Les cauchemars sont des rêves très dysphoriques, bien remémorés au réveil, dont le contenu est souvent caractérisé par la présence de menace à la survie, la sécurité ou l’intégrité physique. Les cauchemars surviendraient surtout durant le sommeil paradoxal. Bien qu’il s’agisse pour la plupart des gens d’une expérience rare et bénigne, il est de plus en plus apparent que les cauchemars entretiennent des liens avec la psychopathologie. Plusieurs populations psychiatriques ont une fréquence des cauchemars supérieure à la population générale. Au-delà d’être simplement associés à la psychopathologie, les cauchemars peuvent par exemple prédire le développement du trouble de stress post-traumatique, constituer un facteur de risque pour le suicide, ou amplifier des difficultés de régulation émotionnelle. Ainsi, les cauchemars peuvent être pertinents pour la clinique. Malgré cela, leur pathophysiologie demeure un sujet peu exploré. Plus spécifiquement, il existe peu de recherche portant sur leurs corrélats neuronaux. Selon le modèle neurocognitif des cauchemars, les cauchemars constitueraient un échec de la fonction normale des rêves, qui serait d’aider à la régulation émotionnelle en mêlant le contenu de mémoires émotionnellement négatives à celui d’autres mémoires plus neutres, permettant ainsi l’extinction de ces mémoires négatives. La fonction du rêve, et donc la présence de cauchemars, reposerait sur un réseau limbique-préfrontal composé du cortex préfrontal médian et cingulaire antérieur, de l’hippocampe et de l’amygdale. L’objectif de cette thèse est d’étudier les mécanismes cérébraux potentiellement impliqués dans les cauchemars de manière à tester le modèle neurocognitif des cauchemars. Dans une première étude, nous avons utilisé l’analyse spectrale pour comparer l’activité EEG à l’éveil et durant le sommeil entre 18 participants rapportant des cauchemars fréquents et 15 participants contrôles. Les résultats démontrent davantage d’activité 2-5Hz à l’éveil, en sommeil lent et en sommeil paradoxal, principalement aux électrodes centrales et frontales, chez les participants avec cauchemars comparativement aux participants contrôles. Ces résultats étaient plus apparents en sommeil paradoxal. Ces résultats répliquent partiellement une étude antérieure démontrant une activité 3-4Hz plus importante pour des participants avec cauchemars que des contrôles. L’apport original de l’étude réside surtout dans sa démonstration d’altérations de l’activité EEG visibles autant durant l’éveil que durant le sommeil, ce qui constitue un appui à la continuité éveil-sommeil avancée par le modèle neurocognitif des cauchemars. Dans une deuxième étude, nous avons utilisé la tomographie par émission monophotonique pour enregistrer le flux sanguin cérébral régional (une mesure indirecte de l’activité neuronale) de 18 participants avec cauchemars fréquents durant le visionnement d’images émotionnellement négatives ou neutres. Les résultats démontrent que la sévérité des cauchemars est associée négativement au FSCr de régions inclues dans le modèle neurocognitif (cortex cingulaire antérieur et préfrontal médian), mais aussi d’autres régions corticales (frontales, temporales, insula). En résumé, cette thèse apporte un appui partiel au modèle neurocognitif des cauchemars, mais souligne également certaines limites du modèle et propose de nouvelles avenues de recherche pour comprendre les mécanismes neuronaux des cauchemars. Cette thèse souligne aussi des implications cliniques à l’étude des corrélats neuronaux des cauchemars, notamment par rapport à la compréhension des traitements (pharmacologiques ou non-pharmacologiques). / Nightmares are defined as highly dysphoric dreams that are well-remembered upon awakening, frequently involving threats to survival, security or physical integrity. They are thought to happen most frequently during rapid eye movement sleep. For most people, nightmares are a rare occurrence and are mostly benign. However, research shows that nightmares are linked to psychopathology. Many psychiatric populations have an elevated nightmare frequency compared to the general population. In addition to being associated with psychopathology, nightmares can for example predict the development of post-traumatic stress disorder, be a risk factor for suicide, or diminish emotional regulation capabilities. Therefore, nightmares can be relevant to clinical practice. However, research about their pathophysiology is lacking. More specifically, there is a lack of research on the neural correlates of nightmares. According to the neurocognitive model of nightmares, nightmares are a breakdown of the normal function of dreams. Dreams are thought to help emotional regulation by combining emotionally negative memories with more neutral memories, thereby extinguishing these negative memories. The function of dreams, and therefore the occurrence of nightmares, is thought to be supported by a limbic-prefrontal circuit comprising medial prefrontal and anterior cingulate cortices, hippocampus, and amygdala. The aim of this dissertation is to study brain mechanisms involved in nightmares, thereby testing the neurocognitive model of nightmares. In study 1, we used spectral analysis to compare EEG activity in wake and sleep between 18 frequent nightmare recallers and 15 control participants. The results show higher 2-5Hz activity during wake, non-REM and REM sleep, mainly for central and frontal derivations, for frequent nightmare recallers compared to controls. Differences were most apparent for REM sleep. These results partly replicate past work showing heightened 3-4Hz activity in frequent nightmare recallers compared to controls. It improves upon past work by demonstrating cross-state alterations of EEG activity, thereby supporting the cross-state continuity assumption of the neurocognitive model of nightmares. In study 2, we used single photon emission tomography to obtain regional cerebral blood flow (an indirect measure of neuronal activity) from 18 frequent nightmare recallers while they were viewing pictures with a negative or neutral emotional valence. Results demonstrate that the severity of nightmares is negatively associated with brain regions included (medial prefrontal and anterior cingulate cortices) and not included (frontal, temporal and insular regions) in the neurocognitive model of nightmares. In sum, this dissertation offers partial support to the neurocognitive model of nightmares, while also highlighting limits of the model and proposing ideas for future investigations on the neural correlates of nightmares. This dissertation also discusses some clinical implications of the study of the neural correlates of nightmares, most importantly providing a better understanding of nightmare-reducing treatments (pharmacological or non-pharmacological).

Le diagnostic de mort cérébrale est une étape complexe et chronophage lors de l'évaluation des patients en soins intensifs soupçonnés d'être en décès neurologique. Bien que les critères neurologiques cliniques qui déterminent la mort cérébrale soient largement acceptés dans le monde, le diagnostic reste imparfait et l'utilisation de tests auxiliaires tels que la perfusion tomographique cérébrale (CTP) est souvent nécessaire pour le confirmer. L'objectif principal de ce travail était d'explorer la faisabilité de classer la mort cérébrale à partir de scans CTP par le traitement automatique de l’image. Les scans CTP de l'étude prospective canadienne multicentrique de validation du CTP pour le diagnostic de décès neurologique ont été regroupées à partir de 11 sites participants (INDex-CTP, ClinicalTrials.gov, NCT03098511). Des caractéristiques spatiales et temporelles ont été extraites en utilisant une combinaison de deux modules de convolution et utilisées pour prédire la mort neurologique. Les performances du modèle ont également été évaluées sur différentes catégories de blessures cérébrales. Les études de 217 patients ont été utilisées pour entraîner le modèle. Nous rapportons une AUC de 0,79 (IC95 % 0,76-0,82), un score F1 de 0,82 (IC95 % 0,80-0,83), une précision de 0,92 (IC95 % 0,91-0,93), un rappel de 0,76 (CI95 % 0,72-0,79) ainsi qu'une valeur prédictive négative de 0,49 (CI95 % 0,45-0,53). En raison de la petite taille d'échantillon, nous n'avons pas effectué de tests statistiques sur des sous-ensembles de lésions cérébrales, mais avons signalé une valeur prédictive négative du modèle présumé plus élevée sur des blessures cérébrales anoxiques avec 0,82 (CI95 % 0,77-0,87). Ce modèle montre des preuves préliminaires soutenant la faisabilité de développer un réseau neuronal profond pour classer les patients comateux comme étant neurologiquement décédés ou non. Des recherches supplémentaires sont nécessaires pour valider et améliorer le modèle en utilisant des ensembles de données plus vastes et diversifiés. / The diagnostic of brain death is a complex and chronophage step when evaluating patients in critical care suspected of being neurologically deceased. Although the clinical neurological criteria that determine brain death are mostly accepted worldwide, the diagnosis remains imperfect and often the use of ancillary tests such as brain computed tomography perfusion (CTP) are required to confirm it. The main objective of this work was to explore the feasibility of classifying brain death from CTP scans using deep learning. CTP studies from a multicenter prospective diagnostic cohort study with the primary objective of evaluating the diagnostic accuracy of neurological death using CTP were pooled from 11 participating sites (INDex-CTP, ClinicalTrials.gov, NCT03098511). Spatial and temporal features were extracted using a combination of two convolution modules and used to predict neurological death. The performance of the model was also evaluated on subsets of cerebral injuries. 217 patients' studies were used to train the model. We report an AUC of 0.79 (IC95% 0.76-0.82), a F1 score of 0.82 (IC95% 0.80-0.83), a precision of 0.92 (IC95% 0.91-0.93), a recall of 0.76 (CI95% 0.72-0.79) as well as a negative predictive value of 0.49 (CI95% 0.45-0.53). Due to a lack of sample size, we did not perform statistical tests on subsets of cerebral injury, but report suspected higher model negative predictive value on anoxic cerebral injury with 0.82 (CI95% 0.77-0.87). This model shows preliminary evidence supporting the feasibility of developing a deep neural network to classify comatose patients as neurologically deceased or not. Additional research is needed to validate and refine the model by employing larger and more diverse datasets.

Ce mémoire est séparé en deux volets, tous deux axés sur la spectroscopie proche infra-rouge (NIRS) pour la quantification des paramètres hémodynamiques. La NIRS est principalement basée sur la mesure des coefficients d'absorption (μa) et de dispersion (μs’) des tissus afin de retrouver les concentrations d'oxy- et de déoxyhémoglobine dans le sang. L'imagerie à l'aide de la NIRS est basée sur le parcours des photons à travers le tissu biologique à différentes longueurs d'onde du spectre proche infra-rouge. Le premier appareil de NIRS dont il sera question est un appareil de spectroscopie résolue dans le temps. Ce type de système retrouve des concentrations absolues d'hémoglobine à l'aide d'un bandeau placé sur la peau d’un sujet, dans ce cas-ci sur le front. Le modèle d’analyse des données permet la séparation des contributions extra-cérébrales et cérébrales aux données. Cette méthode fournit des données plus exactes sur la saturation en oxygène du cerveau, par rapport à un modèle homogène où le signal est contaminé par les couches superficielles. Une étude sur les changements hémodynamiques cérébraux de jeunes adultes pendant une activité physique a été réalisée, et l’article en détaillant les résultats est transcrit au chapitre 2. Le chapitre 3 comprend un retour sur cette étude et aborde les possibilités de travaux futurs. La seconde partie de mes travaux s’est déroulée sous forme de stage en entreprise durant l’été 2016. Sous la supervision de Dennis Hueber, Ph. D., et Beniamino Barbieri, Ph. D., j’ai effectué des recherches portant sur un appareil de NIRS manufacturé par la compagnie ISS Inc. et dont un prototype se trouve actuellement dans le laboratoire de mon superviseur Mathieu Dehaes, Ph. D. Cet appareil combine deux modalités d’imagerie optique, soit la NIRS dans le domaine des fréquences et la spectroscopie de corrélation diffuse. Le chapitre 4 détaille les tâches que j’ai réalisées durant ce temps, de même que les résultats des analyses que j’ai effectuées. / This master’s thesis is separated in two phases, both focused on near infrared spectroscopy for the quantification of hemodynamic parameters. NIRS is based on the measure of absorption (μa) and scattering (μs’) coefficients of tissues in order to recover the oxy- and deoxyhemoglobin concentrations in the blood. Its results are based on the photon propagation in tissue at different near-infrared wavelengths. The first NIRS system used during my studies is a time-resolved spectroscopy system. This device allowed us to retrieve absolute hemoglobin concentrations using a headband placed over the subject’s skin and centered on their forehead. The data analysis model which we used allowed us to separate extra-cerebral and cerebral contributions of the signal. This method yielded quantitative absolute measures of cerebral oxygen saturation as opposed to the traditional homogenous model where the signal is contaminated by superficial layers. A study on cerebral hemodynamic changes in young adults during exercise was conducted, and the published article detailing its results is transcribed in Chapter 2. Chapter 3 includes a review of this study and discusses potential future works. The second part of my research consisted in an industrial internship during the summer of 2016. Under the supervision of Dennis Hueber, Ph. D., and Beniamino Barbieri, Ph. D., I have worked on a NIRS device manufactured by ISS Inc., a prototype of which is currently in the laboratory of my supervisor Mathieu Dehaes, Ph. D. This device combines two NIRS modalities: frequency-domain NIRS and diffuse correlation spectroscopy. Chapter 4 details the work I have performed at ISS and the results of my research and analysis.

La profondeur possible d’imagerie en laser-scanning microscopie est limitée non seulement par la distance de travail des lentilles de objectifs mais également par la dégradation de l’image causée par une atténuation et une diffraction de la lumière passant à travers l’échantillon. Afin d’étendre cette limite, il est possible, soit de retourner le spécimen pour enregistrer les images depuis chaque côté, or couper progressivement la partie supérieure de l’échantillon au fur et à mesure de l‘acquisition. Les différentes images prises de l’une de ces manières doivent ensuite être combinées pour générer un volume unique. Cependant, des mouvements de l’échantillon durant les procédures d’acquisition engendrent un décalage non seulement sur en translation selon les axes x, y et z mais également en rotation autour de ces même axes, rendant la fusion entres ces multiples images difficile. Nous avons développé une nouvelle approche appelée 2D-SIFT-in-3D-Space utilisant les SIFT (scale Invariant Feature Transform) pour atteindre un recalage robuste en trois dimensions de deux images. Notre méthode recale les images en corrigeant séparément les translations et rotations sur les trois axes grâce à l’extraction et l’association de caractéristiques stables de leurs coupes transversales bidimensionnelles. Pour évaluer la qualité du recalage, nous avons également développé un simulateur d’images de laser-scanning microscopie qui génère une paire d’images 3D virtuelle dans laquelle le niveau de bruit et les angles de rotations entre les angles de rotation sont contrôlés avec des paramètres connus. Pour une concaténation précise et naturelle de deux images, nous avons également développé un module permettant une compensation progressive de la luminosité et du contraste en fonction de la distance à la surface de l’échantillon. Ces outils ont été utilisés avec succès pour l’obtention d’images tridimensionnelles de haute résolution du cerveau de la mouche Drosophila melanogaster, particulièrement des neurones dopaminergiques, octopaminergiques et de leurs synapses. Ces neurones monoamines sont particulièrement important pour le fonctionnement du cerveau et une étude de leur réseau et connectivité est nécessaire pour comprendre leurs interactions. Si une évolution de leur connectivité au cours du temps n’a pas pu être démontrée via l’analyse de la répartition des sites synaptiques, l’étude suggère cependant que l’inactivation de l’un de ces types de neurones entraine des changements drastiques dans le réseau neuronal. / Although laser scanning microscopy is a powerful tool for obtaining thin optical sections, the possible depth of imaging is limited by the working distance of the microscope objective but also by the image degradation caused by the attenuation of both excitation laser beam and the light emitted from the fluorescence-labeled objects. Several workaround techniques have been employed to overcome this problem, such as recording the images from both sides of the sample, or by progressively cutting off the sample surface. The different views must then be combined in a unique volume. However, a straightforward concatenation is often not possible, because the small rotations that occur during the acquisition procedure, not only in translation along x, y and z axes but also in rotation around those axis, making the fusion uneasy. To address this problem we implemented a new algorithm called 2D-SIFT-in-3D-Space using SIFT (scale Invariant Feature Transform) to achieve a robust registration of big image stacks. Our method register the images fixing separately rotations and translations around the three axes using the extraction and matching of stable features in 2D cross-sections. In order to evaluate the registration quality, we created a simulator that generates artificial images that mimic laser scanning image stacks to make a mock pair of image stacks one of which is made from the same stack with the other but is rotated arbitrarily with known angles and filtered with a known noise. For a precise and natural-looking concatenation of the two images, we also developed a module progressively correcting the sample brightness and contrast depending on the sample surface. Those tools we successfully used to generate tridimensional high resolution images of the fly Drosophila melanogaster brain, in particular, its octopaminergic and dopaminergic neurons and their synapses. Those monoamine neurons appear to be determinant in the correct operating of the central nervous system and a precise and systematic analysis of their evolution and interaction is necessary to understand its mechanisms. If an evolution over time could not be highlighted through the pre-synaptic sites analysis, our study suggests however that the inactivation of one of these neuron types triggers drastic changes in the neural network.

No description available.

This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.

New advances in computational modeling and instrumentation in the past decade has enabled the use of electromagnetic radiation for non-invasive monitoring of the physio-logical state of biological tissues. The near infrared (NIR) light having the wavelength range of 600 nm -1000 nm has been the main contender in these emerging molecular imaging modalities. Assessment of accurate pathological condition of the tissue under investigation relies on the contrast in the molecular images, where the endogenous contrast may not be sufficient in these scenarios. The fluorescence (exogenous) contrast agents have been deployed to overcome these difficulties, where the preferential uptake by the tumor vasculature leads to high contrast,making this modality one of the biggest contenders in small-animal and soft-tissue molecular imaging modalities. In Fluorescence diffuse optical spectroscopy/imaging, this exogenous drug is excited by NIR laser light causing the emission of the fluorescence light. The emitted fluorescence light is typically dependent on the life time and concentration of the exogenous drug coupled with physiology associated with the tissue under investigation. As there is an excitation and emission of the light,the underlying physics of the problem is described by a coupled diffusion equations. These coupled diffusion equations are typically solved by advanced numerical methods, which tend to be computationally demanding. In this work, analytical solutions for these coupled partial differential equations (PDEs) for the regular geometries for both time-domain and frequency-domain cases were developed. Till now, the existing literature has not dealt with all regular geometries and derived analytical solutions were only for couple of geometries. Here a universally acceptable generic solution was developed based on Green’s function approach that is applicable to any regular geometry. Using this, the analytical solutions for the regular geometries that is encountered in diffuse fluorescence spectroscopy/imaging were obtained. These solutions can play an important role in determining the bulk fluorescence properties of the tissue, which could act as good initial guesses for the advanced image reconstruction techniques and/or can also facilitate the calibration of experimental fluorescence data by removing biases and source-detector variations. In the second part of this work, the developed analytical models for regular geometries were validated through comparison with the established numerical models that are traditionally used in the diffuse fluorescence spectroscopy/imaging. This comparison not only validated the developed analytical models, but also showed that analytical models are capable of providing bulk fluorescence properties with at least one order of magnitude less computational cost compared to the highly optimized traditional numerical models.

Epileptic syndromes with continuous spikes and waves during slow sleep (CSWS) are age-related epileptic encephalopathy characterized by the development of various psychomotor regressions in close temporal concordance with the appearance of the electroencephalogram (EEG) pattern of CSWS (Tassinari et al. 2000). This EEG pattern consists in sleep-related activation and diffusion of spike-wave discharges during usually more than 85% of non-rapid eye movement (non-REM) sleep (Tassinari et al. 2000). <p>A minority of the CSWS cases has been associated to cortical or thalamic lesions (symptomatic cases), while in the other cases, the aetiology is unknown. We reported two families combining benign childhood epilepsy with centro-temporal spikes (BCECS), which is the most common form of idiopathic epilepsy in childhood, and cryptogenic epilepsy with CSWS in first-degree relatives. As idiopathic epilepsies are by definition epilepsies related to a genetic predisposition, these data suggests the existence of a continuum ranging from asymptomatic carriers of centro-temporal spikes to cryptogenic epilepsies with CSWS. This hypothesis is further supported by common clinical characteristics between BCECS and epilepsies with CSWS (Fejerman et al. 2000).<p>Epileptic syndromes with CSWS are characterized by an acute phase defined by the emergence of psychomotor deficits, various types of seizures and CSWS activity at around three to eight years of age (Holmes and Lenck-Santini, 2006; Veggiotti et al. 2001). This acute phase is followed by a recovery phase in which patients’ clinical condition improves together with the remission of CSWS pattern, which spontaneously occur at around 15 years of age but may be prompted by using antiepileptic drugs (AED) including corticosteroids (Holmes and Lenck-Santini, 2006; Veggiotti et al. 2001). This biphasic evolution suggests that CSWS activity largely contributes to the psychomotor deficits observed in these patients (Holmes and Lenck-Santini, 2006; Van Bogaert et al. 2006). However, some authors still consider CSWS activity as an epiphenomenon reflecting the underlying brain pathology, rather than the direct cause of the psychomotor regression (Aldenkamp and Arends, 2004). The pathophysiological mechanisms of how CSWS activity could actually lead to psychomotor regression are still poorly understood.<p>Functional cerebral imaging techniques such as positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), represent unique ways to non-invasively study the impact of epileptic activity on normal brain function. The PET technique using [18F]-fluorodeoxyglucose (FDG) gives information about the regional neuronal glucose consumption via the neurometabolic coupling while the fMRI technique studies the regional perfusional changes directly related to specific events of interest via the neurovascular coupling. We applied both FDG-PET and EEG combined with fMRI (EEG-fMRI) techniques to epileptic children with CSWS to better approach the functional repercussions of CSWS activity on neurophysiological functions and to determine the potential pathophysiological link between CSWS activity and psychomotor regression.<p>In a first FDG-PET study, we determined the regional cerebral glucose metabolic patterns at the acute phase of CSWS in 18 children. We found three types of metabolic patterns: the association of focal hypermetabolism with distinct hypometabolism in 10 patients, focal hypometabolism without any associated area of increased metabolism in five children, and the absence of any significant metabolic abnormality in three patients. The hypermetabolic brain areas were anatomically related to an EEG focus. This anatomical relationship was clearly less consistent for hypometabolic regions. The metabolic abnormalities involved mainly the associative cortices. The metabolic heterogeneity found in these children could be due to the use of corticosteroids before PET as it was significantly associated with the absence of focal hypermetabolism. At the group level, patients with at least one hypermetabolic brain areas showed significant increased metabolism in the right parietal region that was associated to significant hypometabolism in the prefrontal cortex. This finding was interpreted as a phenomenon of remote inhibition of the frontal lobes by highly epileptogenic and hypermetabolic posterior cortex. This hypothesis was supported by effective connectivity analyses which demonstrated the existence of significant changes in the metabolic relationship between these brain areas in this group of children compared to the control group or to the group of children without any significant hypermetabolic brain area. <p>This remote inhibition hypothesis would be reinforced by the demonstration, at the recovery phase of CSWS, of a common resolution of hypermetabolism at the site of epileptic foci and hypometabolism in distant connected brain areas. We thus performed a second FDG-PET study to determine the evolution of cerebral metabolism in nine children recovering from CSWS. At the acute phase of CSWS, all children had a metabolic pattern characterized by the association of focal hypermetabolism with distinct focal hypometabolic areas. The evolution to CSWS recovery was characterized by a complete or almost complete regression of both hypermetabolic and hypometabolic abnormalities. At the group level, the altered effective connectivity found at the acute phase between focal hypermetabolism (centro-parietal regions and right fusiform gyrus) and widespread hypometabolism (prefrontal and orbito-frontal cortices, temporal lobes, left parietal cortex, precuneus and cerebellum) markedly regressed at recovery. These results were of particular interest because they strongly suggested that the metabolic abnormalities observed during the acute phase of CSWS were mainly related to the neurophysiological effects of CSWS activity and not to the underlying cause of the epileptic disease. Moreover, this study confirmed that phenomena of remote inhibition do occur in epileptic syndromes with CSWS. <p>EEG-fMRI is a functional cerebral imaging technique that allows non-invasive mapping of haemodynamic changes directly associated to epileptic activity. In a first EEG-fMRI study, we determined the clinical relevance of the perfusional changes linked to interictal epileptic discharges in a group of seven children with pharmacoresistant focal epilepsy. This study showed that the EEG-fMRI technique is a promising tool to non-invasively localize the epileptic focus and its repercussion on normal brain function in children with epilepsy. Then, to further demonstrate the involvement of CSWS activity in the neurophysiological changes detected by FDG-PET, we used the EEG-fMRI technique to study the perfusional changes directly related to the epileptic activity in an epileptic girl with CSWS. This patient developed a cognitive and behavioural regression in association with a major increase in frequency and diffusion of the spike-wave discharges during the awake state (spike index: 50-75%) and non-REM sleep (spike index: 85-90%). The patient’s neuropsychological profile was dominated by executive dysfunction and memory impairment. During runs of secondarily generalized spike-wave discharges, EEG-fMRI demonstrated deactivations in the lateral and medial fronto-parietal cortices, posterior cingulate gyrus and cerebellum together with focal relative activations in the right frontal, parietal and temporal cortices. These results suggested that the neuropsychological impairment in this case could be related to specific cortical dysfunction secondary to the spread of the epileptic activity from focal hypermetabolic foci. <p>Taken together, both FDG-PET and EEG-fMRI investigations performed in epileptic children with CSWS have shown increases in metabolism/perfusion at the site of the epileptic focus that were associated to decreases in metabolism/perfusion in distinct connected brain areas. These data highly suggest that the neurophysiological effects of CSWS activity are not restricted to the epileptic focus but spread to connected brain areas via a possible mechanism of surrounding and/or remote inhibition. This mechanism is characterised by an epilepsy-induced inhibition of neurons that surround or are remote from the epileptic focus and connected with it via cortico-cortical or polysynaptic pathways (Witte and Bruehl, 1999). The existence of surrounding and remote inhibition phenomena have been well documented in different types of animal models of focal epilepsy using various functional cerebral imaging methods such as autoradiography or optical imaging (Bruehl et al. 1998; Bruehl and Witte, 1995; Witte et al. 1994). Their occurrence in human epilepsy have also been suspected in temporal or extra-temporal lobe epilepsies using FDG-PET, EEG-fMRI or single photon emission computed tomography (SPECT) (Blumenfeld et al. 2004; Schwartz and Bonhoeffer, 2001; Van Paesschen et al. 2003; Van Paesschen et al. 2007). Moreover, the demonstration of the regression of distant hypometabolic areas after surgical resection or disconnection of the epileptic focus further suggest that such inhibition mechanism do occur in epilepsy (Bruehl et al. 1998; Jokeit et al. 1997). On a clinical point of view, the demonstration of the existence of such inhibition mechanisms in epilepsies with CSWS brings new important insights for the understanding of the pathophysiological mechanisms involved in the psychomotor regression observed in these conditions. Indeed, these data highly suggest that the psychomotor regression is not only related to the neurophysiological impairment at the site of the epileptic foci but also to epilepsy-induced neurophysiological changes in distant connected brain areas. <p><p> / Doctorat en Sciences médicales / info:eu-repo/semantics/nonPublished

L’accident vasculaire cérébrale (AVC) ischémique est une des premières causes de mortalité dans le monde, par conséquent il constitue un véritable enjeu de santé publique. Cette pathologie résulte de l’obstruction d’une artère cérébrale par un caillot et déclenche une inflammation, pouvant majorer les lésions tissulaires du cerveau. À ce jour les traitements anti-inflammatoires appliqués en clinique se sont révélés inefficaces. Il est donc indispensable de développer de nouvelles approches diagnostiques pour une meilleure compréhension des mécanismes biologiques impliqués dans cette pathologie. Dans ce contexte, nous avons proposé la conception d’une nanoplateforme hybride multimodale comme agent de contraste adapté à trois techniques d’imagerie médicale. Ces nanoparticules au cœur inorganique, composé de GdF3 augmentent sensiblement le contraste en IRM et leur opacité procure un rehaussement de contraste pour le Scanner Spectral à Comptage Photonique (SPCCT), une technique de développement récent. La troisième modalité, la microscopie biphotonique procure une haute résolution et une très grande sensibilité, tout en permettant d’obtenir des images en temps réel. Grâce à un chromophore adapté, greffé à la surface de la particule, cette modalité devient également accessible. Ces particules inorganiques sont synthétisées par une méthode solvothermale originale, développée par notre équipe. La surface des nanoparticules est ensuite modifiée par différents ligands polyéthylène glycol (PEG) fonctionnalisés, qui rendent les particules de GdF3 stables en milieu physiologique (comme le sang), biocompatibles et furtives. Enfin, un chromophore spécialement développé au sein de notre laboratoire, pour des applications d’absorption biphotonique, a été greffé à la surface de la particule. Le couplage du chromophore a été effectué via une réaction click azoture-alcyne, activée thermiquement (sans catalyse par Cu(I)). La toxicité des particules a été évaluée par deux techniques différentes, appliquées sur des cellules d’origine humaine. À l’issue de ces tests aucun effet cytotoxique n’a été observé. Après avoir démontré les propriétés multimodales de ces nanoobjets, des expériences précliniques in vivo ont été menées. Nous avons montré, que lors de l’observation du cerveau de souris la nanosonde augmente efficacement le contraste en SPCCT, IRM et produit un signal intense en microscopie 2-photons intravitale. Les particules se sont révélées particulièrement stables dans le sang : grâce à leur furtivité elles restent dans la circulation longtemps, ce qui favorise leur passage à travers la barrière hémato-enchéphalique lésée. Elles sont également phagocytées par les cellules immunitaires activées. La dynamique spatio-temporelle de ces cellules marquées par les nanoparticules a pu être imagée / Ischemic stroke, as one of the most common causes of death, represents an important health issue. The pathology consists of the occlusion of an artery in the brain leading to an acute inflammatory process. Post-stroke inflammation usually results in irreversible secondary brain tissue damage. To date, the clinical application of anti-inflammatory treatments has been either negative or inconclusive. For a better understanding of this complex physiological process and development of efficient treatment, there is an urgent need to develop performant in-vivo diagnostic tools. In that context, we proposed to design a multimodal hybrid nanoprobe for enhancing the contrast in three different clinical and pre-clinical imaging modalities. The ability of this probe to enhance contrast in MRI (Magnetic Resonance Imaging) and a recently developed spectral photon counting scanner computed tomography (SPCCT) is intrinsic to the inorganic GdF3 core. The inorganic nanoparticle size and morphology was optimized for the biological application. The third modality, two-photon imaging, provides high spatial resolution, high sensitivity, and allows real-time imaging. To make GdF3 nanoparticles visible by two-photon microscopy, a specially designed organic moiety is added to the nanoplatform. The inorganic nanoparticles are synthesized by the original solvothermal method developed in our group. Surface modifications with different PEG derivatives confer to the GdF3 nanoparticles high stability in physiological media (such as blood), biocompatibility, and stealth. The two-photon active chromophore synthesized in our laboratory is grafted to the particle surface via a thermally activated (catalyst-free) alkyne-azide click reaction. Toxicity of the nanoobjects has been assessed by using two different tests on four human-derived cells, and no cytotoxic effect of the particles was found. After the demonstration of the multimodality of the particles, pre-clinical in vivo experiments were performed. We evidenced that the particles successfully enhance SPCCT, MRI contrast in the brain of the small animal via a T2-effect and provide a high-intensity two-photon signal for in-vivo microscopy. Besides, the nanoparticles revealed to be stable and long-circulating in the blood, which favored their cross through the altered blood-brain barrier. Their phagocytose by activated immune cells offered the possibility to follow cell-trafficking

Die Autoimmunenzephalitis ist eine kürzlich beschriebene entzündliche Erkrankung des zentralen Nervensystems, die Gedächtnisdefizite, Psychosen, oder epileptische Anfälle hervorrufen kann. Derzeit ist hingegen noch nicht ausreichend verstanden, welche pathologischen Veränderungen zu den kognitiven Defiziten führen 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 Gedächtnisdefizite mit fokalen strukturellen Läsionen im Hippocampus einher. Durch eine funktionelle Störung der Resting-State-Konnektivität des Default-Mode- und Salienznetzwerkes beeinträchtigen diese Hippocampusläsionen 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 Gedächtnisses und exekutiver Funktionen. Zuletzt zeigt eine transdiagnostische Analyse, dass der anteriore Hippocampus eine erhöhte Vulnerabilität gegenüber immunvermittelten pathologischen Prozessen aufweist. Diese Ergebnisse legen nahe, dass kognitive Symptome auch noch nach der Entlassung aus der stationären Behandlung fortbestehen können. Sowohl umschriebene strukturelle Hippocampusläsionen als auch Veränderungen in makroskopischen funktionellen Hirnnetzwerken tragen zur pathophysiologischen Erklärung dieser Symptome bei. Zudem erlauben diese Ergebnisse einen Einblick in neuroplastische Veränderungen des Gehirns und haben weitreichende Implikationen für die Langzeitversorgung und das Design zukünftiger 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.