Demenzverdacht, aber normale neuropsychologische Screening-Untersuchung - wie weiter?

Die Demenz betrifft viele, belastet Angehörige und führt zu hohen Kosten, weshalb die Schweiz eine Sensibilisierungskampagne lancierte, um u.a. die Früherkennung der Demenz zu fördern. Dank der Früherkennung erleben Patienten und Angehörige Vorteile, wie weniger Notfallzuweisungen oder spätere Heimeintritte. Die Früherkennung ist aber schwierig, wenn Patienten zwar Gedächtnisprobleme beklagen, die Screening-Tests aber normal ausfallen. Möglicherweise helfen Geruchstests und weitere klinische Zeichen bei der Entscheidung, welche Patienten weiter abgeklärt werden. Die Zeit für funktionelle Bildgebungen und Biomarker ist noch nicht reif. Zentral bleibt bei kognitiven Beschwerden und normalem Screening das Gespräch mit Patient und Angehörigen, um nächste Schritte gemeinsam zu beschliessen. Der Hausarzt nimmt dabei eine zentrale, koordinierende und beratende Funktion ein, um Menschen mit Gedächtnisstörungen kompetent und effizient zu betreuen.

Olfactory bulb volume predicts therapeutic outcome in major depression disorder

The volume of the olfactory bulb (OB) is strongly reduced in patients with major depressive disorder (MDD) and this group exhibits markedly decreased olfactory function. It has been suggested that olfactory input is important for maintaining balance in limbic neurocircuits. The aim of our study was to investigate whether reduced OB volume is associated with response to therapy in MDD. Twenty-four inpatients (all women, age 21-49 years, mean 38 ± 10 years SD) with MDD and 36 healthy controls (all women, age 20-52 years, mean 36 ± 10 years SD) underwent structural MRI. OB volume was compared between responders (N = 13) and non-responders (N = 11) to psychotherapy. Retest of OB volume was performed about 6 months after the end of therapy in nine of the patients. Therapy responders exhibited no significant difference in OB volume compared to healthy controls. However, average OB volume of non-responders was 23 % smaller compared to responders (p = .0011). Furthermore, OB volume was correlated with the change of depression severity (r = .46, p = .024). Volume of the OB did not change in the course of therapy. OB volume may be a biological vulnerability factor for the occurrence and/or maintenance of depression, at least in women.

Functional connectivity measured with magnetoencephalography identifies persons with HIV disease

There is need for a valid and reliable biomarker for HIV Associated Neurocognitive Disorder (HAND). The purpose of the present study was to provide preliminary evidence of the potential utility of neuronal functional connectivity measures obtained using magnetoencephalography (MEG) to identify HIV-associated changes in brain function. Resting state, eyes closed, MEG data from 10 HIV-infected individuals and 8 seronegative controls were analyzed using mutual information (MI) between all pairs of MEG sensors to ...

Optimisation of algorithms to compute information theoretic indexes

Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document. Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document.

Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

Time scales in cognitive neuroscience

Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.

Análisis de la actividad neuronal y cerebral mediante técnicas de redes complejas

El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

Mental chronometry using latency-resolved functional MRI

Vascular responses to neural activity are exploited as the basis of a number of brain imaging techniques. The vascular response is thought to be too slow to resolve the temporal sequence of events involved in cognitive tasks, and hence, imaging studies of mental chronometry have relied on techniques such as the evoked potential. Using rapid functional MRI (fMRI) of single trials of two simple behavioral tasks, we demonstrate that while the microvascular response to the onset of neural activity is delayed consistently by several seconds, the relative timing between the onset of the fMRI responses in different brain areas appears preserved. We examined a number of parameters that characterize the fMRI response and determined that its onset time is best defined by the inflection point from the resting baseline. We have found that fMRI onset latencies determined in this manner correlate well with independently measurable parameters of the tasks such as reaction time or stimulus presentation time and can be used to determine the origin of processing delays during cognitive or perceptual tasks with a temporal accuracy of tens of milliseconds and spatial resolution of millimeters.

Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia

Neuropathological and brain imaging studies suggest that schizophrenia may result from neurodevelopmental defects. Cytoarchitectural studies indicate cellular abnormalities suggestive of a disruption in neuronal connectivity in schizophrenia, particularly in the dorsolateral prefrontal cortex. Yet, the molecular mechanisms underlying these findings remain unclear. To identify molecular substrates associated with schizophrenia, DNA microarray analysis was used to assay gene expression levels in postmortem dorsolateral prefrontal cortex of schizophrenic and control patients. Genes determined to have altered expression levels in schizophrenics relative to controls are involved in a number of biological processes, including synaptic plasticity, neuronal development, neurotransmission, and signal transduction. Most notable was the differential expression of myelination-related genes suggesting a disruption in oligodendrocyte function in schizophrenia.

Pain perception: Is there a role for primary somatosensory cortex?

Anatomical, physiological, and lesion data implicate multiple cortical regions in the complex experience of pain. These regions include primary and secondary somatosensory cortices, anterior cingulate cortex, insular cortex, and regions of the frontal cortex. Nevertheless, the role of different cortical areas in pain processing is controversial, particularly that of primary somatosensory cortex (S1). Human brain-imaging studies do not consistently reveal pain-related activation of S1, and older studies of cortical lesions and cortical stimulation in humans did not uncover a clear role of S1 in the pain experience. Whereas studies from a number of laboratories show that S1 is activated during the presentation of noxious stimuli as well as in association with some pathological pain states, others do not report such activation. Several factors may contribute to the different results among studies. First, we have evidence demonstrating that S1 activation is highly modulated by cognitive factors that alter pain perception, including attention and previous experience. Second, the precise somatotopic organization of S1 may lead to small focal activations, which are degraded by sulcal anatomical variability when averaging data across subjects. Third, the probable mixed excitatory and inhibitory effects of nociceptive input to S1 could be disparately represented in different experimental paradigms. Finally, statistical considerations are important in interpreting negative findings in S1. We conclude that, when these factors are taken into account, the bulk of the evidence now strongly supports a prominent and highly modulated role for S1 cortex in the sensory aspects of pain, including localization and discrimination of pain intensity.

Preserved speech abilities and compensation following prefrontal damage.

Lesions to left frontal cortex in humans produce speech production impairments (nonfluent aphasia). These impairments vary from subject to subject and performance on certain speech production tasks can be relatively preserved in some patients. A possible explanation for preservation of function under these circumstances is that areas outside left prefrontal cortex are used to compensate for the injured brain area. We report here a direct demonstration of preserved language function in a stroke patient (LF1) apparently due to the activation of a compensatory brain pathway. We used functional brain imaging with positron emission tomography (PET) as a basis for this study.

Cognición no social y neuroimagen en TEA sin discapacidad intelectual

La presente tesis doctoral está constituida por tres estudios independientes pero relacionados entre sí: 1) Estimation of the intelligence quotient using Wechsler intelligence scales in children and adolescents with Asperger syndrome (SA), 2) Executive function is affected in autism spectrum disorder, but does not correlate with intelligence, y 3) Reduced gyrification is related to reduced interhemispheric connectivity in autism spectrum disorders. El objetivo general es estudiar las alteraciones cognitivas en niños y adolescentes con un Trastorno del Espectro Autista (TEA) sin discapacidad intelectual (SDI) asociada, particularmente en cuanto a sus aspectos en funcionamiento general (puntuaciones en escala de inteligencia Wechsler) y funciones ejecutivas, y estudiar la girificación y conectividad en el córtex prefrontal teniendo en cuenta su relación con las funciones ejecutivas. Como objetivos específicos: i) Medir los perfiles de inteligencia en niños y adolescentes con SA; ii) Evaluar la validez de cinco formas abreviadas de las escalas Wechsler de inteligencia en niños y adolescentes con SA, frente a la versión completa, teniendo en cuenta los criterios propuestos por Resnick & Entin, (1971); iii) Evaluar las funciones ejecutivas en una muestra homogénea de niños y adolescentes con TEA-SDI y comparar sus puntuaciones con las obtenidas por un grupo de niños y adolescentes sanos pareados por edad, años de educación, sexo, estatus socioeconómico y cociente intelectual (CI); iv) Evaluar si los déficits en funciones ejecutivas correlacionan con déficits en inteligencia general; v) Evaluar si los déficits en funcionamiento ejecutivo en los niños y adolescentes con TEA-SDI correlacionan con su nivel de funcionamiento o con la gravedad de los síntomas que presentan; vi) Estudiar la relación entre girificación y conectividad de la sustancia blanca, prestando especial atención a los cambios relacionados con la edad en una muestra de pacientes con TEA de alto funcionamiento; vii) Estudiar la girificación y conectividad en el córtex prefrontal teniendo en cuenta su relación con las funciones ejecutivas; y viii) Replicar los resultados obtenidos en nuestra muestra con los datos procedentes de una base independiente de niños y adolescentes con autismo de alto funcionamiento (Autism Brain Imaging Data Exchange, ABIDE)...

L'étude in vivo de l'impact de la pression pulsée sur les capillaires cérébraux de souris

Plusieurs décennies de recherche ont permis de mieux comprendre les effets de l’athérosclérose sur le système cardiovasculaire, d’améliorer la prévention et de développer des traitements efficaces. Les effets de l’athéroslérose sur le cerveau demeurent toutefois mal compris même si le lien entre le fonctionnement cognitif et la santé du système vasculaire est maintenant bien établi. La venue de nouvelles méthodes d’imagerie telle la microscopie laser à 2-photons (TPLM) permet d’étudier l’impact de certaines maladies sur la microvasculature cérébrale en mesurant le flux sanguin dans des vaisseaux uniques situés dans des régions cérébrales millimétriques sous la surface. Les résultats des études in vitro peuvent dorénavant être corrélés à ceux obtenus in vivo. En premier lieu, ce mémoire revoit la théorie ayant permis le développement de la TPLM qui permet de prendre des mesures hémodynamiques in vivo dans des vaisseaux de très petits calibres tels des capillaires cérébraux de souris. Par la suite, son utilisation est décrite chez des souris anesthésiées afin de comparer les mesures d’hémodynamie cérébrale tels la vitesse des globules rouges, le flux de globules rouges, le flux sanguin cérébral, l’hématocrite sanguin et le diamètre des vaisseaux. Finalement, nous avons comparé les données hémodynamiques entre des souris de 3 mois normales (WT ; n=6) et des souris atteintes d’athérosclérose précoce (ATX ; n=6). Les résultats obtenus sur un nombre total de 209 capillaires (103 pour les souris WT et 106 pour les souris ATX) démontrent que les souris ATX possèdent une vitesse des globules rouges (+40%) plus grande, un flux de globule rouge plus grand (+12%) et un flux capillaire plus élevé (+14%) sans démontrer pour aucun de ces paramètres, une différence statistiquement significative. L’hématocrite moyen (35±4% vs 33±2% ; p=0.71) et le diamètre moyen des vaisseaux (4.88±0.22μm vs 4.86±0.20μm ; p=0.23) étaient également comparables. La vitesse des globules rouges a démontré une faible corrélation avec le diamètre des vaisseaux (r=0.39) et avec le flux de globules rouges/seconde (r=0.59). En conclusion, les travaux menés dans le cadre de ce mémoire de maîtrise permettent d'envisager, grâce aux nouvelles méthodes d’imagerie cérébrale telle la TPLM, une meilleure compréhension des mécanismes hémodynamiques sous-jacents à la microcirculation cérébrale. L’effet d’une pression pulsée augmentée, tel que proposée dans l’athérosclérose reste cependant à démontrer avec cette méthode d’imagerie.

Plasticité du cortex visuel: «homéodynamie» des connexions neuronales et modèle d’effets d’antidépresseurs

Les informations sensorielles sont traitées dans le cortex par des réseaux de neurones co-activés qui forment des assemblées neuronales fonctionnelles. Le traitement visuel dans le cortex est régit par différents aspects des caractéristiques neuronales tels que l’aspect anatomique, électrophysiologique et moléculaire. Au sein du cortex visuel primaire, les neurones sont sélectifs à divers attributs des stimuli tels que l’orientation, la direction, le mouvement et la fréquence spatiale. Chacun de ces attributs conduit à une activité de décharge maximale pour une population neuronale spécifique. Les neurones du cortex visuel ont cependant la capacité de changer leur sélectivité en réponse à une exposition prolongée d’un stimulus approprié appelée apprentissage visuel ou adaptation visuelle à un stimulus non préférentiel. De ce fait, l’objectif principal de cette thèse est d’investiguer les mécanismes neuronaux qui régissent le traitement visuel durant une plasticité induite par adaptation chez des animaux adultes. Ces mécanismes sont traités sous différents aspects : la connectivité neuronale, la sélectivité neuronale, les propriétés électrophysiologiques des neurones et les effets des drogues (sérotonine et fluoxétine). Le modèle testé se base sur les colonnes d’orientation du cortex visuel primaire. La présente thèse est subdivisée en quatre principaux chapitres. Le premier chapitre (A) traite de la réorganisation du cortex visuel primaire suite à une plasticité induite par adaptation visuelle. Le second chapitre (B) examine la connectivité neuronale fonctionnelle en se basant sur des corrélations croisées entre paires neuronales ainsi que sur des corrélations d’activités de populations neuronales. Le troisième chapitre (C) met en liaison les aspects cités précédemment (les effets de l’adaptation visuelle et la connectivité fonctionnelle) aux propriétés électrophysiologiques des neurones (deux classes de neurones sont traitées : les neurones à décharge régulière et les neurones à décharge rapide ou burst). Enfin, le dernier chapitre (D) a pour objectif l’étude de l’effet du couplage de l’adaptation visuelle à l’administration de certaines drogues, notamment la sérotonine et la fluoxétine (inhibiteur sélectif de recapture de la sérotonine). Méthodes En utilisant des enregistrements extracellulaires d’activités neuronales dans le cortex visuel primaire (V1) combinés à un processus d’imagerie cérébrale optique intrinsèque, nous enregistrons l’activité de décharge de populations neuronales et nous examinons l’activité de neurones individuels extraite des signaux multi-unitaires. L’analyse de l’activité cérébrale se base sur différents algorithmes : la distinction des propriétés électrophysiologiques des neurones se fait par calcul de l’intervalle de temps entre la vallée et le pic maximal du potentiel d’action (largeur du potentiel d’action), la sélectivité des neurones est basée sur leur taux de décharge à différents stimuli, et la connectivité fonctionnelle utilise des calculs de corrélations croisées. L’utilisation des drogues se fait par administration locale sur la surface du cortex (après une craniotomie et une durotomie). Résultats et conclusions Dans le premier chapitre, nous démontrons la capacité des neurones à modifier leur sélectivité après une période d’adaptation visuelle à un stimulus particulier, ces changements aboutissent à une réorganisation des cartes corticales suivant un patron spécifique. Nous attribuons ce résultat à la flexibilité de groupes fonctionnels de neurones qui étaient longtemps considérés comme des unités anatomiques rigides. En effet, nous observons une restructuration extensive des domaines d’orientation dans le but de remodeler les colonnes d’orientation où chaque stimulus est représenté de façon égale. Ceci est d’autant plus confirmé dans le second chapitre où dans ce cas, les cartes de connectivité fonctionnelle sont investiguées. En accord avec les résultats énumérés précédemment, les cartes de connectivité montrent également une restructuration massive mais de façon intéressante, les neurones utilisent une stratégie de sommation afin de stabiliser leurs poids de connectivité totaux. Ces dynamiques de connectivité sont examinées dans le troisième chapitre en relation avec les propriétés électrophysiologiques des neurones. En effet, deux modes de décharge neuronale permettent la distinction entre deux classes neuronales. Leurs dynamiques de corrélations distinctes suggèrent que ces deux classes jouent des rôles clés différents dans l’encodage et l’intégration des stimuli visuels au sein d’une population neuronale. Enfin, dans le dernier chapitre, l’adaptation visuelle est combinée avec l’administration de certaines substances, notamment la sérotonine (neurotransmetteur) et la fluoxétine (inhibiteur sélectif de recapture de la sérotonine). Ces deux substances produisent un effet similaire en facilitant l’acquisition des stimuli imposés par adaptation. Lorsqu’un stimulus non optimal est présenté en présence de l’une des deux substances, nous observons une augmentation du taux de décharge des neurones en présentant ce stimulus. Nous présentons un modèle neuronal basé sur cette recherche afin d’expliquer les fluctuations du taux de décharge neuronale en présence ou en absence des drogues. Cette thèse présente de nouvelles perspectives quant à la compréhension de l’adaptation des neurones du cortex visuel primaire adulte dans le but de changer leur sélectivité dans un environnement d’apprentissage. Nous montrons qu’il y a un parfait équilibre entre leurs habiletés plastiques et leur dynamique d’homéostasie.