1,044 research outputs found
Technological advances in deep brain stimulation:Towards an adaptive therapy
Parkinson's disease (PD) is neurodegenerative movement disorder and a treatment method called deep brain stimulation (DBS) may considerably reduce the patient’s motor symptoms. The clinical procedure involves the implantation of a DBS lead, consisting of multiple electrode contacts, through which continuous high frequency (around 130 Hz) electric pulses are delivered in the brain. In this thesis, I presented the research which had the goal to improve current DBS technology, focusing on bringing the conventional DBS system a step closer to adaptive DBS, a personalized DBS therapy. The chapters in this thesis can be seen as individual building blocks for such an adaptive DBS system. After the general introduction, the first two chapters, two novel DBS lead designs are studied in a computational model. The model showed that both studied leads were able to exploit the novel distribution of the electrode contacts to shape and steer the stimulation field to activate more neurons in the chosen target compared to the conventional lead, and to counteract lead displacement. In the fourth chapter, an inverse current source density (CSD) method is applied on local field potentials (LFP) measured in a rat model. The pattern of CSD sources can act as a landmark within the STN to locate the potential stimulation target. The fifth and final chapter described the last building block of the DBS system. We introduced an inertial sensors and force sensor based measurement system, which can record hand kinematics and joint stiffness of PD patients. A system which can act as a feedback signal in an adaptive DBS system
Towards Individualized Transcranial Electric Stimulation Therapy through Computer Simulation
Transkranielle Elektrostimulation (tES) beschreibt eine Gruppe von Hirnstimulationstechniken, die einen schwachen elektrischen Strom über zwei nicht-invasiv am Kopf angebrachten Elektroden applizieren. Handelt es sich dabei um einen Gleichstrom, spricht man von transkranieller Gleichstromstimulation, auch tDCS abgekürzt. Die allgemeine Zielstellung aller Hirnstimulationstechniken ist Hirnfunktion durch ein Verstärken oder Dämpfen von Hirnaktivität zu beeinflussen. Unter den Stimulationstechniken wird die transkranielle Gleichstromstimulation als ein adjuvantes Werkzeug zur Unterstützung der mikroskopischen Reorganisation des Gehirnes in Folge von Lernprozessen und besonders der Rehabilitationstherapie nach einem Schlaganfall untersucht. Aktuelle Herausforderungen dieser Forschung sind eine hohe Variabilität im erreichten Stimulationseffekt zwischen den Probanden sowie ein unvollständiges Verständnis des Zusammenspiels der der Stimulation zugrundeliegenden Mechanismen. Als Schlüsselkomponente für das Verständnis der Stimulationsmechanismen wird das zwischen den Elektroden im Kopf des Probanden aufgebaute elektrische Feld erachtet. Einem grundlegenden Konzept folgend wird angenommen, dass Hirnareale, die einer größeren elektrischen Feldstärke ausgesetzt sind, ebenso einen höheren Stimulationseffekt erfahren. Damit kommt der Positionierung der Elektroden eine entscheidende Rolle für die Stimulation zu. Allerdings verteilt sich das elektrische Feld wegen des heterogenen elektrischen Leitfähigkeitsprofil des menschlichen Kopfes nicht uniform im Gehirn der Probanden. Außerdem ist das Verteilungsmuster auf Grund anatomischer Unterschiede zwischen den Probanden verschieden. Die triviale Abschätzung der Ausbreitung des elektrischen Feldes anhand der bloßen Position der Stimulationselektroden ist daher nicht ausreichend genau für eine zielgerichtete Stimulation.
Computerbasierte, biophysikalische Simulationen der transkraniellen Elektrostimulation ermöglichen die individuelle Approximation des Verteilungsmusters des elektrischen Feldes in Probanden basierend auf deren medizinischen Bildgebungsdaten. Sie werden daher zunehmend verwendet, um tDCS-Anwendungen zu planen und verifizieren, und stellen ein wesentliches Hilfswerkzeug auf dem Weg zu individualisierter Schlaganfall-Rehabilitationstherapie dar. Softwaresysteme, die den dahinterstehenden individualisierten Verarbeitungsprozess erleichtern und für ein breites Feld an Forschern zugänglich machen, wurden in den vergangenen Jahren für den Anwendungsfall in gesunden Erwachsenen entwickelt. Jedoch bleibt die Simulation von Patienten mit krankhaftem Hirngewebe und strukturzerstörenden Läsionen eine nicht-triviale Aufgabe.
Daher befasst sich das hier vorgestellte Projekt mit dem Aufbau und der praktischen Anwendung eines Arbeitsablaufes zur Simulation transkranieller Elektrostimulation. Dabei stand die Anforderung im Vordergrund medizinische Bildgebungsdaten insbesondere neurologischer Patienten mit krankhaft verändertem Hirngewebe verarbeiten zu können. Der grundlegende Arbeitsablauf zur Simulation wurde zunächst für gesunde Erwachsene entworfen und validiert. Dies umfasste die Zusammenstellung medizinischer Bildverarbeitungsalgorithmen zu einer umfangreichen Verarbeitungskette, um elektrisch relevante Strukturen in den Magnetresonanztomographiebildern des Kopfes und des Oberkörpers der Probanden zu identifizieren und zu extrahieren. Die identifizierten Strukturen mussten in Computermodelle überführt werden und das zugrundeliegende, physikalische Problem der elektrischen Volumenleitung in biologischen Geweben mit Hilfe numerischer Simulation gelöst werden.
Im Verlauf des normalen Alterns ist das Gehirn strukturellen Veränderungen unterworfen, unter denen ein Verlust des Hirnvolumens sowie die Ausbildung mikroskopischer Veränderungen seiner Nervenfaserstruktur die Bedeutendsten sind. In einem zweiten Schritt wurde der Arbeitsablauf daher erweitert, um diese Phänomene des normalen Alterns zu berücksichtigen. Die vordergründige Herausforderung in diesem Teilprojekt war die biophysikalische Modellierung der veränderten Hirnmikrostruktur, da die resultierenden Veränderungen im Leitfähigkeitsprofil des Gehirns bisher noch nicht in der Literatur quantifiziert wurden. Die Erweiterung des Simulationsablauf zeichnete sich vorrangig dadurch aus, dass mit unsicheren elektrischen Leitfähigkeitswerten gearbeitet werden konnte. Damit war es möglich den Einfluss der ungenau bestimmbaren elektrischen Leitfähigkeit der verschiedenen biologischen Strukturen des menschlichen Kopfes auf das elektrische Feld zu ermitteln. In einer Simulationsstudie, in der Bilddaten von 88 Probanden einflossen, wurde die Auswirkung der veränderten Hirnfaserstruktur auf das elektrische Feld dann systematisch untersucht. Es wurde festgestellt, dass sich diese Gewebsveränderungen hochgradig lokal und im Allgemeinen gering auswirken.
Schließlich wurden in einem dritten Schritt Simulationen für Schlaganfallpatienten durchgeführt. Ihre großen, strukturzerstörenden Läsionen wurden dabei mit einem höheren Detailgrad als in bisherigen Arbeiten modelliert und physikalisch abermals mit unsicheren Leitfähigkeiten gearbeitet, was zu unsicheren elektrischen Feldabschätzungen führte. Es wurden individuell berechnete elektrische Felddaten mit der Hirnaktivierung von 18 Patienten in Verbindung gesetzt, unter Berücksichtigung der inhärenten Unsicherheit in der Bestimmung der elektrischen Felder. Das Ziel war zu ergründen, ob die Hirnstimulation einen positiven Einfluss auf die Hirnaktivität der Patienten im Kontext von Rehabilitationstherapie ausüben und so die Neuorganisierung des Gehirns nach einem Schlaganfall unterstützen kann. Während ein schwacher Zusammenhang hergestellt werden konnte, sind weitere Untersuchungen nötig, um diese Frage abschließend zu klären.:Kurzfassung
Abstract
Contents
1 Overview
2 Anatomical structures in magnetic resonance images
2 Anatomical structures in magnetic resonance images
2.1 Neuroanatomy
2.2 Magnetic resonance imaging
2.3 Segmentation of MR images
2.4 Image morphology
2.5 Summary
3 Magnetic resonance image processing pipeline
3.1 Introduction to human body modeling
3.2 Description of the processing pipeline
3.3 Intermediate and final outcomes in two subjects
3.4 Discussion, limitations & future work
3.5 Conclusion
4 Numerical simulation of transcranial electric
stimulation
4.1 Electrostatic foundations
4.2 Discretization of electrostatic quantities
4.3 The numeric solution process
4.4 Spatial discretization by volume meshing
4.5 Summary
5 Simulation workflow
5.1 Overview of tES simulation pipelines
5.2 My implementation of a tES simulation workflow
5.3 Verification & application examples
5.4 Discussion & Conclusion
6 Transcranial direct current stimulation in the aging brain
6.1 Handling age-related brain changes in tES simulations
6.2 Procedure of the simulation study
6.3 Results of the uncertainty analysis
6.4 Findings, limitations and discussion
7 Transcranial direct current stimulation in stroke patients
7.1 Bridging the gap between simulated electric fields and brain activation in
stroke patients
7.2 Methodology for relating simulated electric fields to functional MRI data
7.3 Evaluation of the simulation study and correlation analysis
7.4 Discussion & Conclusion
8 Outlooks for simulations of transcranial electric stimulation
List of Figures
List of Tables
Glossary of Neuroscience Terms
Glossary of Technical Terms
BibliographyTranscranial electric current stimulation (tES) denotes a group of brain stimulation techniques that apply a weak electric current over two or more non-invasively, head-mounted electrodes. When employing a direct-current, this method is denoted transcranial direct current stimulation (tDCS). The general aim of all tES techniques is the modulation of brain function by an up- or downregulation of brain activity. Among these, transcranial direct current stimulation is investigated as an adjuvant tool to promote processes of the microscopic reorganization of the brain as a consequence of learning and, more specifically, rehabilitation therapy after a stroke. Current challenges of this research are a high variability in the achieved stimulation effects across subjects and an incomplete understanding of the interplay between its underlying mechanisms. A key component to understanding the stimulation mechanism is considered the electric field, which is exerted by the electrodes and distributes in the subjects' heads. A principle concept assumes that brain areas exposed to a higher electric field strength likewise experience a higher stimulation. This attributes the positioning of the electrodes a decisive role for the stimulation. However, the electric field distributes non-uniformly across subjects' brains due to the heterogeneous electrical conductivity profile of the human head. Moreover, the distribution pattern is variable between subjects due to their individual anatomy. A trivial estimation of the distribution of the electric field solely based on the position of the stimulating electrodes is, therefore, not precise enough for a well-targeted stimulation.
Computer-based biophysical simulations of transcranial electric stimulation enable the individual approximation of the distribution pattern of the electric field in subjects based on their medical imaging data. They are, thus, increasingly employed for the planning and verification of tDCS applications and constitute an essential tool on the way to individualized stroke rehabilitation therapy. Software pipelines facilitating the underlying individualized processing for a wide range of researchers have been developed for use in healthy adults over the past years, but, to date, the simulation of patients with abnormal brain tissue and structure disrupting lesions remains a non-trivial task.
Therefore, the presented project was dedicated to establishing and practically applying a tES simulation workflow. The processing of medical imaging data of neurological patients with abnormal brain tissue was a central requirement in this process. The basic simulation workflow was first designed and validated for the simulation of healthy adults. This comprised compiling medical image processing algorithms into a comprehensive workflow to identify and extract electrically relevant physiological structures of the human head and upper torso from magnetic resonance images. The identified structures had to be converted to computational models. The underlying physical problem of electric volume conduction in biological tissue was solved by means of numeric simulation.
Over the course of normal aging, the brain is subjected to structural alterations, among which a loss of brain volume and the development of microscopic alterations of its fiber structure are the most relevant. In a second step, the workflow was, thus, extended to incorporate these phenomena of normal aging. The main challenge in this subproject was the biophysical modeling of the altered brain microstructure as the resulting alterations to the conductivity profile of the brain were so far not quantified in the literature. Therefore, the augmentation of the workflow most notably included the modeling of uncertain electrical properties. With this, the influence of the uncertain electrical conductivity of the biological structures of the human head on the electric field could be assessed. In a simulation study, including imaging data of 88 subjects, the influence of the altered brain fiber structure on the electric field was then systematically investigated. These tissue alterations were found to exhibit a highly localized and generally low impact.
Finally, in a third step, tDCS simulations of stroke patients were conducted. Their large, structure-disrupting lesions were modeled in a more detailed manner than in previous stroke simulation studies, and they were physically, again, modeled by uncertain electrical conductivity resulting in uncertain electric field estimates. Individually simulated electric fields were related to the brain activation of 18 patients, considering the inherently uncertain electric field estimations. The goal was to clarify whether the stimulation exerts a positive influence on brain function in the context of rehabilitation therapy supporting brain reorganization following a stroke. While a weak correlation could be established, further investigation will be necessary to answer that research question.:Kurzfassung
Abstract
Contents
1 Overview
2 Anatomical structures in magnetic resonance images
2 Anatomical structures in magnetic resonance images
2.1 Neuroanatomy
2.2 Magnetic resonance imaging
2.3 Segmentation of MR images
2.4 Image morphology
2.5 Summary
3 Magnetic resonance image processing pipeline
3.1 Introduction to human body modeling
3.2 Description of the processing pipeline
3.3 Intermediate and final outcomes in two subjects
3.4 Discussion, limitations & future work
3.5 Conclusion
4 Numerical simulation of transcranial electric
stimulation
4.1 Electrostatic foundations
4.2 Discretization of electrostatic quantities
4.3 The numeric solution process
4.4 Spatial discretization by volume meshing
4.5 Summary
5 Simulation workflow
5.1 Overview of tES simulation pipelines
5.2 My implementation of a tES simulation workflow
5.3 Verification & application examples
5.4 Discussion & Conclusion
6 Transcranial direct current stimulation in the aging brain
6.1 Handling age-related brain changes in tES simulations
6.2 Procedure of the simulation study
6.3 Results of the uncertainty analysis
6.4 Findings, limitations and discussion
7 Transcranial direct current stimulation in stroke patients
7.1 Bridging the gap between simulated electric fields and brain activation in
stroke patients
7.2 Methodology for relating simulated electric fields to functional MRI data
7.3 Evaluation of the simulation study and correlation analysis
7.4 Discussion & Conclusion
8 Outlooks for simulations of transcranial electric stimulation
List of Figures
List of Tables
Glossary of Neuroscience Terms
Glossary of Technical Terms
Bibliograph
Design of a wearable device for conditional neuromodulation of the pudendal nerve
After spinal cord injury, the normal functions of the lower urinary tract may be disrupted. Namely, incontinence and concurrent voiding problems may ensue. The troublesome side effects of the drugs, infection due to catheterisation, and the costs and risks associated with more invasive treatments indicate the need for alternative forms of treatment. The pudendal nerve neuromodulation may provide such an alternative. The unique aspect of this technique is that depending on the stimulus frequency it may result in micturition-like or continence-like reflexes. Also, the stimulus current can be applied trans-rectally, meaning that a minimally-invasive wearable solution may be developed. The major limitation of such a solution is the high level of the required stimulus current to activate the nerve trans-rectally. The efficacy of the trans-rectal neuromodulation of the pudendal may be increased by only applying the stimulus when needed, when employed to tackle incontinence. The electromyogram signal from the external anal sphincter may be used to detect the onset of hyper-reflexive contractions of the bladder. The ability of recording this signal can be readily incorporated in the neuromodulation device due to the proximity of the structures. However, the recording electrodes should be designed for an efficacious and chronic recording. Thus, the main objective of this thesis was to design and optimise the neuromodulation and recording electrodes on the said device. A volume conductor model of such a device in situ was developed and used in tandem with a double layer cable model of nerve fibres to minimise the stimulus current. It was demonstrated that a considerable reduction in the stimulus current may be achieved even when the variations of the nerve trajectory in different individuals are considered. Using computational models and experimental measurements, a recording assembly was identified for an efficacious recording of the electromyogram from the external anal sphincter
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Noninvasive Neuromodulation: Modeling and Analysis of Transcranial Brain Stimulation with Applications to Electric and Magnetic Seizure Therapy
Bridging the fields of engineering and psychiatry, this dissertation proposes a novel framework for the rational dosing of electric and magnetic seizure therapy, including electroconvulsive therapy (ECT) and magnetic seizure therapy (MST), for the treatment of psychiatric disorders such as medication resistant major depression and schizophrenia. The objective of this dissertation is to develop computational modeling tools that allow ECT and MST stimulation paradigms to be biophysically optimized ex vivo, prior to testing safety and efficacy in preclinical and clinical trials. Despite therapeutic advances, treatment resistant depression (TRD) remains a largely unmet clinical need. ECT is highly effective for TRD, but its side effects limit its real-world clinical utility. Modifications of treatment technique (e.g., electrode placement, stimulus parameters, novel paradigms such as MST) significantly improve the tolerability of convulsive therapy. However, we know relatively little about the distribution of the electric field (E-field) induced in the brain to inform spatial targeting of ECT and MST. Lacking an understanding of biophysical and physiological mechanisms, refinements in ECT/MST technique rely exclusively on time-consuming and costly clinical trials. Consequently, key questions remain unanswered about how to position the ECT electrodes or MST coil for targeted brain stimulation. Addressing this knowledge gap, this dissertation proposes a new platform that will inform an improved spatial targeting of ECT and MST through state-of-the-art computer simulations of the E-field distribution in human and nonhuman primate (NHP) brain.
Part I of this dissertation aims to develop anatomically realistic finite element models of transcranial electric and magnetic stimulation in human and NHPs incorporating tissue heterogeneity and anisotropy derived from structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. The NHP models of ECT and MST are created alongside the human model since NHPs are used in preclinical studies on the mechanisms of seizure therapy.
Part II of this dissertation aims to apply the model developed in Part I to electric and magnetic seizure therapy. We compute the strength and spatial distributions of the E-field induced in the brain by various ECT and MST paradigms. The relative E-field strength among various regions of interest (ROIs) is examined to select electrode/coil configurations that produce most focal stimulation of target ROIs that are considered to mediate the therapeutic action of ECT and MST. Since E-field alone is insufficient to account for individual differences in neurophysiological response, we calibrate the E-field maps relative to the neural activation threshold via in vivo measurements of the corticospinal tract response to single pulses (motor threshold, MT). We derive an empirical estimate of the neural activation threshold by coupling simulated E-field strength with individually measured MT. The E-field strength relative to an empirical neural activation threshold and corresponding volume of suprathreshold stimulation (focality) is examined to inform the selection of ECT and MST stimulus pulse amplitude that will result in focal ROI stimulation. We contrast the ECT/MST stimulation strength and focality with conventional fixed and individually titrated pulse amplitude necessary to induce a seizure (seizure threshold, ST) to study pulse amplitude adjustment as a novel means of controlling stimulation strength and focality. This work provides a basis for rational dosing of seizure therapies that could help improve their risk/benefit ratio and guide the development of safer alternatives for patients with severe psychiatric disorders
Simulating and optimizing electrical current flow and neuronal activation in retinal implants
© 2018 Dr Timothy Bede Esler[Abstract Withheld
Proceedings of the Conference on Progress in Electrically Active Implants - Tissue and Functional Regeneration (ELAINE 2020)
The conference on Progress in Electrically Active Implants - Tissue and Functional Regeneration (ELAINE 2020) focused on novel methods in the electric stimulation of bio-material compounds of living cells and implantable electric stimulation devices. ELAINE 2020 provided international scientists a virtual platform to discuss the latest achievements in the form of invited presentations, selected talks from abstract submissions, and virtual poster sessions. In addition, we particularly invited critical reviews and contributions with negative results or unsuccessful replications to foster the scientific discussion and explicitly encourage young scientists to contribute and submit their work
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