine studies were included in the qualitative synthesis and the meta-analysis. The findings of the conducted analyses indicated there is not enough evidence to suggest that active transcranial direct current stimulation associated with brain-computer interface is more efficient in motor performance and functional independence when compared to sham transcranial direct current stimulation associated with brain-computer interface or brain-computer interface alone. In addition, the quality of evidence was rated very low. A subgroup analysis was performed for the motor performance outcome considering the injury severity level.

CONCLUSION

We found evidence that transcranial direct current stimulation associated with brain-computer interface was not more beneficial than sham transcranial direct current stimulation associated with brain-computer interface or brain-computer interface alone.

A Review on Motor Imagery with Transcranial Alternating Current Stimulation: Bridging Motor and Cognitive Welfare for Patient Rehabilitation

Research has shown the effectiveness of motor imagery in patient motor rehabilitation. Transcranial electrical stimulation has also demonstrated to improve patient motor and non-motor performance. However, mixed findings from motor imagery studies that involved transcranial electrical stimulation suggest that current experimental protocols can be further improved towards a unified design for consistent and effective results. This paper aims to review, with some clinical and neuroscientific findings from literature as support, studies of motor imagery coupled with different types of transcranial electrical stimulation and their experiments onhealthy and patient subjects. This review also includes the cognitive domains of working memory, attention, and fatigue, which are important for designing consistent and effective therapy protocols. Finally, we propose a theoretical all-inclusive framework that synergizes the three cognitive domains with motor imagery and transcranial electrical stimulation for patient rehabilitation, which holds promise of benefiting patients suffering from neuromuscular and cognitive disorders.

Enhanced motor imagery of digits within the same hand via vibrotactile stimulation

Purpose

The aim of the present study is to evaluate the effect of vibrotactile stimulation prior to repeated complex motor imagery of finger movements using the non-dominant hand on motor imagery (MI) performance.

Methods

Ten healthy right-handed adults (4 females and 6 males) participated in the study. The subjects performed motor imagery tasks with and without a brief vibrotactile sensory stimulation prior to performing motor imagery using either their left-hand index, middle, or thumb digits. Mu- and beta-band event-related desynchronization (ERD) at the sensorimotor cortex and an artificial neural network-based digit classification was evaluated.

Results

The ERD and digit discrimination results from our study showed that ERD was significantly different between the vibration conditions for the index, middle, and thumb. It was also found that digit classification accuracy with-vibration (mean ± SD = 66.31 ± 3.79%) was significantly higher than without-vibration (mean ± SD = 62.68 ± 6.58%).

Conclusion

The results showed that a brief vibration was more effective at improving MI-based brain-computer interface classification of digits within a single limb through increased ERD compared to performing MI without vibrotactile stimulation.

Sparse Logistic Regression-Based EEG Channel Optimization Algorithm for Improved Universality across Participants

Electroencephalogram (EEG) channel optimization can reduce redundant information and improve EEG decoding accuracy by selecting the most informative channels. This article aims to investigate the universality regarding EEG channel optimization in terms of how well the selected EEG channels can be generalized to different participants. In particular, this study proposes a sparse logistic regression (SLR)-based EEG channel optimization algorithm using a non-zero model parameter ranking method. The proposed channel optimization algorithm was evaluated in both individual analysis and group analysis using the raw EEG data, compared with the conventional channel selection method based on the correlation coefficients (CCS). The experimental results demonstrate that the SLR-based EEG channel optimization algorithm not only filters out most redundant channels (filters 75-96.9% of channels) with a 1.65-5.1% increase in decoding accuracy, but it can also achieve a satisfactory level of decoding accuracy in the group analysis by employing only a few (2-15) common EEG electrodes, even for different participants. The proposed channel optimization algorithm can realize better universality for EEG decoding, which can reduce the burden of EEG data acquisition and enhance the real-world application of EEG-based brain-computer interface (BCI).

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

Brain-Computer Interfaces (BCI) is an exciting and emerging research area for researchers and scientists. It is a suitable combination of software and hardware to operate any device mentally. This review emphasizes the significant stages in the BCI domain, current problems, and state-of-the-art findings. This article also covers how current results can contribute to new knowledge about BCI, an overview of BCI from its early developments to recent advancements, BCI applications, challenges, and future directions. The authors pointed to unresolved issues and expressed how BCI is valuable for analyzing the human brain. Humans' dependence on machines has led humankind into a new future where BCI can play an essential role in improving this modern world.

Transcranial direct current stimulation (tDCS) in depression induces structural plasticity

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique involving administration of well-tolerated electrical current to the brain through scalp electrodes. TDCS may improve symptoms in neuropsychiatric disorders, but mixed results from recent clinical trials underscore the need to demonstrate that tDCS can modulate clinically relevant brain systems over time in patients. Here, we analyzed longitudinal structural MRI data from a randomized, double-blind, parallel-design clinical trial in depression (NCT03556124, N = 59) to investigate whether serial tDCS individually targeted to the left dorso-lateral prefrontal cortex (DLPFC) can induce neurostructural changes. Significant (FWEc p < 0.05) treatment-related gray matter changes were observed with active high-definition (HD) tDCS relative to sham tDCS within the left DLPFC stimulation target. No changes were observed with active conventional tDCS. A follow-up analysis within individual treatment groups revealed significant gray matter increases with active HD-tDCS in brain regions functionally connected with the stimulation target, including the bilateral DLPFC, bilateral posterior cingulate cortex, subgenual anterior cingulate cortex, and the right hippocampus, thalamus and left caudate brain regions. Integrity of blinding was verified, no significant differences in stimulation-related discomfort were observed between treatment groups, and tDCS treatments were not augmented by any other adjunct treatments. Overall, these results demonstrate that serial HD-tDCS leads to neurostructural changes at a predetermined brain target in depression and suggest that such plasticity effects may propagate over brain networks.

A Review of Online Classification Performance in Motor Imagery-Based Brain–Computer Interfaces for Stroke Neurorehabilitation

Motor imagery (MI)-based brain–computer interfaces (BCI) have shown increased potential for the rehabilitation of stroke patients; nonetheless, their implementation in clinical practice has been restricted due to their low accuracy performance. To date, although a lot of research has been carried out in benchmarking and highlighting the most valuable classification algorithms in BCI configurations, most of them use offline data and are not from real BCI performance during the closed-loop (or online) sessions. Since rehabilitation training relies on the availability of an accurate feedback system, we surveyed articles of current and past EEG-based BCI frameworks who report the online classification of the movement of two upper limbs in both healthy volunteers and stroke patients. We found that the recently developed deep-learning methods do not outperform the traditional machine-learning algorithms. In addition, patients and healthy subjects exhibit similar classification accuracy in current BCI configurations. Lastly, in terms of neurofeedback modality, functional electrical stimulation (FES) yielded the best performance compared to non-FES systems.

Non-invasive brain stimulation for fatigue in post-acute sequelae of SARS-CoV-2 (PASC)

BACKGROUND

and purpose: Fatigue is among the most common persistent symptoms following post-acute sequelae of Sars-COV-2 infection (PASC). The current study investigated the potential therapeutic effects of High-Definition transcranial Direct Current Stimulation (HD-tDCS) associated with rehabilitation program for the management of PASC-related fatigue.

METHODS

Seventy patients with PASC-related fatigue were randomized to receive 3 mA or sham HD-tDCS targeting the left primary motor cortex (M1) for 30 min paired with a rehabilitation program. Each patient underwent 10 sessions (2 sessions/week) over five weeks. Fatigue was measured as the primary outcome before and after the intervention using the Modified Fatigue Impact Scale (MFIS). Pain level, anxiety severity and quality of life were secondary outcomes assessed, respectively, through the McGill Questionnaire, Hamilton Anxiety Rating Scale (HAM-A) and WHOQOL.

RESULTS

Active HD-tDCS resulted in significantly greater reduction in fatigue compared to sham HD-tDCS (mean group MFIS reduction of 22.11 points vs 10.34 points). Distinct effects of HD-tDCS were observed in fatigue domains with greater effect on cognitive (mean group difference 8.29 points; effect size 1.1; 95% CI 3.56-13.01; P < .0001) and psychosocial domains (mean group difference 2.37 points; effect size 1.2; 95% CI 1.34-3.40; P < .0001), with no significant difference between the groups in the physical subscale (mean group difference 0.71 points; effect size 0.1; 95% CI 4.47-5.90; P = .09). Compared to sham, the active HD-tDCS group also had a significant reduction in anxiety (mean group difference 4.88; effect size 0.9; 95% CI 1.93-7.84; P < .0001) and improvement in quality of life (mean group difference 14.80; effect size 0.7; 95% CI 7.87-21.73; P < .0001). There was no significant difference in pain (mean group difference -0.74; no effect size; 95% CI 3.66-5.14; P = .09).

CONCLUSION

An intervention with M1 targeted HD-tDCS paired with a rehabilitation program was effective in reducing fatigue and anxiety, while improving quality of life in people with PASC.

Effects of neurofeedback training combined with transcranial direct current stimulation on motor imagery: A randomized controlled trial

Introduction

Neurofeedback (NFB) training and transcranial direct current stimulation (tDCS) have been shown to individually improve motor imagery (MI) abilities. However, the effect of combining both of them with MI has not been verified. Therefore, the aim of this study was to examine the effect of applying tDCS directly before MI with NFB.

Methods

Participants were divided into an NFB group (n = 10) that performed MI with NFB and an NFB + tDCS group (n = 10) that received tDCS for 10 min before MI with NFB. Both groups performed 60 MI trials with NFB. The MI task was performed 20 times without NFB before and after training, and μ-event-related desynchronization (ERD) and vividness MI were evaluated.

Results

μ-ERD increased significantly in the NFB + tDCS group compared to the NFB group. MI vividness significantly increased before and after training.

Discussion

Transcranial direct current stimulation and NFB modulate different processes with respect to MI ability improvement; hence, their combination might further improve MI performance. The results of this study indicate that the combination of NFB and tDCS for MI is more effective in improving MI abilities than applying them individually.

On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders

Emerging brain technologies have significantly transformed human life in recent decades. For instance, the closed-loop brain-computer interface (BCI) is an advanced software-hardware system that interprets electrical signals from neurons, allowing communication with and control of the environment. The system then transmits these signals as controlled commands and provides feedback to the brain to execute specific tasks. This paper analyzes and presents the latest research on closed-loop BCI that utilizes electric/magnetic stimulation, optogenetic, and sonogenetic techniques. These techniques have demonstrated great potential in improving the quality of life for patients suffering from neurodegenerative or psychiatric diseases. We provide a comprehensive and systematic review of research on the modalities of closed-loop BCI in recent decades. To achieve this, the authors used a set of defined criteria to shortlist studies from well-known research databases into categories of brain stimulation techniques. These categories include deep brain stimulation, transcranial magnetic stimulation, transcranial direct-current stimulation, transcranial alternating-current stimulation, and optogenetics. These techniques have been useful in treating a wide range of disorders, such as Alzheimer's and Parkinson's disease, dementia, and depression. In total, 76 studies were shortlisted and analyzed to illustrate how closed-loop BCI can considerably improve, enhance, and restore specific brain functions. The analysis revealed that literature in the area has not adequately covered closed-loop BCI in the context of cognitive neural prosthetics and implanted neural devices. However, the authors demonstrate that the applications of closed-loop BCI are highly beneficial, and the technology is continually evolving to improve the lives of individuals with various ailments, including those with sensory-motor issues or cognitive deficiencies. By utilizing emerging techniques of stimulation, closed-loop BCI can safely improve patients' cognitive and affective skills, resulting in better healthcare outcomes.

Rehabilitation Interventions Combined with Noninvasive Brain Stimulation on Upper Limb Motor Function in Stroke Patients

(1) Background: This systematic review aimed to focus on the effects of rehabilitation interventions combined with noninvasive brain stimulation on upper limb motor function in stroke patients. (2) Methods: PubMed, MEDLINE, and CINAHL were used for the literature research. Articles were searched using the following terms: "Stroke OR CVA OR cerebrovascular accident" AND "upper limb OR upper extremity" AND "NIBS OR Non-Invasive Brain Stimulation" OR "rTMS" OR "repetitive transcranial magnetic stimulation" OR "tDCS" OR "transcranial direct current stimulation" AND "RCT" OR randomized control trial." In total, 12 studies were included in the final analysis. (3) Results: Analysis using the Physiotherapy Evidence Database scale for qualitative evaluation of the literature rated eight articles as "excellent" and four as "good." Combined rehabilitation interventions included robotic therapy, motor imagery using brain-computer interaction, sensory control, occupational therapy, physiotherapy, task-oriented approach, task-oriented mirror therapy, neuromuscular electrical stimulation, and behavior observation therapy. (4) Conclusions: Although it is difficult to estimate the recovery of upper limb motor function in stroke patients treated with noninvasive brain stimulation alone, a combination of a task-oriented approach, occupational therapy, action observation, wrist robot-assisted rehabilitation, and physical therapy can be effective.

A Novel Patient-Tailored, Cumulative Neurotechnology-Based Therapy for Upper-Limb Rehabilitation in Severely Impaired Chronic Stroke Patients: The AVANCER Study Protocol

Effective, patient-tailored rehabilitation to restore upper-limb motor function in severely impaired stroke patients is still missing. If suitably combined and administered in a personalized fashion, neurotechnologies offer a large potential to assist rehabilitative therapies to enhance individual treatment effects. AVANCER (clinicaltrials.gov NCT04448483) is a two-center proof-of-concept trial with an individual based cumulative longitudinal intervention design aiming at reducing upper-limb motor impairment in severely affected stroke patients with the help of multiple neurotechnologies. AVANCER will determine feasibility, safety, and effectivity of this innovative intervention. Thirty chronic stroke patients with a Fugl-Meyer assessment of the upper limb (FM-UE) <20 will be recruited at two centers. All patients will undergo the cumulative personalized intervention within two phases: the first uses an EEG-based brain-computer interface to trigger a variety of patient-tailored movements supported by multi-channel functional electrical stimulation in combination with a hand exoskeleton. This phase will be continued until patients do not improve anymore according to a quantitative threshold based on the FM-UE. The second interventional phase will add non-invasive brain stimulation by means of anodal transcranial direct current stimulation to the motor cortex to the initial approach. Each phase will last for a minimum of 11 sessions. Clinical and multimodal assessments are longitudinally acquired, before the first interventional phase, at the switch to the second interventional phase and at the end of the second interventional phase. The primary outcome measure is the 66-point FM-UE, a significant improvement of at least four points is hypothesized and considered clinically relevant. Several clinical and system neuroscience secondary outcome measures are additionally evaluated. AVANCER aims to provide evidence for a safe, effective, personalized, adjuvant treatment for patients with severe upper-extremity impairment for whom to date there is no efficient treatment available.

The Role of Neuroplasticity in Improving the Decision-Making Quality of Individuals With Agenesis of the Corpus Callosum: A Systematic Review

Although individuals with agenesis of corpus callosum (ACC) possess intelligence coefficients within regular parameters, current studies have demonstrated decision-making compromise and potential negative social consequences. Furthermore, alternative pathways regarding brain connectivity in acallosal patients combined with cognitive therapy that would potentially mitigate such difficulties. Therefore, this study aimed to examine the current state of the art regarding brain foundations in the role of neuroplasticity by improving the decision-making quality in ACC.

A systematic revision of literature was performed including studies conducted on non-syndromic ACC individuals and analyzing the impact of the potential role of neuroplasticity on the decision-making published to date. Studies with patients who underwent callosotomy were excluded. Experimental studies performed on animal models were included.

During this period, 849 studies were identified; among them, 11 were eligible for qualitative analysis. Despite the paucity of evidence on this matter, patients with ACC present considerable decision-making difficulties mainly due to the functional connectivity impairment in the frontal lobes. Moreover, neuroplasticity was characterized by increased anterior commissure width as compared with controls. Notwithstanding, no studies were conducted on cognitive therapists managing this type of disease.

Although the reorganization of inter-hemispheric bundles on anterior commissure has demonstrated the main natural neuroanatomic strategy in ACC, further evidence will be needed to clarify whether cognitive stimulus could improve the decision-making quality.

The Application of Technological Intervention for Stroke Rehabilitation in Southeast Asia: A Scoping Review With Stakeholders' Consultation

Background

The technological intervention is considered as an adjunct to the conventional therapies applied in the rehabilitation session. In most high-income countries, technology has been widely used in assisting stroke survivors to undergo their treatments. However, technology use is still lacking in Southeast Asia, especially in middle- and low-income countries. This scoping review identifies and summarizes the technologies and related gaps available in Southeast Asia pertaining to stroke rehabilitation.

Methods

The JBI manual for evidence synthesis was used to conduct a scoping study. Until September 2021, an electronic search was performed using four databases (Medline, CINAHL, Scopus, ASEAN Citation Index). Only the studies that were carried out in Southeast Asia were chosen.

Results

Forty-one articles were chosen in the final review from 6,873 articles found during the initial search. Most of the studies reported the implementation of technological intervention combined with conventional therapies in stroke rehabilitation. Advanced and simple technologies were found such as robotics, virtual reality, telerehabilitation, motion capture, assistive devices, and mobility training from Singapore, Thailand, Malaysia, and Indonesia. The majority of the studies show that technological interventions can enhance the recovery period of stroke survivors. The consultation session suggested that the technological interventions should facilitate the needs of the survivors, caregivers, and practitioners during the rehabilitation.

Conclusions

The integration of technology into conventional therapies has shown a positive outcome and show significant improvement during stroke recovery. Future studies are recommended to investigate the potential of home-based technological intervention and lower extremities.

Tools to explore neuroplasticity in humans: Combining interventional neurophysiology with functional and structural magnetic resonance imaging and spectroscopy

This chapter summarizes how brain imaging can be used in combination with non-invasive transcranial stimulation to probe and induce neuroplasticity in the human brain. We aim to give a conceptual account and highlight exemplary studies. We showcase the scientific and clinical potentials of studies focusing on the combination of transcranial magnetic stimulation (TMS) with Magnetic Resonance Imaging (MRI) or Magnetic Resonance Spectroscopy (MRS). MRI and MRS can be used before brain stimulation to identify target networks and loci but also to inform individual dosing. After a brain stimulation session, MRI and MRS can be used to pinpoint how the stimulation protocol alters brain function, structure, or metabolism and relate these after-effects to behavioral and clinical outcomes. Complementing these "offline" approaches, TMS can also be applied "online" during MRI or MRS to delineate how stimulation acutely engages the stimulated brain regions and networks. In this case, it is critical to account for confounds introduced by off-target stimulation of peripheral structures of the nervous system that may not only confound MR-based readouts but also induce neuroplastic phenomena.

Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study

Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been proven effective in post-stroke motor function enhancement, yet whether the combination of MI-BCI and tDCS may further benefit the rehabilitation of motor functions remains unknown. This study investigated brain functional activity and connectivity changes after a 2 week MI-BCI and tDCS combined intervention in 19 chronic subcortical stroke patients. Patients were randomized into MI-BCI with tDCS group and MI-BCI only group who underwent 10 sessions of 20 min real or sham tDCS followed by 1 h MI-BCI training with robotic feedback. We derived amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) from resting-state functional magnetic resonance imaging (fMRI) data pre- and post-intervention. At baseline, stroke patients had lower ALFF in the ipsilesional somatomotor network (SMN), lower ReHo in the contralesional insula, and higher ALFF/Reho in the bilateral posterior default mode network (DMN) compared to age-matched healthy controls. After the intervention, the MI-BCI only group showed increased ALFF in contralesional SMN and decreased ALFF/Reho in the posterior DMN. In contrast, no post-intervention changes were detected in the MI-BCI + tDCS group. Furthermore, higher increases in ALFF/ReHo/FC measures were related to better motor function recovery (measured by the Fugl-Meyer Assessment scores) in the MI-BCI group while the opposite association was detected in the MI-BCI + tDCS group. Taken together, our findings suggest that brain functional re-normalization and network-specific compensation were found in the MI-BCI only group but not in the MI-BCI + tDCS group although both groups gained significant motor function improvement post-intervention with no group difference. MI-BCI and tDCS may exert differential or even opposing impact on brain functional reorganization during post-stroke motor rehabilitation; therefore, the integration of the two strategies requires further refinement to improve efficacy and effectiveness.

Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation

Brain-computer interfaces (BCIs) provide a unique technological solution to circumvent the damaged motor system. For neurorehabilitation, the BCI can be used to translate neural signals associated with movement intentions into tangible feedback for the patient, when they are unable to generate functional movement themselves. Clinical interest in BCI is growing rapidly, as it would facilitate rehabilitation to commence earlier following brain damage and provides options for patients who are unable to partake in traditional physical therapy. However, substantial challenges with existing BCI implementations have prevented its widespread adoption. Recent advances in knowledge and technology provide opportunities to facilitate a change, provided that researchers and clinicians using BCI agree on standardisation of guidelines for protocols and shared efforts to uncover mechanisms. We propose that addressing the speed and effectiveness of learning BCI control are priorities for the field, which may be improved by multimodal or multi-stage approaches harnessing more sensitive neuroimaging technologies in the early learning stages, before transitioning to more practical, mobile implementations. Clarification of the neural mechanisms that give rise to improvement in motor function is an essential next step towards justifying clinical use of BCI. In particular, quantifying the unknown contribution of non-motor mechanisms to motor recovery calls for more stringent control conditions in experimental work. Here we provide a contemporary viewpoint on the factors impeding the scalability of BCI. Further, we provide a future outlook for optimal design of the technology to best exploit its unique potential, and best practices for research and reporting of findings.

Task-related brain functional network reconfigurations relate to motor recovery in chronic subcortical stroke

Stroke leads to both regional brain functional disruptions and network reorganization. However, how brain functional networks reconfigure as task demand increases in stroke patients and whether such reorganization at baseline would facilitate post-stroke motor recovery are largely unknown. To address this gap, brain functional connectivity (FC) were examined at rest and motor tasks in eighteen chronic subcortical stroke patients and eleven age-matched healthy controls. Stroke patients underwent a 2-week intervention using a motor imagery-assisted brain computer interface-based (MI-BCI) training with or without transcranial direct current stimulation (tDCS). Motor recovery was determined by calculating the changes of the upper extremity component of the Fugl-Meyer Assessment (FMA) score between pre- and post-intervention divided by the pre-intervention FMA score. The results suggested that as task demand increased (i.e., from resting to passive unaffected hand gripping and to active affected hand gripping), patients showed greater FC disruptions in cognitive networks including the default and dorsal attention networks. Compared to controls, patients had lower task-related spatial similarity in the somatomotor-subcortical, default-somatomotor, salience/ventral attention-subcortical and subcortical-subcortical connections, suggesting greater inefficiency in motor execution. Importantly, higher baseline network-specific FC strength (e.g., dorsal attention and somatomotor) and more efficient brain network reconfigurations (e.g., somatomotor and subcortical) from rest to active affected hand gripping at baseline were related to better future motor recovery. Our findings underscore the importance of studying functional network reorganization during task-free and task conditions for motor recovery prediction in stroke.

Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering

Interdisciplinary combinations of medicine and engineering are part of the strategic plan of many universities aiming to be world-class institutions. One area in which these interactions have been prominent is rehabilitation of stroke hemiplegia. This article reviews advances in the last five years of stroke hemiplegia rehabilitation via interdisciplinary combination of medicine and engineering. Examples of these technologies include VR, RT, mHealth, BCI, tDCS, rTMS, and TCM rehabilitation. In this article, we will summarize the latest research in these areas and discuss the advantages and disadvantages of each to examine the frontiers of interdisciplinary medicine and engineering advances.

Influence of iTBS on the Acute Neuroplastic Change After BCI Training

Objective: Brain-computer interface (BCI) training is becoming increasingly popular in neurorehabilitation. However, around one third subjects have difficulties in controlling BCI devices effectively, which limits the application of BCI training. Furthermore, the effectiveness of BCI training is not satisfactory in stroke rehabilitation. Intermittent theta burst stimulation (iTBS) is a powerful neural modulatory approach with strong facilitatory effects. Here, we investigated whether iTBS would improve BCI accuracy and boost the neuroplastic changes induced by BCI training. Methods: Eight right-handed healthy subjects (four males, age: 20-24) participated in this two-session study (BCI-only session and iTBS+BCI session in random order). Neuroplastic changes were measured by functional near-infrared spectroscopy (fNIRS) and single-pulse transcranial magnetic stimulation (TMS). In BCI-only session, fNIRS was measured at baseline and immediately after BCI training. In iTBS+BCI session, BCI training was followed by iTBS delivered on the right primary motor cortex (M1). Single-pulse TMS was measured at baseline and immediately after iTBS. fNIRS was measured at baseline, immediately after iTBS, and immediately after BCI training. Paired-sample t-tests were used to compare amplitudes of motor-evoked potentials, cortical silent period duration, oxygenated hemoglobin (HbO2) concentration and functional connectivity across time points, and BCI accuracy between sessions. Results: No significant difference in BCI accuracy was detected between sessions (p > 0.05). In BCI-only session, functional connectivity matrices between motor cortex and prefrontal cortex were significantly increased after BCI training (p's < 0.05). In iTBS+BCI session, amplitudes of motor-evoked potentials were significantly increased after iTBS (p's < 0.05), but no change in HbO2 concentration or functional connectivity was observed throughout the whole session (p's > 0.05). Conclusions: To our knowledge, this is the first study that investigated how iTBS targeted on M1 influences BCI accuracy and the acute neuroplastic changes after BCI training. Our results revealed that iTBS targeted on M1 did not influence BCI accuracy or facilitate the neuroplastic changes after BCI training. Therefore, M1 might not be an effective stimulation target of iTBS for the purpose of improving BCI accuracy or facilitate its effectiveness; other brain regions (i.e., prefrontal cortex) are needed to be further investigated as potentially effective stimulation targets.

Progress in Brain Computer Interface: Challenges and Opportunities

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.

Pain relief for osteoarthritis through combined treatment (PROACT): Protocol for a randomized controlled trial of mindfulness meditation combined with transcranial direct current stimulation in non-Hispanic black and white adults with knee osteoarthritis

Knee osteoarthritis (OA) is a leading cause of late life pain and disability, and non-Hispanic black (NHB) adults experience greater OA-related pain and disability than non-Hispanic whites (NHWs). Recent evidence implicates psychosocial stress, cognitive-attentional processes, and altered central pain processing as contributors to greater OA-related pain and disability among NHBs. To address these ethnic/race disparities, this clinical trial will test whether a mindfulness intervention (Breathing and Attention Training, BAT) combined with transcranial direct current stimulation (tDCS) will enhance pain modulatory balance and pain-related brain function, reduce clinical pain, and attenuate ethnic differences therein, among NHBs and NHWs with knee OA. Participants will complete assessments of clinical pain, function, psychosocial measures, and quantitative sensory testing (QST), including mechanical temporal summation and conditioned pain modulation. Neuroimaging will be performed to examine pain-related brain structure and function. Then, participants will be randomized to one of four groups created by crossing two BAT conditions (Real vs. Sham) with two tDCS conditions (Real vs. Sham). Participants will then undergo five treatment sessions during which the assigned BAT and tDCS interventions will be delivered concurrently for 20 min over one week. After the fifth intervention session, participants will undergo assessments of clinical pain and function, QST and neuroimaging identical to the pretreatment measures, and monthly follow-up assessments of pain will be conducted for three months. This will be the first study to determine whether mindfulness and tDCS treatments will show additive or synergistic effects when combined, and whether treatment effects differ across ethnic/race groups.

The Hua-Shan rehabilitation program after contralateral seventh cervical nerve transfer for spastic arm paralysis

Purpose: To propose the novel Hua-Shan rehabilitation program for patients undergoing the contralateral seventh cervical nerve transfer, and explore the influence of different rehabilitation on the postoperative recovery.Materials and methods: The Hua-Shan program was established in consideration of the three elements: the nerve regeneration, brain plasticity and group therapy. Its effect was evaluated by comparing the postoperative recovery of the hemorrhagic stroke survivors among the following three groups: Group A-standard Hua-Shan program after surgery; Group B-standard traditional program after surgery; Group C-no standard rehabilitation after surgery.Results: Significantly better functions after surgery were detected in all the groups, while the absence of standard rehabilitation massively offset the benefits of the surgery. Furthermore, the Hua-Shan program showed advantage over the traditional rehabilitation, which may largely be attributed to its improvements for the fine action of wrist&finger.Conclusions: The Hua-Shan program provided the opportunity to maximize the benefits of contralateral seventh cervical nerve transfer.IMPLICATIONS FOR REHABILITATIONStandard rehabilitation plays key roles in the recovery process for patients undergoing contralateral seventh cervical nerve transfer.The Hua-Shan program targeting nerve regeneration, brain plasticity and group therapy further improved the benefits of patients undergoing contralateral seventh cervical nerve transfer.

Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review

Brain computer interfaces (BCI) for the rehabilitation of motor impairments exploit sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the neurophysiological processes underpinning the SMR often vary over time and across subjects. Inherent intra- and inter-subject variability causes covariate shift in data distributions that impede the transferability of model parameters amongst sessions/subjects. Transfer learning includes machine learning-based methods to compensate for inter-subject and inter-session (intra-subject) variability manifested in EEG-derived feature distributions as a covariate shift for BCI. Besides transfer learning approaches, recent studies have explored psychological and neurophysiological predictors as well as inter-subject associativity assessment, which may augment transfer learning in EEG-based BCI. Here, we highlight the importance of measuring inter-session/subject performance predictors for generalized BCI frameworks for both normal and motor-impaired people, reducing the necessity for tedious and annoying calibration sessions and BCI training.

Rewiring the Lesioned Brain: Electrical Stimulation for Post-Stroke Motor Restoration

Electrical stimulation has been extensively applied in post-stroke motor restoration, but its treatment mechanisms are not fully understood. Stimulation of neuromotor control system at multiple levels manipulates the corresponding neuronal circuits and results in neuroplasticity changes of stroke survivors. This rewires the lesioned brain and advances functional improvement. This review addresses the therapeutic mechanisms of different stimulation modalities, such as noninvasive brain stimulation, peripheral electrical stimulation, and other emerging techniques. The existing applications, the latest progress, and future directions are discussed. The use of electrical stimulation to facilitate post-stroke motor recovery presents great opportunities in terms of targeted intervention and easy applicability. Further technical improvements and clinical studies are required to reveal the neuromodulatory mechanisms and to enhance rehabilitation therapy efficiency in stroke survivors and people with other movement disorders.

tDCS-Enhanced Consolidation of Writing Skills and Its Associations With Cortical Excitability in Parkinson Disease: A Pilot Study

Background. Learning processes of writing skills involve the re-engagement of previously established motor programs affected by Parkinson disease (PD). To counteract the known problems with consolidation in PD, transcranial direct current stimulation (tDCS) could be imperative to achieve a lasting regeneration of habitual motor skills. Objective. To examine tDCS-enhanced learning of writing and explore alterations in cortical excitability after stimulation in PD compared with healthy controls (HCs). Methods. Ten patients and 10 HCs received 2 training sessions combined with 20 minutes of 1-mA anodal tDCS or sham on the left primary motor cortex in a randomized crossover design. Writing skills on a tablet and paper were assessed at baseline, after training, and after 1 week of follow-up. Before and immediately after the intervention, cortical excitability and inhibition were measured during rest and activity. Results. Writing amplitude and velocity improved when practice was tDCS supplemented compared with sham in PD. Benefits were sustained at retention for trained and untrained tasks on the tablet as well as for writing on paper. No improvements were found for HCs. Reduced resting motor thresholds after tDCS indicated tDCS-enhanced cortical excitability. Additionally, increments in motor-evoked potential amplitudes correlated with improved writing in PD, whereas HCs showed the opposite pattern. Conclusion. Our results endorse the usefulness of tDCS-boosted learning in PD, at least when applied to improving writing capacity. Although further confirmatory studies are needed, these novel findings are striking because tDCS-mediated consolidation was found for learning a motor task directly affected by PD.

Quantitative EEG as Biomarkers for the Monitoring of Post-Stroke Motor Recovery in BCI and tDCS Rehabilitation

This study investigates the neurological changes in the brain activity of chronic stroke patients undergoing different types of motor rehabilitative interventions and their relationship with the clinical recovery using the Quantitative Electroencephalography (QEEG) features. Over a period of two weeks, 19 hemiplegic chronic stroke patients underwent 10 sessions of upper extremity motor rehabilitation using a brain-computer interface paradigm (BCI group, n=9) and transcranial direct current stimulation coupled BCI paradigm (tDCS group, n=10). The pre- and post-treatment brain activations, as well as the intervention-induced changes in the neuronal activity, were quantified using 11 QEEG features and their relationship with clinical motor improvement was investigated. Significant treatment-induced change in the relative theta power was observed in the BCI group and the change was significantly correlated with the clinical improvements. Also, in the BCI group, the relative theta power and interactions between the theta, alpha, and beta power were identified as monitory biomarkers of motor recovery. On the contrary, the tDCS group was characterized by the significant change in brain asymmetry. Furthermore, we observed significant intergroup differences in the predictive capabilities of post-intervention QEEG features between the BCI and tDCS group. Based on the intergroup differences observed in this study and convergent results from the other neuroimaging analysis performed on the same cohort, we suggest that distinctly different mechanisms of neuronal recovery were facilitated by tDCS and BCI interventions and these treatment specific mechanisms can be encapsulated using QEEG.

Transcending the brain: is there a cost to hacking the nervous system?

Great advancements have recently been made to understand the brain and the potential that we can extract out of it. Much of this has been centred on modifying electrical activity of the nervous system for improved physical and cognitive performance in those with clinical impairment. However, there is a risk of going beyond purely physiological performance improvements and striving for human enhancement beyond traditional human limits. Simple ethical guidelines and legal doctrine must be examined to keep ahead of technological advancement in light of the impending mergence between biology and machine. By understanding the role of modern ethics, this review aims to appreciate the fine boundary between what is considered ethically justified for current neurotechnology.

Prognostic and Monitory EEG-Biomarkers for BCI Upper-Limb Stroke Rehabilitation

With the availability of multiple rehabilitative interventions, identifying the one that elicits the best motor outcome based on the unique neuro-clinical profile of the stroke survivor is a challenging task. Predicting the potential of recovery using biomarkers specific to an intervention hence becomes important. To address this, we investigate intervention-specific prognostic and monitory biomarkers of motor function improvements using quantitative electroencephalography (QEEG) features in 19 chronic stroke patients following two different upper extremity rehabilitative interventions viz. Brain-computer interface (BCI) and transcranial direct current stimulation coupled BCI (tDCS-BCI). Brain symmetry index was found to be the best prognostic QEEG for clinical gains following BCI intervention ( r = -0.80 , p = 0.02 ), whereas power ratio index (PRI) was observed to be the best predictor for tDCS-BCI ( r = -0.96 , p = 0.004 ) intervention. Importantly, statistically significant between-intervention differences observed in the predictive capabilities of these features suggest that intervention-specific biomarkers can be identified. This approach can be further pursued to distinctly predict the expected response of a patient to available interventions. The intervention with the highest predicted gains may then be recommended to the patient, thereby enabling a personalized rehabilitation regime.

Role of Rehabilitation in Neural Plasticity

AIM

Verifying if physical therapy, neurostimulation techniques, aerobic fitness and video games can induce neural plasticity making it possible for cortical reorganisation, motor recovery in patients, improvement of cognitive functions and transfer of spatial knowledge in the everyday living environment.

METHODS

There have been revised scientific articles respectively focused on the role of pain, the role of physical therapy, neurostimulation techniques and video games in cortical reorganisation. Articles related to the role of pain have taken in the study subjects with pain, to observe its role in cortical reorganisation. Studies related to physical therapy and neurostimulation techniques after cerebrovascular accident consisted of the involvement of these subjects which exposed to different neurostimulations. Also, related to cognition and video games subjects exposed to these interventions for cognitive benefits.

RESULTS

From all articles reviewed there have been effective results of neurostimulation techniques, aerobic fitness and video games in cortical reorganisation inducing neural plasticity (p < 0.05) toward motor recovery, improvement of executive functions and transfer of spatial knowledge.

CONCLUSION

Rehabilitation through locomotor training and neurostimulation techniques, improves mobility in subjects after a cerebrovascular accident due to cortical reorganisation. Also, through aerobic fitness and video games, there have been improvements in cognitive functions. This way, rehabilitation dedicated to the promotion of well-being and health urges beneficial neuroplastic changes in brain corresponding in functional improvement.

Late functional improvement after lacunar stroke: a population-based study

BACKGROUND

Recovery in function after stroke involves neuroplasticity and adaptation to impairments. Few studies have examined differences in late functional improvement beyond 3 months among stroke subtypes, although interventions for late restorative therapies are often studied in lacunar stroke. Therefore, we compared rates of functional improvement beyond 3 months in patients with lacunar versus non-lacunar strokes.

METHODS

In a prospective, population-based cohort of 3-month ischaemic stroke survivors (Oxford Vascular Study; 2002-2014), we examined changes in functional status (modified Rankin Scale (mRS), Rivermead Mobility Index (RMI), Barthel Index (BI)) in patients with lacunar versus non-lacunar strokes from 3 to 60 months poststroke, stratifying by age. We used logistic regression adjusted for age, sex and baseline disability to compare functional improvement (≥1 mRS grades, ≥1 RMI points and/or ≥2 BI points), particularly from 3 to 12 months.

RESULTS

Among 1425 3-month survivors, 234 patients with lacunar stroke did not differ from others in 3-month outcome (adjusted OR (aOR) for 3-month mRS >2 adjusted for age/sex/National Institutes of Health Stroke Scale score/prestroke disability: 1.14, 95% CI 0.75 to 1.74, p=0.55), but were more likely to demonstrate further improvement between 3 months and 1 year (aOR (mRS) adjusted for age/sex/3-month mRS: 1.64, 1.17 to 2.31, p=0.004). The results were similar on restricting analyses to patients with 3-month mRS 2-4 and excluding recurrent events (aOR (mRS): 2.28, 1.34 to 3.86, p=0.002), or examining BI and RMI (aOR (RMI) adjusted for age/sex/3-month RMI: 1.78, 1.20 to 2.64, p=0.004).

CONCLUSION

Patients with lacunar strokes have significant potential for late functional improvement from 3 to 12 months, which should motivate patients and clinicians to maximise late improvements in routine practice. However, since late recovery is common, intervention studies enrolling patients with lacunar strokes should be randomised and controlled.

Differential Amplitude of Low-Frequency Fluctuations in brain networks after BCI Training with and without tDCS in Stroke

Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in upper-limb stroke rehabilitation. Besides functional connectivity, regional amplitude of local low-frequency fluctuations (ALFF) may provide complementary information on the underlying neural mechanism in disease. Yet, findings on spontaneous brain activity during resting-state in stroke patients after intervention are limited and inconsistent. Here, we sought to investigate the different brain alteration patterns induced by tDCS compared to MI-BCI for upper-limb rehabilitation in chronic stroke patients using resting-state fMRI-based ALFF method. Our results suggested that stroke patients have lower ALFF in the ipsilesional somatomotor network compared to controls at baseline. Increased ALFF at contralesional somatomotor network and alterations in higher-level cognitive networks such as the default mode network (DMN) and salience networks accompany motor recovery after intervention; though the MI-BCI alone group and MI-BCI combined with tDCS group exhibit differential patterns.

EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study

In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha-beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI.