Validating age-related functional imaging changes in verbal working memory with acute stroke

Abstract. Functional imaging studies consistently find that older adults recruit bilateral brain regions in cognitive tasks that are strongly lateralized in younger adults, a characterization known as the Hemispheric Asymmetry Reduction in Older Adults model. While functional imaging displays what brain areas are active during tasks, it cannot demonstrate what brain regions are necessary for task performance. We used behavioral data from acute stroke patients to test the hypothesis that older adults need both hemispheres for a verbal working memory task that is predominantly left-lateralized in younger adults. Right-handed younger (age 50, n = 7) and older adults (age > 50, n = 21) with acute unilateral stroke, as well as younger (n = 6) and older (n = 13) transient ischemic attack (TIA) patients, performed a self-paced verbal item-recognition task. Older patients with stroke to either hemisphere had a higher frequency of deficits in the verbal working memory task compared to older TIA patients. Additionally, the deficits in older stroke patients were mainly in retrieval time while the deficits in younger stroke patients were mainly in accuracy. These data suggest that bihemispheric activity is necessary for older adults to successfully perform a verbal working memory task

Spatio-temporal evolution of interictal epileptic activity : a study with unaveraged multichannel MEG data in association with MRIs.

This thesis addresses issues relating to MEG modelling, analysis and interpretation of results. A source model employing current density distributions, namely Magnetic Field Tomography (MET), is used to obtain the MEG results. The first issue of concern refers to the registration of MEG data with structural MR images in an attempt to improve the localisation capability of MEG/MET. Simulations testing some spatial and tem poral aspects of the reconstruction capability of MET are also provided. A novel way of conducting MET studies in depth is suggested and implemented: the iterative use of a source space designed to cover deep situated structures on either side of the brain. The main bulk of this thesis is concerned with research into interictal epileptic activity as recorded by means of multichannel MEG system s and analysed using MET. The major aim is to investigate whether or not MET analysis of unaveraged MEG data (single epochs) is feasible in cases of pathophysiological signals and more specifically interictal signals from patients with epilepsy of a complex partial type. The investigation is undertaken against the "traditional" view of the impropriety and absurdity of using single epoch records in the MEG analysis due to noise dominance; we provide evidence that analysis of single, unaveraged epileptic spikes is actually feasible: we demonstrate spatio-temporal coherence in the MET results of the various single interictal events and show that activity extracted from the "averaged event" is made up of activity contributions which occur intermittently and at variable latencies. Our statements are drawn from the study of both superficial and deep activity

How does iReadMore therapy change the reading network of patients with central alexia?

Central alexia (CA) is an acquired reading disorder co-occurring with a generalised language deficit (aphasia). The roles of perilesional and ipsilesional tissue in recovery from post-stroke aphasia are unclear. We investigated the impact of reading training (using iReadMore, a therapy app) on the connections within and between the right and left hemisphere of the reading network of patients with CA. In patients with pure alexia, iReadMore increased feedback from left inferior frontal region (IFG) to the left occipital (OCC) region. We aimed to identify if iReadMore therapy was effective through a similar mechanism in CA patients.Participants with chronic post-stroke CA (n=23) completed 35 hours of iReadMore training over four weeks. Reading accuracy for trained and untrained words was assessed before and after therapy. The neural response to reading trained and untrained words in the left and right OCC, ventral occipitotemporal (vOT) and IFG was examined using event-related magnetoencephalography.The training-related modulation in effective connectivity between regions was modelled at the group level with Dynamic Causal Modelling.iReadMore training improved participants' reading accuracy by an average of 8.4% (range: -2.77 to 31.66) while accuracy for untrained words was stable. Training increased regional sensitivity in bilateral frontal and occipital regions, and strengthened feedforward connections within the left hemisphere. Our data suggests that iReadMore training in these patients modulates lower-order visual representations, as opposed to higher-order, more abstract ones, in order to improve word reading accuracy.SIGNIFICANCE STATEMENTThis is the first study to conduct a network-level analyses of therapy effects in participants with post-stroke central alexia. When patients trained with iReadMore (a multimodal, behavioural, mass practice, computer-based therapy), reading accuracy improved by an average 8.4% on trained items. A network analysis of the magnetoencephalography data associated with this improvement revealed an increase in regional sensitivity in bilateral frontal and occipital regions and strengthening of feedforward connections within the left hemisphere. This indicates that in CA patients iReadMore engages lower-order, intact resources within the left hemisphere (posterior to their lesion locations) to improve word reading. This provides a foundation for future research to investigate reading network modulation in different CA subtypes, or for sentence level therapy

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/

Hemispheric asymmetry in the efficiency of attentional networks

Advantage in conflict resolution was observed, which may indicate hemispheric asymmetry of the executive network. No VF effect for alerting was found. The results, consistent with the common notion of general right hemisphere dominance for attention, provide a more detailed account of hemispheric asymmetries of the attentional networks than previous studies using the LANT task

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

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/

Real-time functional architecture of visual word recognition.

Despite a century of research into visual word recognition, basic questions remain unresolved about the functional architecture of the process that maps visual inputs from orthographic analysis onto lexical form and meaning and about the units of analysis in terms of which these processes are conducted. Here we use magnetoencephalography, supported by a masked priming behavioral study, to address these questions using contrasting sets of simple (walk), complex (swimmer), and pseudo-complex (corner) forms. Early analyses of orthographic structure, detectable in bilateral posterior temporal regions within a 150-230 msec time frame, are shown to segment the visual input into linguistic substrings (words and morphemes) that trigger lexical access in left middle temporal locations from 300 msec. These are primarily feedforward processes and are not initially constrained by lexical-level variables. Lexical constraints become significant from 390 msec, in both simple and complex words, with increased processing of pseudowords and pseudo-complex forms. These results, consistent with morpho-orthographic models based on masked priming data, map out the real-time functional architecture of visual word recognition, establishing basic feedforward processing relationships between orthographic form, morphological structure, and lexical meaning.This is the final version of the article. It first appeared from MIT Press via http://dx.doi.org/10.1162/jocn_a_0069