Combined rTMS and virtual reality brain-computer interface training for motor recovery after stroke

An Investigation of Parameter-Dependent Cell-Type Specific Effects of Transcranial Focused Ultrasound Stimulation Using an Awake Head-Fixed Rodent Model

Transcranial focused ultrasound (tFUS) is a promising neuromodulation technique able to target shallow and deep brain structures with high precision. Previous studies have demonstrated that tFUS stimulation responses are both cell-type specific and controllable through altering stimulation parameters. Specifically, tFUS can elicit time-locked neural activity in regular spiking units (RSUs) that is sensitive to increases in pulse repetition frequency (PRF), while time-locked responses are not seen in fast spiking units (FSUs). These findings suggest a unique capability of tFUS to alter circuit network dynamics with cell-type specificity; however, these results could be biased by the use of anesthesia, which significantly modulates neural activities. In this study, we develop an awake head-fixed rat model specifically designed for tFUS study, and address a key question if tFUS still has cell-type specificity under awake conditions. Using this novel animal model, we examined a series of PRFs and burst duty cycles (DCs) to determine their effects on neuronal subpopulations without anesthesia. We conclude that cell-type specific time-locked and delayed responses to tFUS as well as PRF and DC sensitivity are present in the awake animal model and that despite some differences in response, isoflurane anesthesia is not a major confound in studying the cell-type specificity of ultrasound neuromodulation. We further determine that, in an awake, head-fixed setting, the preferred PRF and DC for inducing time-locked excitation with our pulsed tFUS paradigm are 1500 Hz and 60%, respectively.

Transcranial focused ultrasound to V5 enhances human visual motion brain-computer interface by modulating feature-based attention

A brain-computer interface (BCI) enables users to control devices with their minds. Despite advancements, non-invasive BCIs still exhibit high error rates, prompting investigation into the potential reduction through concurrent targeted neuromodulation. Transcranial focused ultrasound (tFUS) is an emerging non-invasive neuromodulation technology with high spatiotemporal precision. This study examines whether tFUS neuromodulation can improve BCI outcomes, and explores the underlying mechanism of action using high-density electroencephalography (EEG) source imaging (ESI). As a result, V5-targeted tFUS significantly reduced the error in a BCI speller task. Source analyses revealed a significantly increase in theta and alpha activities in the tFUS condition at both V5 and downstream in the dorsal visual processing pathway. Correlation analysis indicated that the connection within the dorsal processing pathway was preserved during tFUS stimulation, while the ventral connection was weakened. These findings suggest that V5-targeted tFUS enhances feature-based attention to visual motion.

Continuous tracking using deep learning-based decoding for noninvasive brain-computer interface

Brain-computer interfaces (BCI) using electroencephalography provide a noninvasive method for users to interact with external devices without the need for muscle activation. While noninvasive BCIs have the potential to improve the quality of lives of healthy and motor-impaired individuals, they currently have limited applications due to inconsistent performance and low degrees of freedom. In this study, we use deep learning (DL)-based decoders for online continuous pursuit (CP), a complex BCI task requiring the user to track an object in 2D space. We developed a labeling system to use CP data for supervised learning, trained DL-based decoders based on two architectures, including a newly proposed adaptation of the PointNet architecture, and evaluated the performance over several online sessions. We rigorously evaluated the DL-based decoders in a total of 28 human participants, and found that the DL-based models improved throughout the sessions as more training data became available and significantly outperformed a traditional BCI decoder by the last session. We also performed additional experiments to test an implementation of transfer learning by pretraining models on data from other subjects, and midsession training to reduce intersession variability. The results from these experiments showed that pretraining did not significantly improve performance, but updating the models' midsession may have some benefit. Overall, these findings support the use of DL-based decoders for improving BCI performance in complex tasks like CP, which can expand the potential applications of BCI devices and help to improve the quality of lives of healthy and motor-impaired individuals.

Effects of motor imagery-based neurofeedback training after bilateral repetitive transcranial magnetic stimulation on post-stroke upper limb motor function: an exploratory crossover clinical trial

OBJECTIVE

To examine the clinical effects of combining motor imagery-based neurofeedback training with bilateral repetitive transcranial magnetic stimulation for upper limb motor function in subacute and chronic stroke.

DESIGN

Clinical trial following an AB/BA crossover design with counterbalanced assignment.

SUBJECTS

Twenty individuals with subacute (n = 4) or chronic stroke (n = 16).

METHODS

Ten consecutive sessions of bilateral repetitive transcranial magnetic stimulation alone (therapy A) were compared vs a combination of10 consecutive sessions of bilateral repetitive transcranial magnetic stimulation with 12 non-consecutive sessions of motor imagery-based neurofeedback training (therapy B). Patients received both therapies (1-month washout period), in sequence AB or BA. Participants were assessed before and after each therapy and at 15-days follow-up, using the Fugl-Meyer Assessment-upper limb, hand-grip strength, and the Nottingham Sensory Assessment as primary outcome measures.

RESULTS

Both therapies resulted in improved functionality and sensory function. Therapy B consistently exhibited superior effects compared with therapy A, according to Fugl-Meyer Assessment and tactile and kinaesthetic sensory function across multiple time-points, irrespective of treatment sequence. No statistically significant differences between therapies were found for hand-grip strength.

CONCLUSION

Following subacute and chronic stroke, integrating bilateral repetitive transcranial magnetic stimulation and motor imagery-based neurofeedback training has the potential to enhance functional performance compared with using bilateral repetitive transcranial magnetic stimulation alone in upper limb recovery.

Favoring the cognitive-motor process in the closed-loop of BCI mediated post stroke motor function recovery: challenges and approaches

The brain-computer interface (BCI)-mediated rehabilitation is emerging as a solution to restore motor skills in paretic patients after stroke. In the human brain, cortical motor neurons not only fire when actions are carried out but are also activated in a wired manner through many cognitive processes related to movement such as imagining, perceiving, and observing the actions. Moreover, the recruitment of motor cortexes can usually be regulated by environmental conditions, forming a closed-loop through neurofeedback. However, this cognitive-motor control loop is often interrupted by the impairment of stroke. The requirement to bridge the stroke-induced gap in the motor control loop is promoting the evolution of the BCI-based motor rehabilitation system and, notably posing many challenges regarding the disease-specific process of post stroke motor function recovery. This review aimed to map the current literature surrounding the new progress in BCI-mediated post stroke motor function recovery involved with cognitive aspect, particularly in how it refired and rewired the neural circuit of motor control through motor learning along with the BCI-centric closed-loop.

Graph analysis of cortical reorganization after virtual reality-based rehabilitation following stroke: a pilot randomized study

Introduction

Stroke is the leading cause of functional disability worldwide. With the increase of the global population, motor rehabilitation of stroke survivors is of ever-increasing importance. In the last decade, virtual reality (VR) technologies for rehabilitation have been extensively studied, to be used instead of or together with conventional treatments such as physiotherapy or occupational therapy. The aim of this work was to evaluate the GestureCollection VR-based rehabilitation tool in terms of the brain changes and clinical outcomes of the patients.

Methods

Two groups of chronic patients underwent a rehabilitation treatment with (experimental) or without (control) complementation with GestureCollection. Functional magnetic resonance imaging exams and clinical assessments were performed before and after the treatment. A functional connectivity graph-based analysis was used to assess differences between the connections and in the network parameters strength and clustering coefficient.

Results

Patients in both groups showed improvement in clinical scales, but there were more increases in functional connectivity in the experimental group than in the control group.

Discussion

The experimental group presented changes in the connections between the frontoparietal and the somatomotor networks, associative cerebellum and basal ganglia, which are regions associated with reward-based motor learning. On the other hand, the control group also had results in the somatomotor network, in its ipsilateral connections with the thalamus and with the motor cerebellum, which are regions more related to a purely mechanical activity. Thus, the use of the GestureCollection system was successfully shown to promote neuroplasticity in several motor-related areas.

Challenges of neural interfaces for stroke motor rehabilitation

More than 85% of stroke survivors suffer from different degrees of disability for the rest of their lives. They will require support that can vary from occasional to full time assistance. These conditions are also associated to an enormous economic impact for their families and health care systems. Current rehabilitation treatments have limited efficacy and their long-term effect is controversial. Here we review different challenges related to the design and development of neural interfaces for rehabilitative purposes. We analyze current bibliographic evidence of the effect of neuro-feedback in functional motor rehabilitation of stroke patients. We highlight the potential of these systems to reconnect brain and muscles. We also describe all aspects that should be taken into account to restore motor control. Our aim with this work is to help researchers designing interfaces that demonstrate and validate neuromodulation strategies to enforce a contingent and functional neural linkage between the central and the peripheral nervous system. We thus give clues to design systems that can improve or/and re-activate neuroplastic mechanisms and open a new recovery window for stroke patients.

Transcranial Focused Ultrasound to V5 Enhances Human Visual Motion Brain-Computer Interface by Modulating Feature-Based Attention

Paralysis affects roughly 1 in 50 Americans. While there is no cure for the condition, brain-computer interfaces (BCI) can allow users to control a device with their mind, bypassing the paralyzed region. Non-invasive BCIs still have high error rates, which is hypothesized to be reduced with concurrent targeted neuromodulation. This study examines whether transcranial focused ultrasound (tFUS) modulation can improve BCI outcomes, and what the underlying mechanism of action might be through high-density electroencephalography (EEG)-based source imaging (ESI) analyses. V5-targeted tFUS significantly reduced the error for the BCI speller task. ESI analyses showed significantly increased theta activity in the tFUS condition at both V5 and downstream the dorsal visual processing pathway. Correlation analysis indicates that the dorsal processing pathway connection was preserved during tFUS stimulation, whereas extraneous connections were severed. These results suggest that V5-targeted tFUS' mechanism of action is to raise the brain's feature-based attention to visual motion.

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.

Post-Stroke Rehabilitation of Distal Upper Limb with New Perspective Technologies: Virtual Reality and Repetitive Transcranial Magnetic Stimulation-A Mini Review

Upper extremity motor impairment is the most common sequelae in patients with stroke. Moreover, its continual nature limits the optimal functioning of patients in the activities of daily living. Because of the intrinsic limitations in the conventional form of rehabilitation, the rehabilitation applications have been expanded to technology-driven solutions, such as Virtual Reality and Repetitive Transcranial Magnetic Stimulation (rTMS). The motor relearning processes are influenced by variables, such as task specificity, motivation, and feedback provision, and a VR environment in the form of interactive games could provide novel and motivating customized training solutions for better post-stroke upper limb motor improvement. rTMS being a precise non-invasive brain stimulation method with good control of stimulation parameters, has the potential to facilitate neuroplasticity and hence a good recovery. Although several studies have discussed these forms of approaches and their underlying mechanisms, only a few of them have specifically summarized the synergistic applications of these paradigms. To bridge the gaps, this mini review presents recent research and focuses precisely on the applications of VR and rTMS in distal upper limb rehabilitation. It is anticipated that this article will provide a better representation of the role of VR and rTMS in distal joint upper limb rehabilitation in patients with stroke.

Effectiveness of Repetitive Transcranial Magnetic Stimulation Combined with Visual Feedback Training in Improving Neuroplasticity and Lower Limb Function after Chronic Stroke: A Pilot Study

After a stroke, sustained gait impairment can restrict participation in the activities listed in the International Classification of Functioning, Disability, and Health model and cause poor quality of life. The present study investigated the effectiveness of repetitive transcranial magnetic stimulation (rTMS) and visual feedback training (VF) training in improving lower limb motor performance, gait, and corticospinal excitability in patients with chronic stroke. Thirty patients were randomized into three groups that received either rTMS or sham stimulation over the contralesional leg region accompanied by VF training groups in addition to the conventional rehabilitation group. All participants underwent intervention sessions three times per week for four weeks. Outcome measures included the motor-evoked potential (MEP) of the anterior tibialis muscle, Berg Balance Scale (BBS) scores, Timed Up and Go (TUG) test scores, and Fugl–Meyer Assessment of Lower Extremity scores. After the intervention, the rTMS and VF group had significantly improved in MEP latency (p = 0.011), TUG scores (p = 0.008), and BBS scores (p = 0.011). The sham rTMS and VF group had improved MEP latency (p = 0.027). The rTMS and VF training may enhance the cortical excitability and walking ability of individuals with chronic stroke. The potential benefits encourage a larger trial to determine the efficacy in stroke patients.

Evaluating the effectiveness of the safety experience room, an affordable interactive education intervention to prevent unintentional injury among rural preschoolers in China: protocol for a cluster randomized controlled trial

BACKGROUND

Interactive and experiential learning programs have proven effective to teach children safety and prevent child unintentional injury. However, previously-published programs were designed primarily to address safety concerns of children living in urban, well-resourced areas, and therefore might be less effective or economically infeasible to distribute to children in resource-limited areas, such as those living in rural areas or underdeveloped regions. This proposed study will evaluate the effectiveness of teaching children safety lessons to rural preschoolers in China through the preschool-based Safety Experience Room intervention that was developed based on relevant theories, the lessons of previous intervention research, the characteristics of child injuries in underdeveloped rural areas, and the needs and circumstances of rural families and preschools in China. The study will also evaluate the cost-effectiveness of delivering the program.

METHODS AND ANALYSIS

A single-blinded, 12-month follow-up, parallel-group cluster randomized controlled trial with a 1:1 allocation ratio will be implemented in two selected counties. In total, at least 2378 rural preschoolers aged 3-6 years old will be recruited from 12 preschools, 6 in Yang County and 6 in Shicheng County. Clusters will be randomized at the preschool level and allocated to the control group (routine school-based education) or the intervention group (routine school-based education plus the Safety Experience Room education). External support strategies will be implemented by local partners to minimize attrition. Data collection will be conducted at baseline and then every 3 months during a 12-month follow-up time period. Intention-to-treat (ITT) data analysis will be used. Generalized estimation equations (GEE) will evaluate the effectiveness of the program and generalized cost-effectiveness analysis (GCEA) will evaluate the cost-effectiveness of it. A per-protocol (PP) sensitivity analysis will assess the robustness of ITT results. Subgroup analyses will be performed to evaluate the impact of socio-demographic factors on the intervention effect, following the same strategies as the primary analyses.

DISCUSSION

The newly-designed Safety Experience Room program is expected to be feasible, effective, and financially beneficial. If these hypotheses prove true, we will take steps to disseminate the program to rural preschools across China.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ( http://www.chictr.org.cn ), CHiCTR2000038025, registered on 8 September 2020.

Virtual reality-induced motor function of the upper extremity and brain activation in stroke: study protocol for a randomized controlled trial

Background

The benefits of virtual reality (VR)-based rehabilitation were reported in patients after stroke, but there is insufficient evidence about how VR promotes brain activation in the central nervous system. Hence, we designed this study to explore the effects of VR-based intervention on upper extremity motor function and associated brain activation in stroke patients.

Methods/design

In this single-center, randomized, parallel-group clinical trial with a blinded assessment of outcomes, a total of 78 stroke patients will be assigned randomly to either the VR group or the control group. All stroke patients who have upper extremity motor deficits will be tested with functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and clinical evaluation. Clinical assessment and fMRI will be performed three times on each subject. The primary outcome is the change in performance on the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE). Secondary outcomes are functional independence measure (FIM), Barthel Index (BI), grip strength, and changes in the blood oxygenation level-dependent (BOLD) effect in the ipsilesional and contralesional primary motor cortex (M1) on the left and right hemispheres assessed with resting-state fMRI (rs-fMRI), task-state fMRI (ts-fMRI), and changes in EEG at the baseline and weeks 4 and 8.

Discussion

This study aims to provide high-quality evidence for the relationship between upper extremity motor function and brain activation in stroke. In addition, this is the first multimodal neuroimaging study that explores the evidence for neuroplasticity and associated upper motor function recovery after VR in stroke patients.

Clinical trial registration

Chinese Clinical Trial Registry, identifier: ChiCTR2200063425.

BCI-FES With Multimodal Feedback for Motor Recovery Poststroke

An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals-user-generated intent-to-move neural activity recorded from cerebral cortical motor areas-to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.

Motor Imagery: How to Assess, Improve Its Performance, and Apply It for Psychosis Diagnostics

With this review, we summarize the state-of-the-art of scientific studies in the field of motor imagery (MI) and motor execution (ME). We composed the brain map and description that correlate different brain areas with the type of movements it is responsible for. That gives a more complete and systematic picture of human brain functionality in the case of ME and MI. We systematized the most popular methods for assessing the quality of MI performance and discussed their advantages and disadvantages. We also reviewed the main directions for the use of transcranial magnetic stimulation (TMS) in MI research and considered the principal effects of TMS on MI performance. In addition, we discuss the main applications of MI, emphasizing its use in the diagnostics of various neurodegenerative disorders and psychoses. Finally, we discuss the research gap and possible improvements for further research in the field.

The Frequency Effect of the Motor Imagery Brain Computer Interface Training on Cortical Response in Healthy Subjects: A Randomized Clinical Trial of Functional Near-Infrared Spectroscopy Study

Background

The motor imagery brain computer interface (MI-BCI) is now available in a commercial product for clinical rehabilitation. However, MI-BCI is still a relatively new technology for commercial rehabilitation application and there is limited prior work on the frequency effect. The MI-BCI has become a commercial product for clinical neurological rehabilitation, such as rehabilitation for upper limb motor dysfunction after stroke. However, the formulation of clinical rehabilitation programs for MI-BCI is lack of scientific and standardized guidance, especially limited prior work on the frequency effect. Therefore, this study aims at clarifying how frequency effects on MI-BCI training for the plasticity of the central nervous system.

Methods

Sixteen young healthy subjects (aged 22.94 ± 3.86 years) were enrolled in this randomized clinical trial study. Subjects were randomly assigned to a high frequency group (HF group) and low frequency group (LF group). The HF group performed MI-BCI training once per day while the LF group performed once every other day. All subjects performed 10 sessions of MI-BCI training. functional near-infrared spectroscopy (fNIRS) measurement, Wolf Motor Function Test (WMFT) and brain computer interface (BCI) performance were assessed at baseline, mid-assessment (after completion of five BCI training sessions), and post-assessment (after completion of 10 BCI training sessions).

Results

The results from the two-way ANOVA of beta values indicated that GROUP, TIME, and GROUP × TIME interaction of the right primary sensorimotor cortex had significant main effects [GROUP: F_(1,14) = 7.251, P = 0.010; TIME: F_(2,13) = 3.317, P = 0.046; GROUP × TIME: F_(2,13) = 5.676, P = 0.007]. The degree of activation was affected by training frequency, evaluation time point and interaction. The activation of left primary sensory motor cortex was also affected by group (frequency) (P = 0.003). Moreover, the TIME variable was only significantly different in the HF group, in which the beta value of the mid-assessment was higher than that of both the baseline assessment (P = 0.027) and post-assessment (P = 0.001), respectively. Nevertheless, there was no significant difference in the results of WMFT between HF group and LF group.

Conclusion

The major results showed that more cortical activation and better BCI performance were found in the HF group relative to the LF group. Moreover, the within-group results also showed more cortical activation after five sessions of BCI training and better BCI performance after 10 sessions in the HF group, but no similar effects were found in the LF group. This pilot study provided an essential reference for the formulation of clinical programs for MI-BCI training in improvement for upper limb dysfunction.

Effects of virtual reality-based motor rehabilitation: a systematic review of fMRI studies

BACKGROUND

The use of virtual reality (VR) as a rehabilitation tool has been shown to induce motor and cognitive improvements in different populations. Functional magnetic resonance imaging (fMRI) has been used to investigate neuroplasticity resulting from these treatments. We hypothesize that VR rehabilitation induces functional improvement and brain changes that can be detected by fMRI.

OBJECTIVE

To systematically review the effects of VR intervention on the cortical reorganization measured by fMRI and associated with functional improvement.

METHODS

We performed a systematic review of studies published between 2005 and 2021. Papers were retrieved from six databases using the following keywords: "motor rehabilitation", "fMRI" and "virtual reality". Case studies, pre-post studies, cross-sectional studies, and randomized controlled trials published were included. Manuscripts were assessed by The NIH Study Quality Assessment Tools to determine their quality.

RESULTS

Twenty-three articles met our eligibility criteria: 18 about VR rehabilitation in stroke and five on other clinical conditions (older adults, cerebral palsy, and Parkinson's disease). Changes in neural patterns of activation and reorganization were revealed in both the ipsilesional and the contralesional hemispheres. Results were located mainly in the primary motor cortex, sensorimotor cortex and supplementary motor area in post-stroke patients in the acute, subacute, and chronic rehabilitation phases, and were associated with functional improvement after VR intervention. Similar effects were observed in older adults and in patients with other neurological diseases with improved performance.

CONCLUSION

Most stroke-related studies showed either restoration to normal or increase of activation patterns or relateralization at/to the ipsilesional hemisphere, with some also reporting a decrease in activity or extent of activation after VR therapy. In general, VR intervention demonstrated evidence of efficacy both in neurological rehabilitation and in performance improvement of older adults, accompanied by fMRI evidence of brain reorganization.

The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia

Background: Motor attempt and motor imagery (MI) are two common motor tasks used in brain-computer interface (BCI). They are widely researched for motor rehabilitation in patients with hemiplegia. The differences between the motor attempt (MA) and MI tasks of patients with hemiplegia can be used to promote BCI application. This study aimed to explore the accuracy of BCI and event-related desynchronization (ERD) between the two tasks.

Materials and Methods: We recruited 13 patients with stroke and 3 patients with traumatic brain injury, to perform MA and MI tasks in a self-control design. The BCI accuracies from the bilateral, ipsilesional, and contralesional hemispheres were analyzed and compared between different tasks. The cortical activation patterns were evaluated with ERD and laterality index (LI).

Results: The study showed that the BCI accuracies of MA were significantly (p < 0.05) higher than MI in the bilateral, ipsilesional, and contralesional hemispheres in the alpha-beta (8–30 Hz) frequency bands. There was no significant difference in ERD and LI between the MA and MI tasks in the 8–30 Hz frequency bands. However, in the MA task, there was a negative correlation between the ERD values in the channel CP1 and ipsilesional hemispheric BCI accuracies (r = −0.552, p = 0.041, n = 14) and a negative correlation between the ERD values in channel CP2 and bilateral hemispheric BCI accuracies (r = −0.543, p = 0.045, n = 14). While in the MI task, there were negative correlations between the ERD values in channel C4 and bilateral hemispheric BCI accuracies (r = −0.582, p = 0.029, n = 14) as well as the contralesional hemispheric BCI accuracies (r = −0.657, p = 0.011, n = 14). As for motor dysfunction, there was a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 8–13 Hz (r = 0.565, p = 0.035, n = 14) in the MA task and a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 13–30 Hz (r = 0.558, p = 0.038, n = 14) in the MI task.

Conclusion: The MA task may achieve better BCI accuracy but have similar cortical activations with the MI task. Cortical activation (ERD) may influence the BCI accuracy, which should be carefully considered in the BCI motor rehabilitation of patients with hemiplegia.

Investigation of displacement of intracranial electrode induced by focused ultrasound stimulation

Transcranial focused ultrasound (tFUS) is an emerging neuromodulation technique to modulate brain activity non-invasively with high spatial specificity and focality. Given the influence of tFUS on brain activity, combining tFUS with multi-channel intracranial electrophysiological recordings enables monitoring of the activity of large populations of neurons with high temporal resolution. However, the physical interactions between tFUS and the electrode may affect a reliable assessment of neuronal activity, which remains poorly understood. In this paper, high-frequency ultrasound (HFUS) system was developed and integrated into tFUS neuromodulation system. The performance of the HFUS-based displacement tracking and analysis was evaluated by the theoretical analysis in the literature. The effects of various pressure levels on the displacements of the silicon-based microelectrode array in ex vivo brain tissue were investigated. The developed approach was capable of tracking and measuring the motion of a solid sphere in a tissue-mimicking phantom and measured displacements were comparable to theoretical predictions. The significant changes in the averaged peak displacements of the microelectrode array in ex vivo brain were observed with a pulse duration of 200 μs and a peak-to-peak pressure from 131 kPa at a center frequency of 500 kHz compared with the values from the negative control group. The present results demonstrate the relationship between several pressure levels and displacements of the microelectrode array in ex vivo brain through the developed approach. This approach can be used to determine a vibration-free threshold of ultrasound parameters in multi-channel intracranial recordings for a reliable assessment of electrophysiological activities of living neurons.

5 Hz rTMS improves motor-imagery based BCI classification performance

Brain-computer interface (BCI) based rehabilitation has been proven a promising method facilitating motor recovery. Recognizing motor intention is crucial for realizing BCI rehabilitation training. Event-related desynchronization (ERD) is a kind of electroencephalogram (EEG) inherent characteristics associated with motor intention. However, due to brain deficits poststroke, some patients are not able to generate ERD, which discourages them to be involved in BCI rehabilitation training. To boost ERD during motor imagery (MI), this paper investigates the effects of high-frequency repetitive transcranial magnetic stimulation (rTMS) on BCI classification performance. Eleven subjects participated in this study. The experiment consisted of two conditions: rTMS + MI versus sham rTMS + MI, which were arranged on different days. MI tests with 64-channel EEG recording were arranged immediately before and after rTMS and sham rTMS. Time-frequency analysis were utilized to measure ERD changes. Common spatial pattern was used to extract features and linear discriminant analysis was used to calculate offline classification accuracies. Paired-sample t-test and Wilcoxon signed rank tests with post-hoc analysis were used to compare performance before and after stimulation. Statistically stronger ERD (-13.93±12.99%) was found after real rTMS compared with ERD (-5.71±21.25%) before real rTMS (p<0.05). Classification accuracy after real rTMS (70.71±10.32%) tended to be higher than that before real rTMS (66.50±8.48%) (p<0.1). However, no statistical differences were found after sham stimulation. This research provides an effective method in improving BCI performance by utilizing neural modulation.Clinical Relevance- This study offers a promising treatment for patients who cannot be recruited in BCI rehabilitation training due to poor BCI classification performance.

Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication

During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. Most studies have investigated emotions using functional magnetic resonance imaging (fMRI), including the real-time application in neurofeedback training. However, the electroencephalogram (EEG) is a more suitable tool for therapeutic application. Our study aims at establishing a method to classify discrete complex emotions (e.g., tenderness and anguish) elicited through a near-immersive scenario that can be later used for EEG-neurofeedback. EEG-based affective computing studies have mainly focused on emotion classification based on dimensions, commonly using passive elicitation through single-modality stimuli. Here, we integrated both passive and active elicitation methods. We recorded electrophysiological data during emotion-evoking trials, combining emotional self-induction with a multimodal virtual environment. We extracted correlational and time-frequency features, including frontal-alpha asymmetry (FAA), using Complex Morlet Wavelet convolution. Thinking about future real-time applications, we performed within-subject classification using 1-s windows as samples and we applied trial-specific cross-validation. We opted for a traditional machine-learning classifier with low computational complexity and sufficient validation in online settings, the Support Vector Machine. Results of individual-based cross-validation using the whole feature sets showed considerable between-subject variability. The individual accuracies ranged from 59.2 to 92.9% using time-frequency/FAA and 62.4 to 92.4% using correlational features. We found that features of the temporal, occipital, and left-frontal channels were the most discriminative between the two emotions. Our results show that the suggested pipeline is suitable for individual-based classification of discrete emotions, paving the way for future personalized EEG-neurofeedback training.

Structural connectivity changes in the motor execution network after stroke rehabilitation

Background:

Although quite a very few studies have tested structural connectivity changes following an intervention, it reflects only selected key brain regions in the motor network. Thus, the understanding of structural connectivity changes related to the motor recovery process remains unclear.

Objective:

This study investigated structural connectivity changes of the motor execution network following a combined intervention of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) and intensive occupational therapy (OT) after a stroke using graph theory approach.

Methods:

Fifty-six stroke patients underwent Fugl-Meyer Assessment (FMA), Wolf Motor Function Test-Functional Ability Scale (WMFT-FAS), diffusion tensor imaging (DTI), and T1 weighted imaging before and after the intervention. We examined graph theory measures related to twenty brain regions using structural connectomes.

Results:

The ipsilesional and contralesional hemisphere showed structural connectivity changes post-intervention after stroke. We found significantly increased regional centralities and nodal efficiency within the frontal pole and decreased degree centrality and nodal efficiency in the ipsilesional thalamus. Correlations were found between network measures and clinical assessments in the cuneus, postcentral gyrus, precentral gyrus, and putamen of the ipsilesional hemisphere. The contralesional areas such as the caudate, cerebellum, and frontal pole also showed significant correlations.

Conclusions:

This study was helpful to expand the understanding of structural connectivity changes in both hemispheric networks during the motor recovery process following LF-rTMS and intensive OT after stroke.

Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation

Brain-computer interfaces (BCIs) designed for motor rehabilitation use brain signals associated with motor-processing states to guide neuroplastic changes in a state-dependent manner. These technologies are uniquely positioned to induce targeted and functionally relevant plastic changes in the human motor nervous system. However, while several studies have shown that BCI-based neuromodulation interventions may improve motor function in patients with lesions in the central nervous system, the neurophysiological structures and processes targeted with the BCI interventions have not been identified. In this review, we first summarize current knowledge of the changes in the central nervous system associated with learning new motor skills. Then, we propose a classification of current BCI paradigms for plasticity induction and motor rehabilitation based on the expected neural plastic changes promoted. This classification proposes four paradigms based on two criteria: the plasticity induction methods and the brain states targeted. The existing evidence regarding the brain circuits and processes targeted with these different BCIs is discussed in detail. The proposed classification aims to serve as a starting point for future studies trying to elucidate the underlying plastic changes following BCI interventions.

Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation

Recent advances in brain-computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily living and personal goals. Here we evaluate the principles, benefits, challenges, and future directions of brain-computer interfaces in the context of neurorehabilitation. We then explore the clinical translation of these technologies and propose an approach to facilitate implementation of brain-computer interfaces for persons with neurologic disease.

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.

Theta burst stimulation over the prefrontal cortex: Effects on cerebral oximetry and cardiovascular measures in healthy humans

Theta Burst Stimulation (TBS) is a non-invasive neurophysiological technique, able to induce changes in synaptic activity. Research suggests that TBS may induce changes in cerebral oxygenation, cerebral blood flow, blood pressure and heart rate but there are conflicting results across studies. Thus, the objective of our sham-controlled study is to evaluate if TBS applied to the dorsolateral prefrontal cortex (DLPFC) of healthy volunteers produces changes in cerebral oximetry, heart rate and blood pressure. Forty-nine volunteers of both sexes were randomly allocated to one of five stimulation groups. Before and after real TBS or sham stimulation, blood pressure, heart rate, and cerebral oxygenation of the volunteers were measured. Cerebral oxygenation values were obtained with a near infra-red spectroscopy system. We found a significant reduction in left cortex oximetry after continuous TBS (cTBS) over the left DLPFC (p = 0.039) and a non-significant reduction in right cortex oximetry (p = 0.052). Right hemisphere inhibition (using cTBS) seemed to originate a significant reduction of 8 mmHg in systolic arterial pressure. No other changes were seen in oximetry, cardiac frequency and diastolic arterial pressure. In our group of normal subjects, cTBS applied to the left DLPFC was able to reduce oxygenation in the left cortex. Right hemisphere inhibition was associated with a significant reduction in systolic pressure.

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.

Noninvasive Brain Stimulation & Space Exploration: Opportunities and Challenges

As NASA prepares for longer space missions aiming for the Moon and Mars, astronauts' health and performance are becoming a central concern due to the threats associated with galactic cosmic radiation, unnatural gravity fields, and life in extreme environments. In space, the human brain undergoes functional and structural changes related to fluid shift and changes in intracranial pressure. Behavioral abnormalities, such as cognitive deficits, sleep disruption, and visuomotor difficulties, as well as psychological effects, are also an issue. We discuss opportunities and challenges of noninvasive brain stimulation (NiBS) methods - including transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) - to support space exploration in several ways. NiBS includes safe and portable techniques already applied in a wide range of cognitive and motor domains, as well as therapeutically. NiBS could be used to enhance in-flight performance, supporting astronauts during pre-flight Earth-based training, as well as to identify biomarkers of post-flight brain changes for optimization of rehabilitation/compensatory strategies. We review these NiBS techniques and their effects on brain physiology, psychology, and cognition.

Virtual reality and non-invasive brain stimulation for rehabilitation applications: a systematic review

The present article reports the results of a systematic review on the potential benefits of the combined use of virtual reality (VR) and non-invasive brain stimulation (NIBS) as a novel approach for rehabilitation. VR and NIBS are two rehabilitation techniques that have been consistently explored by health professionals, and in recent years there is strong evidence of the therapeutic benefits of their combined use. In this work, we reviewed research articles that report the combined use of VR and two common NIBS techniques, namely transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS). Relevant queries to six major bibliographic databases were performed to retrieve original research articles that reported the use of the combination VR-NIBS for rehabilitation applications. A total of 16 articles were identified and reviewed. The reviewed studies have significant differences in the goals, materials, methods, and outcomes. These differences are likely caused by the lack of guidelines and best practices on how to combine VR and NIBS techniques. Five therapeutic applications were identified: stroke, neuropathic pain, cerebral palsy, phobia and post-traumatic stress disorder, and multiple sclerosis rehabilitation. The majority of the reviewed studies reported positive effects of the use of VR-NIBS. However, further research is still needed to validate existing results on larger sample sizes and across different clinical conditions. For these reasons, in this review recommendations for future studies exploring the combined use of VR and NIBS are presented to facilitate the comparison among works.

Improving performance in motor imagery BCI-based control applications via virtually embodied feedback

OBJECTIVE

Brain-computer interfaces (BCIs) based on motor imagery (MI) are commonly used for control applications. However, these applications require strong and discriminant neural patterns for which extensive experience in MI may be necessary. Inspired by the field of rehabilitation where embodiment is a key element for improving cortical activity, our study proposes a novel control scheme in which virtually embodiable feedback is provided during control to enhance performance.

METHODS

Subjects underwent two immersive virtual reality control scenarios in which they controlled the two-dimensional movement of a device using electroencephalography (EEG). The two scenarios only differ on whether embodiable feedback, which mirrors the movement of the classified intention, is provided. After undergoing each scenario, subjects also answered a questionnaire in which they rated how immersive the scenario and embodiable the feedback were.

RESULTS

Subjects exhibited higher control performance, greater discriminability in brain activity patterns, and enhanced cortical activation when using our control scheme compared to the standard control scheme in which embodiable feedback is absent. Moreover, the self-rated embodiment and presence scores showed significantly positive linear relationships with performance.

SIGNIFICANCE

The findings in our study provide evidence that providing embodiable feedback as guidance on how intention is classified may be effective for control applications by inducing enhanced neural activity and patterns with greater discriminability. By applying embodiable feedback to immersive virtual reality, our study also serves as another instance in which virtual reality is shown to be a promising tool for improving MI.

Clinical Application of Virtual Reality for Upper Limb Motor Rehabilitation in Stroke: Review of Technologies and Clinical Evidence

Neurorehabilitation for stroke is important for upper limb motor recovery. Conventional rehabilitation such as occupational therapy has been used, but novel technologies are expected to open new opportunities for better recovery. Virtual reality (VR) is a technology with a set of informatics that provides interactive environments to patients. VR can enhance neuroplasticity and recovery after a stroke by providing more intensive, repetitive, and engaging training due to several advantages, including: (1) tasks with various difficulty levels for rehabilitation, (2) augmented real-time feedback, (3) more immersive and engaging experiences, (4) more standardized rehabilitation, and (5) safe simulation of real-world activities of daily living. In this comprehensive narrative review of the application of VR in motor rehabilitation after stroke, mainly for the upper limbs, we cover: (1) the technologies used in VR rehabilitation, including sensors; (2) the clinical application of and evidence for VR in stroke rehabilitation; and (3) considerations for VR application in stroke rehabilitation. Meta-analyses for upper limb VR rehabilitation after stroke were identified by an online search of Ovid-MEDLINE, Ovid-EMBASE, the Cochrane Library, and KoreaMed. We expect that this review will provide insights into successful clinical applications or trials of VR for motor rehabilitation after stroke.

Virtual Reality Meets Non-invasive Brain Stimulation: Integrating Two Methods for Cognitive Rehabilitation of Mild Cognitive Impairment

Mild cognitive impairment (MCI) refers to a subtle, general cognitive decline with a detrimental impact on elderlies' independent living and quality of life. Without a timely diagnosis, this condition can evolve into dementia over time, hence the crucial need for early detection, prevention, and rehabilitation. For this purpose, current neuropsychological interventions have been integrated with (i) virtual reality, which immerses the user in a controlled, ecological, and safe environment (so far, both virtual reality-based cognitive and motor rehabilitation have revealed promising positive outcomes); and (ii) non-invasive brain stimulation, i.e., transcranial magnetic or electric brain stimulation, which has emerged as a promising cognitive treatment for MCI and Alzheimer's dementia. To date, these two methods have been employed separately; only a few studies (limited to motor rehabilitation) have suggested their integration. The present paper suggests to extend this integration to cognitive rehabilitation as well as to provide a multimodal stimulation that could enhance cognitive training, resulting in a more efficient rehabilitation.

Neuromodulation Management of Chronic Neuropathic Pain in The Central Nervous system

Neuromodulation is becoming one of the clinical tools for treating chronic neuropathic pain by transmitting controlled physical energy to the pre-identified neural targets in the central nervous system. Its nature of drug-free, non-addictive and improved targeting have attracted increasing attention among neuroscience research and clinical practices. This article provides a brief overview of the neuropathic pain and pharmacological routines for treatment, summarizes both the invasive and non-invasive neuromodulation modalities for pain management, and highlights an emerging brain stimulation technology, transcranial focused ultrasound (tFUS) with a focus on ultrasound transducer devices and the achieved neuromodulation effects and applications on pain management. Practical considerations of spatial guidance for tFUS are discussed for clinical applications. The safety of transcranial ultrasound neuromodulation and its future prospectives on pain management are also discussed.

Strengthening the perception of the virtual worlds in a virtual reality environment

Virtual reality is becoming more and more improved primarily due to numerous applications and the powers of mobile devices. Using various sensors, precise displays and high computing powers smartphone are becoming devices that make the boost in technology. Now it is necessary to efficiently use various sensors without affecting system operation and improve control abilities for various purposes. Especially in practical applications received by mass users such as games and any kind of experience. In this article, we propose a system that allows to extend the perception of the virtual world by conveying information about the user's movements in reality into the supervised model. The system retrieves data from several sources, quickly analyzes them using artificial intelligence techniques, and returns information to the mobile phone about the activity that is being processed. The concept extends the understanding of today's virtual reality by allowing the user to move and perform simple gestures in a specially designed room. Moreover, we propose multiplayer mode in virtual reality, where players are in different places. The proposed architecture of the system has been tested on simple applications, and the results show high potential for implementations in various apps by achieving almost 90% efficiency in changing player direction in real time and only 7.5% of collision cases.

Embodiment Is Related to Better Performance on a Brain-Computer Interface in Immersive Virtual Reality: A Pilot Study

Electroencephalography (EEG)-based brain-computer interfaces (BCIs) for motor rehabilitation aim to "close the loop" between attempted motor commands and sensory feedback by providing supplemental information when individuals successfully achieve specific brain patterns. Existing EEG-based BCIs use various displays to provide feedback, ranging from displays considered more immersive (e.g., head-mounted display virtual reality (HMD-VR)) to displays considered less immersive (e.g., computer screens). However, it is not clear whether more immersive displays improve neurofeedback performance and whether there are individual performance differences in HMD-VR versus screen-based neurofeedback. In this pilot study, we compared neurofeedback performance in HMD-VR versus a computer screen in 12 healthy individuals and examined whether individual differences on two measures (i.e., presence, embodiment) were related to neurofeedback performance in either environment. We found that, while participants' performance on the BCI was similar between display conditions, the participants' reported levels of embodiment were significantly different. Specifically, participants experienced higher levels of embodiment in HMD-VR compared to a computer screen. We further found that reported levels of embodiment positively correlated with neurofeedback performance only in HMD-VR. Overall, these preliminary results suggest that embodiment may relate to better performance on EEG-based BCIs and that HMD-VR may increase embodiment compared to computer screens.

Design of TMS coils with reduced Lorentz forces: application to concurrent TMS-fMRI

OBJECTIVE

Interleaving TMS (transcranial magnetic stimulation) with fMRI (functional Magnetic Resonance Imaging) is a promising technique to study functional connectivity in the human brain, but its development is being restricted by technical limitations, such as that due to the interaction of the TMS current pulses with the magnetic fields of an MRI scanner. In this work, a TMS coil design method capable of controlling Lorentz forces experienced by the coil in the presence of static magnetic fields is presented.

APPROACH

The suggested approach is based on an existing inverse boundary element method (IBEM) for TMS coil design, in which new electromagnetic computational models of the Lorentz forces have been included to be controlled in the design process.

MAIN RESULTS

To demonstrate the validity of this technique, it has been used for the design and simulation of TMS coils wound on rectangular flat, spherical and hemispherical surfaces with improved mechanical stability. The obtained results confirm that TMS coils with reduced Lorentz forces inside the static main field of an MRI scanner can be produced, which is achieved to the detriment of other coil performance parameters.

SIGNIFICANCE

The proposed approach provides an efficient tool to design TMS stimulators of a wide range of coil geometries with improved mechanical stability, which can be extremely useful to overcome current limitations for interleaved TMS-fMRI.

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

Brain computer interface (BCI)-based training is promising for the treatment of stroke patients with upper limb (UL) paralysis. However, most stroke patients receive comprehensive treatment that not only includes BCI, but also routine training. The purpose of this study was to investigate the topological alterations in brain functional networks following comprehensive treatment, including BCI training, in the subacute stage of stroke. Twenty-five hospitalized subacute stroke patients with moderate to severe UL paralysis were assigned to one of two groups: 4-week comprehensive treatment, including routine and BCI training (BCI group, BG, n = 14) and 4-week routine training without BCI support (control group, CG, n = 11). Functional UL assessments were performed before and after training, including, Fugl-Meyer Assessment-UL (FMA-UL), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT). Neuroimaging assessment of functional connectivity (FC) in the BG was performed by resting state functional magnetic resonance imaging. After training, as compared with baseline, all clinical assessments (FMA-UL, ARAT, and WMFT) improved significantly (p < 0.05) in both groups. Meanwhile, better functional improvements were observed in FMA-UL (p < 0.05), ARAT (p < 0.05), and WMFT (p < 0.05) in the BG. Meanwhile, FC of the BG increased across the whole brain, including the temporal, parietal, and occipital lobes and subcortical regions. More importantly, increased inter-hemispheric FC between the somatosensory association cortex and putamen was strongly positively associated with UL motor function after training. Our findings demonstrate that comprehensive rehabilitation, including BCI training, can enhance UL motor function better than routine training for subacute stroke patients. The reorganization of brain functional networks topology in subacute stroke patients allows for increased coordination between the multi-sensory and motor-related cortex and the extrapyramidal system. Future long-term, longitudinal, controlled neuroimaging studies are needed to assess the effectiveness of BCI training as an approach to promote brain plasticity during the subacute stage of stroke.

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.

HS-CNN: a CNN with hybrid convolution scale for EEG motor imagery classification

OBJECTIVE

Electroencephalography (EEG) motor imagery classification has been widely used in healthcare applications such as mobile assistive robots and post-stroke rehabilitation. Recently, EEG motor imagery classification methods based on convolutional neural networks (CNNs) have been proposed and have achieved relatively high classification accuracy. However, these methods use single convolution scale in the CNN, while the best convolution scale differs from subject to subject. This limits the classification accuracy. Another issue is that the classification accuracy degrades when training data is limited.

APPROACH

To address these issues, we have proposed a hybrid-scale CNN architecture with a data augmentation method for EEG motor imagery classification.

MAIN RESULTS

Compared with several state-of-the-art methods, the proposed method achieves an average classification accuracy of 91.57% and 87.6% on two commonly used datasets, which outperforms several state-of-the-art EEG motor imagery classification methods.

SIGNIFICANCE

The proposed method effectively addresses the issues of existing CNN-based EEG motor imagery classification methods and improves the classification accuracy.

Repetitive Transcranial Magnetic Stimulation for the Treatment of Lower Limb Dysfunction in Patients Poststroke: A Systematic Review with Meta-Analysis

PURPOSE

To investigate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in recovery of lower limb dysfunction in patients poststroke.

PARTICIPANTS AND METHODS

Cochrane Central Register of Controlled Trials, Medline, ISI web of knowledge, EBSCO, Embase, Cumulative Index to Nursing and Allied Health Literature and Scopus.

RESULTS

Fifteen trials with 385 patients were included. Results showed that rTMS had a significant effect on balance (standard mean difference [SMD] = .38; 95% confidence interval [CI], .07: .69; I² = 51%) and mobility (SMD: -.67; 95% CI, -1.08: -.26; I² = 72%). However, rTMS had no significant immediate effects on the lower limb subscale of the Fugl-Meyer Assessment (FMA-L) (SMD = .01; 95% CI, -.29: .31; I² = 0%). Continued effects of rTMS was also found to be significant during the follow-up period (SMD = .46; 95% CI, .09: .84; I² = 14%).

CONCLUSION

rTMS was found to result in positive effects on mobility, balance and long-term prognosis of FMA-L. However data indicated that there is insufficient evidence for the effectiveness of rTMS in improving lower limb function.

Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients

In the last decade, technology-assisted stroke rehabilitation has been the focus of research. Electroencephalogram- (EEG-) based brain-computer interface (BCI) has a great potential for motor rehabilitation in stroke patients since the closed loop between motor intention and the actual movement established by BCI can stimulate the neural pathways of motor control. Due to the deficits in the brain, motor intention expression may shift to other brain regions during and even after neural reorganization. The objective of this paper was to study the event-related desynchronization (ERD) topography during motor attempt tasks of the paretic hand in stroke patients and compare the classification performance using different channel-selection strategies in EEG-based BCI. Fifteen stroke patients were recruited in this study. A cue-based experimental paradigm was applied in the experiment, in which each patient was required to open the palm of the paretic or the unaffected hand. EEG was recorded and analyzed to measure the motor intention and indicate the activated brain regions. Support vector machine (SVM) combined with common spatial pattern (CSP) algorithm was used to calculate the offline classification accuracy between the motor attempt of the paretic hand and the resting state applying different channel-selection strategies. Results showed individualized ERD topography during the motor attempt of the paretic hand due to the deficits caused by stroke. Statistical analysis showed a significant increase in the classification accuracy by analyzing the channels showing ERD than analyzing the channels from the contralateral sensorimotor cortex (SM1). The results indicated that for stroke patients whose affected motor cortex is extensively damaged, the compensated brain regions should be considered for implementing EEG-based BCI for motor rehabilitation as the closed loop between the altered activated brain regions and the paretic hand can be stimulated more accurately using the individualized channel-selection strategy.

Effects and safety of combined rTMS and action observation for recovery of function in the upper extremities in stroke patients: A randomized controlled trial

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) modulates cortical excitability and facilitates motor learning to improve motor recovery after stroke. Action observation (AO) therapy effectively facilitates physical training for motor memory formation.

OBJECTIVE

To compare the effectiveness of rTMS alone with that of combined rTMS and AO for the functional recovery of upper extremity function in subacute stroke patients and to verify the safety of the interventions.

METHODS

The present study was a prospective, randomized controlled trial involving subacute unilateral stroke patients. In total, 22 patients were randomly assigned to 2 groups: the trial group (rTMS with AO) and the control group (rTMS alone). Both groups received 1 Hz rTMS (intensity: 120% of resting motor threshold; rMT) over the contralesional primary motor cortex for 20 minutes on 10 consecutive days. Trial group received rTMS while watching a video of 5 different complex hand movements. The functional parameters were the Brunnstrom stage, Fugl-Meyer assessment (FMA) score of the upper extremity, Manual Function Test (MFT) score, and grip power. The following motor evoked potential (MEP) parameters were recorded from the abductor pollicis brevis muscle: rMT, latency, and amplitude. Both parameters were measured before and after the 2 week intervention.

RESULTS

After the 2 week trial, the total FMA and MFT scores were significantly improved in both groups, but the MFT subscores of hand motor function and grip power were significantly improved in the combination therapy group only. In contrast, the changes (Δ) of FMA, MFT, grip power test, and MEP outcomes were not significantly different between the 2 groups. No adverse events or complications were reported.

CONCLUSIONS

Distal upper extremity function, as measured by MFT and grip power, was improved after rTMS and AO in combination. The combination of rTMS with AO may be applied safely to improve upper extremity function after stroke.

Repetitive TMS does not improve cognition in patients with TBI: A randomized double-blind trial

OBJECTIVE

To determine whether high-frequency repetitive transcranial magnetic stimulation (rTMS) improves cognition in patients with severe traumatic brain injury.

METHODS

A single-center, randomized, double-blind, placebo-controlled study of rTMS was conducted in patients aged 18-60 years with chronic (>12 months postinjury) diffuse axonal injury (DAI). Patients were randomized to either a sham or real group in a 1:1 ratio. A 10-session rTMS protocol was used with 10-Hz stimulation over the left dorsolateral prefrontal cortex (DLPFC). Neuropsychological assessments were performed at 3 time points: at baseline, after the 10th rTMS session, and 90 days after intervention. The primary outcome was change in executive function evaluated using the Trail Making Test Part B.

RESULTS

Thirty patients with chronic DAI met the study criteria. Between-group comparisons of performance on TMT Part B at baseline and after the 10th rTMS session did not differ between groups (p = 0.680 and p = 0.341, respectively). No significant differences were observed on other neuropsychological tests. No differences in adverse events between treatment groups were observed.

CONCLUSIONS

Cognitive function in individuals with chronic DAI is not improved by high-frequency rTMS over the left DLPFC, though it appears safe and well-tolerated in this population.

CLINICALTRIALSGOV IDENTIFIER

NCT02167971.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that for individuals with chronic DAI, high-frequency rTMS over the left DLPFC does not significantly improve cognition.

Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms

EEG-based brain-computer interface (BCI) technology creates non-biological pathways for conveying a user's mental intent solely through noninvasively measured neural signals. While optimizing the performance of a single task has long been the focus of BCI research, in order to translate this technology into everyday life, realistic situations, in which multiple tasks are performed simultaneously, must be investigated. In this paper, we explore the concept of cognitive flexibility, or multitasking, within the BCI framework by utilizing a 2-D cursor control task, using sensorimotor rhythms (SMRs), and a four-target visual attention task, using steady-state visual evoked potentials (SSVEPs), both individually and simultaneously. We found no significant difference between the accuracy of the tasks when executing them alone (SMR-57.9% ± 15.4% and SSVEP-59.0% ± 14.2%) and simultaneously (SMR-54.9% ± 17.2% and SSVEP-57.5% ± 15.4%). These modest decreases in performance were supported by similar, non-significant changes in the electrophysiology of the SSVEP and SMR signals. In this sense, we report that multiple BCI tasks can be performed simultaneously without a significant deterioration in performance; this finding will help drive these systems toward realistic daily use in which a user's cognition will need to be involved in multiple tasks at once.

Exploring Training Effect in 42 Human Subjects Using a Non-invasive Sensorimotor Rhythm Based Online BCI

Electroencephalography based brain-computer interfaces (BCIs) show promise of providing an alternative communication channel between the brain and an external device. It is well acknowledged that BCI control is a skill and could be improved through practice and training. In this study, we explore the change of BCI behavioral performance as well as the electrophysiological properties across three training sessions in a pool of 42 human subjects. Our results show that the group average of BCI accuracy and the information transfer rate improved significantly in the third session compared to the first session; especially the significance reached in a smaller subset of a low BCI performance group (average accuracy <70%) as well. There was a significant difference of event-related desynchronization (ERD) lateralization for BCI control between the left- and right-hand imagination task in the last two sessions, but this significant difference was not revealed in the first training sessions. No significant change of R 2 value or event-related desynchronization and synchronization (ERD/ERS) for either channel C3 or channel C4, which were used for online control, was found across the training sessions. The change of ERD lateralization was also not significant across the training sessions. The present results indicate that BCI training could induce a change of behavioral performance and electrophysiological properties quickly, within just a few hours of training, distributed into three sessions. Multiple training sessions might especially be beneficial for the low BCI performers.

Effect of Combined Therapy of Robot and Low-Frequency Repetitive Transcranial Magnetic Stimulation on Hemispatial Neglect in Stroke Patients

Objective

To investigate the effect of upper limb rehabilitation combining robot with low-frequency repetitive transcranial magnetic stimulation (rTMS) on unilateral spatial neglect in stroke patients.

Methods

Patients who had hemispatial neglect after right hemisphere stroke were randomly divided into rTMS only group, robot only group, and combined group. All groups received conventional neglect therapy and additional treatment for each group. rTMS group received rTMS therapy. Robot group received robot therapy, while combined group received both therapies. The effect of therapy was assessed with Motor-Free Visual Perception Test-3 (MVPT-3), line bisection test, star cancellation test, Catherine Bergego Scale (CBS), Mini-Mental State Examination (MMSE), and the Korean version of Modified Barthel Index (K-MBI). These measurements were evaluated before and after treatment.

Results

For each group, 10 patients were recruited. There were no significant differences in baseline characteristics or initial values among the three groups. Two weeks after the therapy, all groups showed significant improvement in MVPT-3, line bisection test, star cancellation test, CBS, MMSE, and K-MBI. However, changes in measurements showed no significant differences among groups.

Conclusion

Treatment effect of the combined therapy of robotic therapy and low-frequency rTMS therapy for hemispatial neglect was not statistically different from that of each single treatment.

Results

of this study did not prove the superiority of any of the three treatments. Further study with large number of patients is needed to evaluate the superiority of these treatments.

Brain-machine interfaces for rehabilitation in stroke: A review

BACKGROUND

Motor paralysis after stroke has devastating consequences for the patients, families and caregivers. Although therapies have improved in the recent years, traditional rehabilitation still fails in patients with severe paralysis. Brain-machine interfaces (BMI) have emerged as a promising tool to guide motor rehabilitation interventions as they can be applied to patients with no residual movement.

OBJECTIVE

This paper reviews the efficiency of BMI technologies to facilitate neuroplasticity and motor recovery after stroke.

METHODS

We provide an overview of the existing rehabilitation therapies for stroke, the rationale behind the use of BMIs for motor rehabilitation, the current state of the art and the results achieved so far with BMI-based interventions, as well as the future perspectives of neural-machine interfaces.

RESULTS

Since the first pilot study by Buch and colleagues in 2008, several controlled clinical studies have been conducted, demonstrating the efficacy of BMIs to facilitate functional recovery in completely paralyzed stroke patients with noninvasive technologies such as the electroencephalogram (EEG).

CONCLUSIONS

Despite encouraging results, motor rehabilitation based on BMIs is still in a preliminary stage, and further improvements are required to boost its efficacy. Invasive and hybrid approaches are promising and might set the stage for the next generation of stroke rehabilitation therapies.