Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

Copy Number Variations in DISC1 and DISC1-Interacting Partners in Major Mental Illness

Acknowledgements We would like to thank all of the patients, relatives and control individuals who participated in the study. We are indebted to the late Prof. Walter Muir, Chair of Developmental Psychiatry and Honorary Consultant in Learning Disability Psychiatry, University of Edinburgh, who initiated these studies and whose work was dedicated to the welfare of the patients who generously participated. We are also grateful to Mrs. Pat Malloy for her assistance with DNA collection and MAQ assays screening of the Scottish samples. The Scottish sample collection was supported by a grant from the Chief Scientist Office (CSO), part of the Scottish Government Health and Social Care Directorates. This research was funded by grants from the CSO to B.S.P. (grant CZB/4/610), The Academy of Medical Sciences/Wellcome Trust to M.J. (grant R41455) and The RS Macdonald Charitable Trust (grant D21419 together with J.H.), the Swedish Research Council (grants 2003-5158 and 2006-4472), the Medical Faculty, Umeå University, and the County Councils of Västerbotten and Norrbotten, Sweden, as well as by grants from the Fund for Scientific Research Flanders (FWO-F), the Industrial Research Fund (IWT) and the Special Research Fund of the University of Antwerp, Belgium. M.J. is funded by a Wellcome Trust Clinical Research Fellowship for MB PhD graduates (R42811). We acknowledge the contribution of the personnel of the VIB Genetic Service Facility (http://www.vibgeneticservicefacility.be/) for the genetic analysis of the Swedish samples. Research nurses Gunnel Johansson, Lotta Kronberg, Tage Johansson and Lisbeth Bertilsson are thankfully acknowledged for their help and expertise. The Betula Study was funded by the Swedish Research Council (grants 345-2003-3883 and 315-2004-6977). We also acknowledge the contribution by the staff in the Betula project

O cérebro sócio-musical: estudo de uma experiência de educação musical

A prática musical tem efeitos positivos no desenvolvimento humano, envolvendo aspectos cognitivos, emocionais, motivacionais e sociais, que implicam em alterações no processamento cerebral. O número de Programas de Educação Musical (PEMs) com enfoque em populações jovens em vulnerabilidade social tem crescido no Brasil e no mundo. Dessa maneira, torna-se importante a realização de estudos que verifiquem os efeitos de PEMs no desenvolvimento destas populações. O objetivo do presente estudo é investigar os impactos de uma experiência de um PEM sobre os aspectos psicológicos de seus estudantes, mais especificamente a autoestima, as habilidades sociais e o funcionamento executivo. A coleta de dados foi realizada em um PEM da cidade de Ribeirão Preto SP e em duas escolas regulares de ensino, uma particular e outra da rede pública. Participaram do estudo 69 crianças e adolescentes com idades entre 10 e 17 anos, divididos em três grupos, a saber: Grupo Iniciante (GI), composto por alunos com até 12 meses de matrícula no PEM; Grupo Experiente (GE), composto por alunos com mais de 24 meses de matrícula no PEM; e Grupo Controle (GC), constituído por participantes sem qualquer envolvimento com aprendizado musical. Cada grupo foi composto por 23 estudantes. Os três grupos de participantes responderam aos seguintes testes psicológicos: Escala de Autoestima de Rosenberg (EAR), Matson Evaluation of Social Skills with Youngsters (MESSY) e Teste de Stroop. Também foram realizadas entrevistas semi-estruturadas com todos os estudantes dos grupos GI e GE, dez estudantes do PEM que não compuseram nenhum grupo por não possuírem o pré-requisito de tempo de matrícula exigido, seis responsáveis legais dos estudantes e doze profissionais do PEM. As entrevistas tiveram a função de fornecerem relatos verbais a respeito dos impactos percebidos nos estudantes pelo envolvimento com o PEM. Os dados dos testes psicológicos foram analisados através dos testes estatísticos ANOVA, Mann-Whitney e t de Student e as entrevistas foram analisadas através da investigação qualitativa em educação. As análises dos testes psicológicos mostraram que os GI e GE não possuem diferenças entre si para nenhuma das variáveis de estudo. O GC apresentou escores inferiores aos GI e GE para a Autoestima e escores superiores para Solidão e Ansiedade Social, indicando que o envolvimento com o PEM pode acarretar em ganhos nessas habilidades. A partir da análise das entrevistas foram construídas três categorias de codificação relacionadas a impactos comportamentais do envolvimento com o PEM, a saber: relacionamento interpessoal, desenvolvimento de habilidades intrapessoais e envolvimento com música e desenvolvimento humano na perspectiva de profissionais e responsáveis legais. A análise das entrevistas indicou que a participação no PEM está relacionada a impactos positivos na autoestima, habilidades sociais e funcionamento executivo dos participantes. Os resultados foram discutidos buscando interrelaciona-los de maneira a integrar os dados colhidos por meio dos testes psicológicos e através das entrevistas. Conclui-se que a participação em PEMs com enfoque no resgate social de populações vulneráveis possui influência no desenvolvimento de crianças e adolescentes, indicando que o uso da educação musical caracteriza uma importante estratégia de intervenção social.

Neuroscience at the new millennium : priorities and plans for the National Institute of Neurological Disorders and Stroke, fiscal years 2000-2001.

"August 1999."

Glutathione in Parkinson's disease

Thesis (Ph.D.)--University of Washington, 2016-03

Non-invasive Detection of Cortical Control Signals for Brain-Computer Interfaces

Thesis (Ph.D.)--University of Washington, 2016-05

An ancient neurotrophin code in zebrafish; the Runx/Cbfβ complex specifies the fate switch from TrkB+ to TrkC+ nociceptors and sensory receptor expression

Thesis (Ph.D.)--University of Washington, 2016-06

Regulation of dendrite growth, placement, and patterning in Drosophila melanogaster class 4 dendrite arborization neurons

Thesis (Ph.D.)--University of Washington, 2016-06

Gene-environment interactions between adult lead exposure and Apolipoprotein E4 on adult hippocampal neurogenesis and cognitive behavior in mice

Thesis (Ph.D.)--University of Washington, 2016-06

Experimental muscle pain changes feedforward postural responses of the trunk muscles

Many studies have identified changes in trunk muscle recruitment in clinical low back pain (LBP). However, due to the heterogeneity of the LBP population these changes have been variable and it has been impossible to identify a cause-effect relationship. Several studies have identified a consistent change in the feed-forward postural response of transversus abdominis (TrA), the deepest abdominal muscle, in association with arm movements in chronic LBP. This study aimed to determine whether the feedforward recruitment of the trunk muscles in a postural task could be altered by acute experimentally induced LBP. Electromyographic (EMG) recordings of the abdominal and paraspinal muscles were made during arm movements in a control trial, following the injection of isotonic (non-painful) and hypertonic (painful) saline into the longissimus muscle at L4, and during a 1-h follow-up. Movements included rapid arm flexion in response to a light and repetitive arm flexion-extension. Temporal and spatial EMG parameters were measured. The onset and amplitude of EMG of most muscles was changed in a variable manner during the period of experimentally induced pain. However, across movement trials and subjects the activation of TrA was consistently reduced in amplitude or delayed. Analyses in the time and frequency domain were used to confirm these findings. The results suggest that acute experimentally induced pain may affect feedforward postural activity of the trunk muscles. Although the response was variable, pain produced differential changes in the motor control of the trunk muscles, with consistent impairment of TrA activity.

Pain and motor control of the lumbopelvic region: effect and possible mechanisms

Many authors report changes in the control of the trunk muscles in people with low back pain (LBP). Although there is considerable disagreement regarding the nature of these changes, we have consistently found differential effects on the deep intrinsic and superficial muscles of the lumbopelvic region. Two issues require consideration; first, the potential mechanisms for these changes in control, and secondly, the effect or outcome of changes in control for lumbopelvic function. Recent data indicate that experimentally induced pain may replicate some of the changes identified in people with LBP. While this does not exclude the possibility that changes in control of the trunk muscles may lead to pain, it does argue that, at least in some cases, pain may cause the changes in control. There are many possible mechanisms, including changes in excitability in the motor pathway, changes in the sensory system, and factors associated. with the attention demanding, stressful and fearful aspects of pain. A new hypothesis is presented regarding the outcome from differential effects of pain on the elements of the motor system. Taken together these data argue for strategies of prevention and rehabilitation of LBP (C) 2003 Elsevier Science Ltd. All rights reserved.

Presynaptic Anchoring of PKA by AKAP7 is Required for Pattern Separation by Dentate Gyrus

Thesis (Ph.D.)--University of Washington, 2016-06

A comprehensive analysis of sexual dimorphism in the midbrain dopamine system

Thesis (Ph.D.)--University of Washington, 2016-06

Functionality, Robustness and Control of Nonlinear Network Dynamics: Modeling and Understanding the C. elegans Connectome

Thesis (Ph.D.)--University of Washington, 2016-06