On the design of EEG-based movement decoders for completely paralyzed stroke patients

Background: Brain machine interface (BMI) technology has demonstrated its efficacy for rehabilitation of paralyzed chronic stroke patients. The critical component in BMI-training consists of the associative connection (contingency) between the intention and the feedback provided. However, the relationship between the BMI design and its performance in stroke patients is still an open question. Methods: In this study we compare different methodologies to design a BMI for rehabilitation and evaluate their effects on movement intention decoding performance. We analyze the data of 37 chronic stroke patients who underwent 4 weeks of BMI intervention with different types of association between their brain activity and the proprioceptive feedback. We simulate the pseudo-online performance that a BMI would have under different conditions, varying: (1) the cortical source of activity (i.e., ipsilesional, contralesional, bihemispheric), (2) the type of spatial filter applied, (3) the EEG frequency band, (4) the type of classifier; and also evaluated the use of residual EMG activity to decode the movement intentions. Results: We observed a significant influence of the different BMI designs on the obtained performances. Our results revealed that using bihemispheric beta activity with a common average reference and an adaptive support vector machine led to the best classification results. Furthermore, the decoding results based on brain activity were significantly higher than those based on muscle activity. Conclusions: This paper underscores the relevance of the different parameters used to decode movement, using EEG in severely paralyzed stroke patients. We demonstrated significant differences in performance for the different designs, which supports further research that should elucidate if those approaches leading to higher accuracies also induce higher motor recovery in paralyzed stroke patients.This study was funded by the Baden-Württemberg Stiftung (GRUENS ROB-1), the Deutsche Forschungsgemeinschaft (DFG, Koselleck and Grant SP 1533/2– 1), the Bundesministerium für Bildung und Forschung BMBF: MOTORBIC (FKZ 13GW0053) and AMORSA (FKZ 16SV7754), the fortüne-Program of the University of Tübingen (2422-0-1 and 2452-0-0) and the Basque Government Science Program (EXOTEK: KK 2016/00083)

Relation Between EEG Measures and Upper Limb Motor Recovery in Stroke Patients: A Scoping Review

Current clinical practice does not leverage electroencephalography (EEG) measurements in stroke patients, despite its potential to contribute to post-stroke recovery predictions. We review the literature on the effectiveness of various quantitative and qualitative EEG-based measures after stroke as a tool to predict upper limb motor outcome, in relation to stroke timeframe and applied experimental tasks. Moreover, we aim to provide guidance on the use of EEG in the assessment of upper limb motor recovery after stroke, suggesting a high potential for some metrics in the appropriate context. We identified relevant papers (N = 16) from databases ScienceDirect, Web of Science and MEDLINE, and assessed their methodological quality with the Joanna Briggs Institute (JBI) Critical Appraisal. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Framework. Identified works used EEG to identify properties including event-related activation, spectral power in physiologically relevant bands, symmetry in brain dynamics, functional connectivity, cortico-muscular coherence and rhythmic coordination. EEG was acquired in resting state or in relation to behavioural conditions. Motor outcome was mainly evaluated with the Upper Limb Fugl-Meyer Assessment. Despite great variability in the literature, data suggests that the most promising EEG quantifiers for predicting post-stroke motor outcome are event-related measures. Measures of spectral power in physiologically relevant bands and measures of brain symmetry also show promise. We suggest that EEG measures may improve our understanding of stroke brain dynamics during recovery, and contribute to establishing a functional prognosis and choosing the rehabilitation approach

Brain Activation During Passive and Volitional Pedaling After Stroke

Background: Prior work indicates that pedaling-related brain activation is lower in people with stroke than in controls. We asked whether this observation could be explained by between-group differences in volitional motor commands and pedaling performance. Methods: Individuals with and without stroke performed passive and volitional pedaling while brain activation was recorded with functional magnetic resonance imaging. The passive condition eliminated motor commands to pedal and minimized between-group differences in pedaling performance. Volume, intensity, and laterality of brain activation were compared across conditions and groups. Results: There were no significant effects of condition and no Group × Condition interactions for any measure of brain activation. Only 53% of subjects could minimize muscle activity for passive pedaling. Conclusions: Altered motor commands and pedaling performance are unlikely to account for reduced pedaling-related brain activation poststroke. Instead, this phenomenon may be due to functional or structural brain changes. Passive pedaling can be difficult to achieve and may require inhibition of excitatory descending drive

Ipsilesional Mu Rhythm Desynchronization and Changes in Motor Behavior Following Post Stroke BCI Intervention for Motor Rehabilitation

Loss of motor function is a common deficit following stroke insult and often manifests as persistent upper extremity (UE) disability which can affect a survivor’s ability to participate in activities of daily living. Recent research suggests the use of brain–computer interface (BCI) devices might improve UE function in stroke survivors at various times since stroke. This randomized crossover-controlled trial examines whether intervention with this BCI device design attenuates the effects of hemiparesis, encourages reorganization of motor related brain signals (EEG measured sensorimotor rhythm desynchronization), and improves movement, as measured by the Action Research Arm Test (ARAT). A sample of 21 stroke survivors, presenting with varied times since stroke and levels of UE impairment, received a maximum of 18–30 h of intervention with a novel electroencephalogram-based BCI-driven functional electrical stimulator (EEG-BCI-FES) device. Driven by spectral power recordings from contralateral EEG electrodes during cued attempted grasping of the hand, the user’s input to the EEG-BCI-FES device modulates horizontal movement of a virtual cursor and also facilitates concurrent stimulation of the impaired UE. Outcome measures of function and capacity were assessed at baseline, mid-therapy, and at completion of therapy while EEG was recorded only during intervention sessions. A significant increase in r-squared values [reflecting Mu rhythm (8–12 Hz) desynchronization as the result of attempted movements of the impaired hand] presented post-therapy compared to baseline. These findings suggest that intervention corresponds with greater desynchronization of Mu rhythm in the ipsilesional hemisphere during attempted movements of the impaired hand and this change is related to changes in behavior as a result of the intervention. BCI intervention may be an effective way of addressing the recovery of a stroke impaired UE and studying neuromechanical coupling with motor outputs.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT02098265

Neurophysiological Biomarkers of Motor Recovery in Severe Chronic Stroke

Schlaganfälle kommen jährlich millionenfach und weltweit vor. Die Patienten leiden fast immer unter verschiedensten Behinderungen, und mehr als die Hälfte entwickelt chronische Lähmungen. Für diese Gruppe der Patienten gibt es keine wirksame standardisierte Therapie. Die Vorgänge im Gehirn der Patienten, die ihre Bewegungsfähigkeit nach dem Schlaganfall wieder verbessern, versteht man auch nach Jahrzehnten der Forschung nur teilweise. Das Finden, Beobachten und Überwachen von neurophysiologischen Korrelaten des Erholungsvorgangs könnte helfen, die Gehirnaktivität vor und während einer solchen Behandlung besser zu verstehen. Durch die Entdeckung solcher “Biomarker” und davon abgeleiteter Vorhersagemodelle könnten neuartige Therapien entwickelt und gezieltere klinische Studien entworfen werden.\\ In dieser Dissertation werden mehrere Analysen von neurophysiologischen Daten der Gehirn- und Muskelaktivität von Gesunden und schwerst gelähmten chronischen Schlaganfallpatienten vorgestellt. Das Potential verschiedener Biomarker wird auf Basis dieser Daten bewertet. Zunächst wurde die Desynchronisierung des Sensorimotorischen Rhythmus’ untersucht. Die Gehirnaktivität von chronisch gelähmten Schlaganfallpatienten wurde während der Ausführung von Bewegungen des gelähmten Arms analysiert. Es ergab sich eine Korrelation zwischen der Erholung der Bewegungsfähigkeit und dem Verlauf der Desynchronisierung des Sensorimotorischen Rhythmus’ sowie dessen Lateralisation zwischen beiden Hemisphären. Die Position der Läsion scheint zudem einen Einfluss auf die Stärke der Desynchronisierung zu haben. Außerdem gab es beim Vergleich von Schlaganfallpatienten und Gesunden Unterschiede in der individuellen dominanten Frequenz des Rhythmus’. In einer weiteren Analyse wurde die Gehirnaktivität in niedrigen Frequenzen des Aktivitätsspektrums untersucht. Diese erhöhte sich bei den Patienten über der Läsion, was Ergebnisse früherer Arbeiten mit Tiermodellen und weniger stark gelähmten Schlaganfallpatienten bestätigt. Darüberhinaus wird eine Vorgehensweise für die Analyse von kohärenten Oszillationen im Gehirn während der Ausführung von Bewegungen vorgestellt. Erste Ergebnisse zeigen, dass sich die Verbindungen innerhalb der beschädigten Gehirnhälfte und zwischen den beiden Gehirnhälften mit der Therapie verstärken. Zuletzt wird ein Experiment vorgestellt, worin die möglichen Effekte der intensiven robotischen Therapie auf die Muskelaktivität der Patienten untersucht werden. Die Ergebnisse zeigten keinen ermüdenden Effekt des Trainings auf die Muskeln.\\ Im letzten Kapitel werden weiterführende Arbeiten für die Erweiterung von bereits existierenden Brain-Machine interface-Therapien vorgestellt. Ein virtuelles Exoskelett wurde zur Verbesserung des visuellen Feedbacks, das die Patienten während des Bewegungstraining mit dem Roboter erhalten, implementiert. Außerdem wurde hier ein umfassendes Training in eine “gamifizierte” Rehabilitationsumgebung integriert, um die Immersion und damit die Motivation der Patienten zu erhöhen.\\ Die hier vorgestellten Biomarker könnten als Bausteine für Modelle von Neurorehabilitation dienen und den Trainingsfortschritt der Patienten in solchen neuartigen Rehabilitationsumgebungen beobachtbar und visualisierbar machen. Die Übertragung der hier vorgestellten Forschungsergebnisse in neue oder verbesserte moderne Behandlungsmethoden könnten Millionen von Schlaganfallpatienten helfen, in Zukunft ihre Bewegungsfähigkeit wiederzuerlangen.The most common repercussion of stroke is disability, affecting millions of survivors globally each year. More than half of the victims develop chronic motor impairments. There is no efficient standardized therapy for this group. The processes in the brain of patients who recover their motor ability are poorly understood, even after decades of research. Finding, observing and tracking neurophysiological correlates of stroke and recovery could facilitate the interpretation of the brain activity before and during treatment. New therapies could be devised and studies designed, based on models and predicitions derived from these biomarkers. This thesis presents analyses of neurophysiological data of brain and muscles of healthy individuals and chronic stroke patients with severe motor impairments. Candidates for biomarkers are presented and their potential evaluated. First, desynchronization of the Sensorimotor Rhythm was considered. The brain activity of chronic stroke patients was analyzed during movement attempts of the paretic arm. There was a correlation between motor impairment and the evolution of desynchronization strength as well as the hemispheric laterality of the desynchronization. Moreover, the location of the lesion might have an effect on the strength of desynchronization. Furthermore, there was a significant difference of the peak center frequency of the rhythm compared between stroke patients and healthy individuals. Secondly, low-frequency activity of the brain during movement attempts of the stroke patients increased from before to after the intervention, confirming previous work in animal models and patients with less severe impairment. Thirdly, a methodology for the analysis of coherent brain oscillations during movement attempts is presented. First results show that connectivity within the hemisphere of the lesion as well as the communication between the hemispheres increased with the therapy. Finally, an experiment investigating potential effects of intensive robot-based interventions on muscle activity is presented. Results from four stroke patients did not indicate that the rehabilitation training induces muscular fatigue. The final chapter presents complementary work on enhancing existing Brain-Machine interface therapies. Sensory feedback to the patient is improved by way of displaying a virtual representation of an exoskeleton for training of movements of hand and arm. Furthermore, a rehabilitation training was embedded in a gamified environment for maximizing immersion and motivation of the patient. The biomarkers presented in these studies could serve as building blocks for modeling neurorehabilitation and to track and visualize recovery in such enriched training environments. The transition of this research to new or improved modern therapeutic approaches in clinical practice could serve millions of stroke victims

Individualisation of transcranial electric stimulation to improve motor function after stroke:Current challenges and future perspective

Transcranial electric stimulation (tES) is a non-invasive brain stimulation technique that could potentially improve motor rehabilitation after stroke. However, the effects of tES are in general stronger in healthy individuals compared to people with stroke. Interindividual variability in brain structure and function due to stroke potentially explain this difference in effects. This thesis describes the development of methods to facilitate the individualisation of tES in people with stroke and identifies objective neurophysiological correlates of motor learning that could potentially help to monitor the response to tES.In chapter 2, EEG correlates of explicit motor task learning were derived in healthy, young participants. Chapter 3 investigated the effects of 3 different tDCS configurations (sham, targeting contralateral M1 and targeting the full resting motor network) on corticospinal excitability. Both conventional and motor network tDCS did not increase corticospinal excitability relative to sham stimulation. Chapter 4 describes methods to create head models of people with stroke and assesses the effects of stroke lesions on the electric fields within stimulation targets. Chapter 5 describes a method to experimentally determine the electric conductivity of the stroke lesion. Finally, Chapter 6 analyses the electric fields generated by conventional tDCS in people with stroke and age-matched controls. It is shown that the one-size-fits-all approach results in more variable electric fields in people with stroke compared to controls. Optimisation of the electrode positions to maximise the electric field in stimulation targets increases the electric fields in people with stroke to the same level as found in healthy controls.This thesis shows anatomical and motor function variability exists between people with stroke due to differences in lesion characteristics. While there are several opportunities to individualise tES, more research is needed to investigate if this improves the effects of tES. As such, clinical implementation of tES seems unrealistic in the foreseeable future.<br/

Individualisation of transcranial electric stimulation to improve motor function after stroke:Current challenges and future perspective

Transcranial electric stimulation (tES) is a non-invasive brain stimulation technique that could potentially improve motor rehabilitation after stroke. However, the effects of tES are in general stronger in healthy individuals compared to people with stroke. Interindividual variability in brain structure and function due to stroke potentially explain this difference in effects. This thesis describes the development of methods to facilitate the individualisation of tES in people with stroke and identifies objective neurophysiological correlates of motor learning that could potentially help to monitor the response to tES.In chapter 2, EEG correlates of explicit motor task learning were derived in healthy, young participants. Chapter 3 investigated the effects of 3 different tDCS configurations (sham, targeting contralateral M1 and targeting the full resting motor network) on corticospinal excitability. Both conventional and motor network tDCS did not increase corticospinal excitability relative to sham stimulation. Chapter 4 describes methods to create head models of people with stroke and assesses the effects of stroke lesions on the electric fields within stimulation targets. Chapter 5 describes a method to experimentally determine the electric conductivity of the stroke lesion. Finally, Chapter 6 analyses the electric fields generated by conventional tDCS in people with stroke and age-matched controls. It is shown that the one-size-fits-all approach results in more variable electric fields in people with stroke compared to controls. Optimisation of the electrode positions to maximise the electric field in stimulation targets increases the electric fields in people with stroke to the same level as found in healthy controls.This thesis shows anatomical and motor function variability exists between people with stroke due to differences in lesion characteristics. While there are several opportunities to individualise tES, more research is needed to investigate if this improves the effects of tES. As such, clinical implementation of tES seems unrealistic in the foreseeable future.<br/

Enhancement of Robot-Assisted Rehabilitation Outcomes of Post-Stroke Patients Using Movement-Related Cortical Potential

Post-stroke rehabilitation is essential for stroke survivors to help them regain independence and to improve their quality of life. Among various rehabilitation strategies, robot-assisted rehabilitation is an efficient method that is utilized more and more in clinical practice for motor recovery of post-stroke patients. However, excessive assistance from robotic devices during rehabilitation sessions can make patients perform motor training passively with minimal outcome. Towards the development of an efficient rehabilitation strategy, it is necessary to ensure the active participation of subjects during training sessions. This thesis uses the Electroencephalography (EEG) signal to extract the Movement-Related Cortical Potential (MRCP) pattern to be used as an indicator of the active engagement of stroke patients during rehabilitation training sessions. The MRCP pattern is also utilized in designing an adaptive rehabilitation training strategy that maximizes patients’ engagement. This project focuses on the hand motor recovery of post-stroke patients using the AMADEO rehabilitation device (Tyromotion GmbH, Austria). AMADEO is specifically developed for patients with fingers and hand motor deficits. The variations in brain activity are analyzed by extracting the MRCP pattern from the acquired EEG data during training sessions. Whereas, physical improvement in hand motor abilities is determined by two methods. One is clinical tests namely Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) which include FMA-wrist, FMA-hand, MAS-hand movements, and MAS-advanced hand movements’ tests. The other method is the measurement of hand-kinematic parameters using the AMADEO assessment tool which contains hand strength measurements during flexion (force-flexion), and extension (force-extension), and Hand Range of Movement (HROM)

Top-down and bottom-up stimulation techniques combined with action observation treatment in stroke rehabilitation: a perspective

Stroke is a central nervous system disease that causes structural lesions and functional impairments of the brain, resulting in varying types, and degrees of dysfunction. The bimodal balance-recovery model (interhemispheric competition model and vicariation model) has been proposed as the mechanism of functional recovery after a stroke. We analyzed how combinations of motor observation treatment approaches, transcranial electrical (TES) or magnetic (TMS) stimulation and peripheral electrical (PES) or magnetic (PMS) stimulation techniques can be taken as accessorial physical therapy methods on symptom reduction of stroke patients. We suggest that top-down and bottom-up stimulation techniques combined with action observation treatment synergistically might develop into valuable physical therapy strategies in neurorehabilitation after stroke. We explored how TES or TMS intervention over the contralesional hemisphere or the lesioned hemisphere combined with PES or PMS of the paretic limbs during motor observation followed by action execution have super-additive effects to potentiate the effect of conventional treatment in stroke patients. The proposed paradigm could be an innovative and adjunctive approach to potentiate the effect of conventional rehabilitation treatment, especially for those patients with severe motor deficits

State-dependent modulation of cortico-spinal networks

Beta-band rhythm (13-30 Hz) is a dominant oscillatory activity in the sensorimotor system. Numerous studies reported on links between motor performance and the cortical and cortico-spinal beta rhythm. However, these studies report divergent beta-band frequencies and are, additionally, based on differently performed motor-tasks (e.g., motor imagination, muscle contraction, reach, grasp, and attention). This diversity blurs the role of beta in the sensorimotor system. It consequently challenges the development of beta-band activity-dependent stimulation protocols in the sensorimotor system. In this vein, we studied the functional role of beta-band cortico-cortical and cortico-spinal networks during a motor learning task. We studied how the contribution of cortical and spinal beta changes in the course of learning, and how this modulation is affected by afferent feedback to the sensorimotor system. We furthermore researched the relationship to motor performance. Consider that we made our study in the absence of any residual movement to allow our findings to be translated into rehabilitation programs for severely affected stroke patients. This thesis, at first, investigates evoked responses after transcranial magnetic stimulation (TMS). This revealed two different beta-band networks, i.e., in the low and high beta-band reflecting cortical and cortico-spinal activity. We, then, used a broader frequency range in the beta-band to trigger passive opening of the hand (peripheral feedback) or cortical stimulation (cortical feedback). While a unilateral hemispheric increase in cortico-spinal synchronization was observed in the group with peripheral feedback, a bilateral hemispheric increase in cortico-cortical and cortico-spinal synchronization was observed for the group with cortical feedback. An improvement in motor performance was found in the peripheral group only. Additionally, an enhancement in the directed cortico-spinal synchronization from cortex to periphery was observed for the peripheral group. Similar neurophysiological and behavioral changes were observed for stroke patients receiving peripheral feedback. The results 6 suggest two different mechanisms for beta-band activity-dependent protocols depending on the feedback modality. While the peripheral feedback appears to increase the synchronization among neural groups, cortical stimulation appears to recruit dormant neurons and to extend the involved motor network. These findings may provide insights regarding the mechanism behind novel activity-dependent protocols. It also highlights the importance of afferent feedback for motor restoration in beta-band activity-dependent rehabilitation programs