Brain oscillatory activity as a biomarker of motor recovery in chronic stroke

In the present work, we investigated the relationship of oscillatory sensorimotor brain activity to motor recovery. The neurophysiological data of 30 chronic stroke patients with severe upper‐limb paralysis are the basis of the observational study presented here. These patients underwent an intervention including movement training based on combined brain–machine interfaces and physiotherapy of several weeks recorded in a double‐blinded randomized clinical trial. We analyzed the alpha oscillations over the motor cortex of 22 of these patients employing multilevel linear predictive modeling. We identified a significant correlation between the evolution of the alpha desynchronization during rehabilitative intervention and clinical improvement. Moreover, we observed that the initial alpha desynchronization conditions its modulation during intervention: Patients showing a strong alpha desynchronization at the beginning of the training improved if they increased their alpha desynchronization. Patients showing a small alpha desynchronization at initial training stages improved if they decreased it further on both hemispheres. In all patients, a progressive shift of desynchronization toward the ipsilesional hemisphere correlates significantly with clinical improvement regardless of lesion location. The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.Bundesministerium für Bildung und Forschung, Grant/Award Numbers: 13GW0053, 16SV7754; Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst, Grant/Award Number: 9156335

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

Event-related desynchronization during movement attempt and execution in severely paralyzed stroke patients: An artifact removal relevance analysis

The electroencephalogram (EEG) constitutes a relevant tool to study neural dynamics and to develop brain-machine interfaces (BMI) for rehabilitation of patients with paralysis due to stroke. However, the EEG is easily contaminated by artifacts of physiological origin, which can pollute the measured cortical activity and bias the interpretations of such data. This is especially relevant when recording EEG of stroke patients while they try to move their paretic limbs, since they generate more artifacts due to compensatory activity. In this paper, we study how physiological artifacts (i.e., eye movements, motion artifacts, muscle artifacts and compensatory movements with the other limb) can affect EEG activity of stroke patients. Data from 31 severely paralyzed stroke patients performing/attempting grasping movements with their healthy/paralyzed hand were analyzed offline. We estimated the cortical activation as the event-related desynchronization (ERD) of sensorimotor rhythms and used it to detect the movements with a pseudo-online simulated BMI. Automated state-of-the-art methods (linear regression to remove ocular contaminations and statistical thresholding to reject the other types of artifacts) were used to minimize the influence of artifacts. The effect of artifact reduction was quantified in terms of ERD and BMI performance. The results reveal a significant contamination affecting the EEG, being involuntary muscle activity the main source of artifacts. Artifact reduction helped extracting the oscillatory signatures of motor tasks, isolating relevant information from noise and revealing a more prominent ERD activity. Lower BMI performances were obtained when artifacts were eliminated from the training datasets. This suggests that artifacts produce an optimistic bias that improves theoretical accuracy but may result in a poor link between task-related oscillatory activity and BMI peripheral feedback. With a clinically relevant dataset of stroke patients, we evidence the need of appropriate methodologies to remove artifacts from EEG datasets to obtain accurate estimations of the motor brain activity.This study was funded by the fortüne-Program of the University of Tübingen (2422-0-1 and 2452-0-0), the Bundesministerium für Bildung und Forschung BMBF MOTORBIC (FKZ 13GW0053) and AMORSA (FKZ 16SV7754), the Deutsche Forschungsgemeinschaft (DFG), the Basque Government Science Program (EXOTEK: KK 2016/00083). The work of A. Insausti-Delgado was supported by the Basque Government's scholarship for predoctoral students

Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients

Objective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing. Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores. Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement. Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.This study was funded by the Fortüne-Program of the University of Tübingen (2452-0-0/2), the Bundesministerium für Bildung und Forschung (AMORSA (FKZ-16SV7754), REHOME (V5GR2001M1007-01)), EUROSTARS (SubliminalHomeRehab (FKZ: 01QE2023C E! 113928)) and the Basque Government Science Program (SINICTUS (2018222036), MODULA (KK-2019/00018), Elkartek-EXOTEK (KK-2016/00083)). N Irastorza-Landa's work was funded by the Basque Government's scholarship for predoctoral students

Unimanual versus bimanual motor imagery classifiers for assistive and rehabilitative brain computer interfaces

Bimanual movements are an integral part of everyday activities and are often included in rehabilitation therapies. Yet electroencephalography (EEG) based assistive and rehabilitative brain computer interface (BCI) systems typically rely on motor imagination (MI) of one limb at the time. In this study we present a classifier which discriminates between uni-and bimanual MI. Ten able bodied participants took part in cue based motor execution (ME) and MI tasks of the left (L), right (R) and both (B) hands. A 32 channel EEG was recorded. Three linear discriminant analysis classifiers, based on MI of L-B, B-R and B--L hands were created, with features based on wide band Common Spatial Patterns (CSP) 8-30 Hz, and band specifics Common Spatial Patterns (CSPb). Event related desynchronization (ERD) was significantly stronger during bimanual compared to unimanual ME on both hemispheres. Bimanual MI resulted in bilateral parietally shifted ERD of similar intensity to unimanual MI. The average classification accuracy for CSP and CSPb was comparable for L-R task (73±9% and 75±10% respectively) and for L-B task (73±11% and 70±9% respectively). However, for R-B task (67±3% and 72±6% respectively) it was significantly higher for CSPb (p=0.0351). Six participants whose L-R classification accuracy exceeded 70% were included in an on-line task a week later, using the unmodified offline CSPb classifier, achieving 69±3% and 66±3% accuracy for the L-R and R-B tasks respectively. Combined uni and bimanual BCI could be used for restoration of motor function of highly disabled patents and for motor rehabilitation of patients with motor deficits

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)

Medico-Legal Aspects of the Nervous System as a Functioning Unit of the Body

We have had the pleasure of working together in recent years on Law-Science problems. During that time we have become increasingly convinced that it is necessary for trial lawyer and scientist alike to think of the human being in terms of the nine main organ systems,\u27reserving a tenth category for the field of personality as the latter represents a synthesis of component structures and functions into variable reaction and behavior patterns. An injury or disability may involve impairment or destruction of an an atomic member or of physiological function; it may involve effects on personality, or psychic values, alone, without discoverable organic lesion, or it may cause disocations both in organ systems and in over-all personality. To achieve a scientific approach to medico-legal problems one must undertake focal analysis in the discovery, or exploratory phases, and synthesis in the phases of evaluation and prognosis

Evaluating the impact of intracortical microstimulation on distant cortical brain regions for neuroprosthetic applications

Enhancing functional motor recovery after localized brain injury is a widely recognized priority in healthcare as disorders of the nervous system that cause motor impairment, such as stroke, are among the most common causes of adult-onset disability. Restoring physiological function in a dysfunctional brain to improve quality of life is a primary challenge in scientific and clinical research and could be driven by innovative therapeutic approaches. Recently, techniques using brain stimulation methodologies have been employed to promote post-injury neuroplasticity for the restitution of motor function. One type of closed-loop stimulation, i.e., activity-dependent stimulation (ADS), has been shown to modify existing functional connectivity within either healthy or injured cerebral cortices and used to increase behavioral recovery following cortical injury. The aim of this PhD thesis is to characterize the electrophysiological correlates of such behavioral recovery in both healthy and injured cortical networks using in vivo animal models. We tested the ability of two different intracortical micro-stimulation protocols, i.e., ADS and its randomized open-loop version (RS), to potentiate cortico-cortical connections between two distant cortical locations in both anaesthetized and awake behaving rats. Thus, this dissertation has the following three main goals: 1) to investigate the ability of ADS to induce changes in intra-cortical activity in healthy anesthetized rats, 2) to characterize the electrophysiological signs of brain injury and evaluate the capability of ADS to promote electrophysiological changes in the damaged network, and 3) to investigate the long-term effects of stimulation by repeating the treatment for 21 consecutive days in healthy awake behaving animals. The results of this study indicate that closed-loop activity-dependent stimulation induced greater changes than open-loop random stimulation, further strengthening the idea that Hebbian-inspired protocols might potentiate cortico-cortical connections between distant brain areas. The implications of these results have the potential to lead to novel treatments for various neurological diseases and disorders and inspire new neurorehabilitation therapies