464 research outputs found

    Depth-dependent intracortical myelin organization in the living human brain determined by in vivo ultra-high field magnetic resonance imaging

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    Background: Intracortical myelin is a key determinant of neuronal synchrony and plasticity that underpin optimal brain function. Magnetic resonance imaging (MRI) facilitates the examination of intracortical myelin but presents with methodological challenges. Here we describe a whole-brain approach for the in vivo investigation of intracortical myelin in the human brain using ultra-high field MRI. Methods: Twenty-five healthy adults were imaged in a 7 Tesla MRI scanner using diffusion-weighted imaging and a T 1 -weighted sequence optimized for intracortical myelin contrast. Using an automated pipeline, T 1 values were extracted at 20 depth-levels from each of 148 cortical regions. In each cortical region, T 1 values were used to infer myelin concentration and to construct a non-linearity index as a measure the spatial distribution of myelin across the cortical ribbon. The relationship of myelin concentration and the non-linearity index with other neuroanatomical properties were investigated. Five patients with multiple sclerosis were also assessed using the same protocol as positive controls. Results: Intracortical T 1 values decreased between the outer brain surface and the gray-white matter boundary following a slope that showed a slight leveling between 50% and 75% of cortical depth. Higher-order regions in the prefrontal, cingulate and insular cortices, displayed higher non-linearity indices than sensorimotor regions. Across all regions, there was a positive association between T 1 values and non-linearity indices (P < 10 125 ). Both T 1 values (P < 10 125 ) and non-linearity indices (P < 10 1215 ) were associated with cortical thickness. Higher myelin concentration but only in the deepest cortical levels was associated with increased subcortical fractional anisotropy (P = 0.05). Conclusions: We demonstrate the usefulness of an automatic, whole-brain method to perform depth-dependent examination of intracortical myelin organization. The extracted metrics, T 1 values and the non-linearity index, have characteristic patterns across cortical regions, and are associated with thickness and underlying white matter microstructure

    Quantitative Magnetic Resonance Imaging of Cortical Multiple Sclerosis Pathology

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    Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

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    Neurodevelopmental processes are widely believed to underlie schizophrenia. Analysis of brain texture from conventional magnetic resonance imaging (MRI) can detect disturbance in brain cytoarchitecture. We tested the hypothesis that patients with schizophrenia manifest quantitative differences in brain texture that, alongside discrete volumetric changes, may serve as an endophenotypic biomarker. Texture analysis (TA) of grey matter distribution and voxel-based morphometry (VBM) of regional brain volumes were applied to MRI scans of 27 patients with schizophrenia and 24 controls. Texture parameters (uniformity and entropy) were also used as covariates in VBM analyses to test for correspondence with regional brain volume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2 mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia

    The Brains of Babies: A Surface Based Approach To Study Cortical Development in Term and Preterm Human Infants

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    Half a million infants are born before term gestation each year in the United States. Although advances in newborn medicine have increased survival rates of very preterm infants to almost 90%, surviving preterm infants are at increased risk for developing lasting neurologic impairments. In order to develop a plausible neuroprotective strategy it is imperative that we improve our understanding of normal cortical development and develop tools to evaluate injury. Using a surface based approach we have characterized normal cortical development in healthy term infants and analyzed abnormalities associated with preterm birth. Accurate cortical surface reconstructions for each hemisphere of 12 healthy term gestation infants and 12 low-risk preterm infants at term equivalent postmenstrual age were generated from structural magnetic resonance imaging data using a novel segmentation algorithm. Data from the 12 term infants were used to establish the first population average surface based atlas of human cerebral cortex at term gestation. Comparing this atlas to a previously established atlas of adult cortex revealed that cortical structure in term infants is similar to the adult in many respects, including the pattern of individual variability and the presence of statistically significant structural asymmetries in lateral temporal cortex, suggesting that that several features of cortical shape are minimally reliant on the postnatal environment. Surprisingly, the pattern of postnatal expansion in surface area is strikingly non-uniform; regions of lateral temporal, parietal, and frontal cortex expand nearly twice as much as other regions in insular and medial occipital cortex. Differential expansion may point to differential sensitivity of cortical circuits to normal or aberrant childhood experiences. The pattern of human postnatal expansion parallels the pattern of evolutionary cortical expansion revealed by comparison between the human and the macaque monkey. Finally, in comparing term and preterm infants, region-specific alterations in cortical folding in the preterm population were found. The most striking shape differences were present in the orbitofrontal and inferior occipital regions with reductions in folding in the insular, lateral temporal, lateral parietal, and lateral frontal cortex. Overall these findings improve our understanding of normal cortical development and help elucidate the potential pathways for cortical injury in preterm infants

    Imaging of cognitive outcomes in patients with autoimmune encephalitis

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    Die Autoimmunenzephalitis ist eine kĂŒrzlich beschriebene entzĂŒndliche Erkrankung des zentralen Nervensystems, die GedĂ€chtnisdefizite, Psychosen, oder epileptische AnfĂ€lle hervorrufen kann. Derzeit ist hingegen noch nicht ausreichend verstanden, welche pathologischen VerĂ€nderungen zu den kognitiven Defiziten fĂŒhren und welche neuropsychologischen und bildgebenden Langzeitoutcomes zu erwarten sind. Anhand von strukturellen und funktionellen Bildgebungsanalysen zeigt diese Dissertation, dass kognitive Defizite auch nach der akuten Phase der Autoimmunenzephalitis fortbestehen können. Bei der LGI1-Enzephalitis gehen GedĂ€chtnisdefizite mit fokalen strukturellen LĂ€sionen im Hippocampus einher. Durch eine funktionelle Störung der Resting-State-KonnektivitĂ€t des Default-Mode- und Salienznetzwerkes beeintrĂ€chtigen diese HippocampuslĂ€sionen auch Hirnregionen außerhalb des limbischen Systems. Bei Patient:innen mit NMDA-Rezeptor-Enzephalitis finden sich in der longitudinalen neuropsychologischen Untersuchung trotz guter allgemeiner Genesung auch noch mehrere Jahre nach der Akutphase persistierende Defizite des GedĂ€chtnisses und exekutiver Funktionen. Zuletzt zeigt eine transdiagnostische Analyse, dass der anteriore Hippocampus eine erhöhte VulnerabilitĂ€t gegenĂŒber immunvermittelten pathologischen Prozessen aufweist. Diese Ergebnisse legen nahe, dass kognitive Symptome auch noch nach der Entlassung aus der stationĂ€ren Behandlung fortbestehen können. Sowohl umschriebene strukturelle HippocampuslĂ€sionen als auch VerĂ€nderungen in makroskopischen funktionellen Hirnnetzwerken tragen zur pathophysiologischen ErklĂ€rung dieser Symptome bei. Zudem erlauben diese Ergebnisse einen Einblick in neuroplastische VerĂ€nderungen des Gehirns und haben weitreichende Implikationen fĂŒr die Langzeitversorgung und das Design zukĂŒnftiger klinischer Studien.Autoimmune encephalitis is a recently described inflammatory disease of the central nervous system that can cause memory deficits, psychosis, or seizures. The trajectory of cognitive dysfunction and the underlying long-term imaging correlates are, however, not yet fully understood. By using advanced structural and functional neuroimaging, this thesis shows that cognitive deficits persist beyond the acute phase. In LGI1 encephalitis, MRI postprocessing revealed that memory deficits are related to focal structural hippocampal lesions. These hippocampal lesions propagate to brain areas outside the limbic system through aberrant resting-state connectivity of the default mode network (DMN) and the salience network. In NMDA receptor encephalitis, a longitudinal analysis of neuropsychological data describes persistent cognitive deficits, especially in the memory and executive domains, despite good physical recovery several years after the acute disease. Lastly, a transdiagnostic analysis reveals that the anterior hippocampus is particularly vulnerable to immune-mediated damage. In conclusion, these results demonstrate that cognitive symptoms in autoimmune encephalitis can persist beyond discharge from neurological care. Both discrete structural hippocampal damage and changes in macroscopic functional networks shed light on the pathophysiological basis of these symptoms. These findings help to explain how the brain responds to pathological damage and have substantial implications for long-term patient care and the design of future clinical studies

    The Architect Who Lost the Ability to Imagine: The Cerebral Basis of Visual Imagery.

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    While the loss of mental imagery following brain lesions was first described more than a century ago, the key cerebral areas involved remain elusive. Here we report neuropsychological data from an architect (PL518) who lost his ability for visual imagery following a bilateral posterior cerebral artery (PCA) stroke. We compare his profile to three other patients with bilateral PCA stroke and another architect with a large PCA lesion confined to the right hemisphere. We also compare structural images of their lesions, aiming to delineate cerebral areas selectively lesioned in acquired aphantasia. When comparing the neuropsychological profile and structural magnetic resonance imaging (MRI) for the aphantasic architect PL518 to patients with either a comparable background (an architect) or bilateral PCA lesions, we find: (1) there is a large overlap of cognitive deficits between patients, with the very notable exception of aphantasia which only occurs in PL518, and (2) there is large overlap of the patients' lesions. The only areas of selective lesion in PL518 is a small patch in the left fusiform gyrus as well as part of the right lingual gyrus. We suggest that these areas, and perhaps in particular the region in the left fusiform gyrus, play an important role in the cerebral network involved in visual imagery

    Towards Individualized Transcranial Electric Stimulation Therapy through Computer Simulation

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    Transkranielle Elektrostimulation (tES) beschreibt eine Gruppe von Hirnstimulationstechniken, die einen schwachen elektrischen Strom ĂŒber zwei nicht-invasiv am Kopf angebrachten Elektroden applizieren. Handelt es sich dabei um einen Gleichstrom, spricht man von transkranieller Gleichstromstimulation, auch tDCS abgekĂŒrzt. Die allgemeine Zielstellung aller Hirnstimulationstechniken ist Hirnfunktion durch ein VerstĂ€rken oder DĂ€mpfen von HirnaktivitĂ€t zu beeinflussen. Unter den Stimulationstechniken wird die transkranielle Gleichstromstimulation als ein adjuvantes Werkzeug zur UnterstĂŒtzung der mikroskopischen Reorganisation des Gehirnes in Folge von Lernprozessen und besonders der Rehabilitationstherapie nach einem Schlaganfall untersucht. Aktuelle Herausforderungen dieser Forschung sind eine hohe VariabilitĂ€t im erreichten Stimulationseffekt zwischen den Probanden sowie ein unvollstĂ€ndiges VerstĂ€ndnis des Zusammenspiels der der Stimulation zugrundeliegenden Mechanismen. Als SchlĂŒsselkomponente fĂŒr das VerstĂ€ndnis 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 grĂ¶ĂŸeren elektrischen FeldstĂ€rke ausgesetzt sind, ebenso einen höheren Stimulationseffekt erfahren. Damit kommt der Positionierung der Elektroden eine entscheidende Rolle fĂŒr die Stimulation zu. Allerdings verteilt sich das elektrische Feld wegen des heterogenen elektrischen LeitfĂ€higkeitsprofil des menschlichen Kopfes nicht uniform im Gehirn der Probanden. Außerdem ist das Verteilungsmuster auf Grund anatomischer Unterschiede zwischen den Probanden verschieden. Die triviale AbschĂ€tzung der Ausbreitung des elektrischen Feldes anhand der bloßen Position der Stimulationselektroden ist daher nicht ausreichend genau fĂŒr 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 fĂŒr ein breites Feld an Forschern zugĂ€nglich machen, wurden in den vergangenen Jahren fĂŒr den Anwendungsfall in gesunden Erwachsenen entwickelt. Jedoch bleibt die Simulation von Patienten mit krankhaftem Hirngewebe und strukturzerstörenden LĂ€sionen 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 verĂ€ndertem Hirngewebe verarbeiten zu können. Der grundlegende Arbeitsablauf zur Simulation wurde zunĂ€chst fĂŒr 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 ĂŒberfĂŒhrt 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 VerĂ€nderungen unterworfen, unter denen ein Verlust des Hirnvolumens sowie die Ausbildung mikroskopischer VerĂ€nderungen seiner Nervenfaserstruktur die Bedeutendsten sind. In einem zweiten Schritt wurde der Arbeitsablauf daher erweitert, um diese PhĂ€nomene des normalen Alterns zu berĂŒcksichtigen. Die vordergrĂŒndige Herausforderung in diesem Teilprojekt war die biophysikalische Modellierung der verĂ€nderten Hirnmikrostruktur, da die resultierenden VerĂ€nderungen im LeitfĂ€higkeitsprofil des Gehirns bisher noch nicht in der Literatur quantifiziert wurden. Die Erweiterung des Simulationsablauf zeichnete sich vorrangig dadurch aus, dass mit unsicheren elektrischen LeitfĂ€higkeitswerten gearbeitet werden konnte. Damit war es möglich den Einfluss der ungenau bestimmbaren elektrischen LeitfĂ€higkeit 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 verĂ€nderten Hirnfaserstruktur auf das elektrische Feld dann systematisch untersucht. Es wurde festgestellt, dass sich diese GewebsverĂ€nderungen hochgradig lokal und im Allgemeinen gering auswirken. Schließlich wurden in einem dritten Schritt Simulationen fĂŒr Schlaganfallpatienten durchgefĂŒhrt. Ihre großen, strukturzerstörenden LĂ€sionen wurden dabei mit einem höheren Detailgrad als in bisherigen Arbeiten modelliert und physikalisch abermals mit unsicheren LeitfĂ€higkeiten gearbeitet, was zu unsicheren elektrischen FeldabschĂ€tzungen fĂŒhrte. Es wurden individuell berechnete elektrische Felddaten mit der Hirnaktivierung von 18 Patienten in Verbindung gesetzt, unter BerĂŒcksichtigung der inhĂ€renten Unsicherheit in der Bestimmung der elektrischen Felder. Das Ziel war zu ergrĂŒnden, ob die Hirnstimulation einen positiven Einfluss auf die HirnaktivitĂ€t der Patienten im Kontext von Rehabilitationstherapie ausĂŒben und so die Neuorganisierung des Gehirns nach einem Schlaganfall unterstĂŒtzen kann. WĂ€hrend ein schwacher Zusammenhang hergestellt werden konnte, sind weitere Untersuchungen nötig, um diese Frage abschließend zu klĂ€ren.: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
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