A proton nuclear magnetic resonance spectrum of the brain in vivo contains peaks from every proton-containing molecule in the brain. Sensitivity limitations mean that only those molecules present at concentrations of at least a few millimolar are detectable in a reasonable period of time; this still leaves many important molecules such as amino acids and other small metabolites. Most of their resonance frequencies fall in the region between 1.0 and 4.5 p.p.m. A typical linewidth in vivo is about 0.05 p.p.m., so the number of distinct peaks observable is restricted. The use of two-dimensional NMR techniques such as COSY can spread peaks out into a second dimension enabling otherwise overlapping peaks to be resolved. This thesis describes the development, testing and application of two such 2D NMR pulse sequences, dubbed ISIS-COSY and ISIS-JRES. They are based on an existing magnetisation localisation sequence and excite detected magnetisation in a manner analogous to the high-resolution sequences COSY and 2D J-resolved spectroscopy. A method for quantifying the metabolites visible in an ISIS-COSY spectrum from their cross-peak intensities is described, and results presented from both control rat brains and those of animals treated with vigabatrin, an inhibitor of GABA-transaminase that has the effect of increasing brain γ-amino butyric acid (GABA) levels. Further applications mentioned are in the study of neutrophil-infiltrated rat brain and adaptation of the ISIS-COSY technique for human use.

For children with intractable seizures, surgical removal of epileptic foci, if identifiable and feasible, can be an effective way to reduce or eliminate seizures. The success of this type of surgery strongly hinges upon the ability to identify and demarcate those epileptic foci. The ultimate goal of this research project is to develop an effective technology for detection of unique in vivo pathophysiological characteristics of epileptic cortex and, subsequently, to use this technology to guide epilepsy surgery intraoperatively. In this PhD dissertation the feasibility of using optical spectroscopy to identify unique in vivo pathophysiological characteristics of epileptic cortex was evaluated and proven using the data collected from children undergoing epilepsy surgery. In this first in vivo human study, static diffuse reflectance and fluorescence spectra were measured from the epileptic cortex, defined by intraoperative ECoG, and its surrounding tissue from pediatric patients undergoing epilepsy surgery. When feasible, biopsy samples were taken from the investigated sites for the subsequent histological analysis. Using the histological data as the gold standard, spectral data was analyzed with statistical tools. The results of the analysis show that static diffuse reflectance spectroscopy and its combination with static fluorescence spectroscopy can be used to effectively differentiate between epileptic cortex with histopathological abnormalities and normal cortex in vivo with a high degree of accuracy. To maximize the efficiency of optical spectroscopy in detecting and localizing epileptic cortex intraoperatively, the static system was upgraded to investigate histopathological abnormalities deep within the epileptic cortex, as well as to detect unique temporal pathophysiological characteristics of epileptic cortex. Detection of deep abnormalities within the epileptic cortex prompted a redesign of the fiberoptic probe. A mechanical probe holder was also designed and constructed to maintain the probe contact pressure and contact point during the time dependent measurements. The dynamic diffuse reflectance spectroscopy system was used to characterize in vivo pediatric epileptic cortex. The results of the study show that some unique wavelength dependent temporal characteristics (e.g., multiple horizontal bands in the correlation coefficient map g(λref = 800 nm, λcomp,t)) can be found in the time dependent recordings of diffuse reflectance spectra from epileptic cortex defined by ECoG.

<p>Intricate neural circuits underlie all brain functions. However, these neural circuits are highly dynamic. The ability to change, or the plasticity, of the brain has long been demonstrated at the level of isolated single synapses under artificial conditions. Circuit organization and brain function has been extensively studied by correlating neuronal activity with information input. The primary visual cortex has become an important model brain region for the study of sensory processing, in large part due to the ease of manipulating visual stimuli. Much has been learned from studies of visual cortex focused on understanding the signal-processing of visual inputs within neural circuits. Many of these findings are generalizable to other sensory systems and other regions of cortex. However, few studies have directly demonstrated the orchestrated neural-circuit plasticity occurring during behavioral experience. </p> <p>It is vital to measure the precise circuit connectivity and to quantitatively characterize experience-dependent circuit plasticity to understand the processes of learning and memory formation. Moreover, it is important to study how circuit connectivity and plasticity in neurological and psychiatric disease states deviates from that in healthy brains. By understanding the impact of disease on circuit plasticity, it may be possible to develop therapeutic interventions to alleviate significant neurological and psychiatric morbidity. In the case of neural trauma or ischemic injury, where neurons and their connections are lost, functional recovery relies on neural-circuit repair. Evaluating whether neurons are reconnected into the local circuitry to re-establish the lost connectivity is crucial for guiding therapeutic development.</p> <p>There are several major technical hurdles for studies aiming to quantify circuit connectivity. First, the lack of high-specificity circuit stimulation methods and second, the low throughput of the gold-standard patch-clamp technique for measuring synaptic events have limited progress in this area. To address these problems, we first engineered the patch-clamp experimental system to automate the patching process, increasing the throughput and consistency of patch-clamp electrophysiology while retaining compatibility of the system for experiments in <i>ex vivo </i>brain slices. We also took advantage of optogenetics, the technology that enables control of neural activity with light through ectopic expression of genetically encoded photo-sensitive channels in targeted neuronal populations. Combining optogenetic stimulation of pre-synaptic axonal terminals and whole-cell patch-clamp recording of post-synaptic currents, we mapped the distribution and strength of synaptic connections from a specific group of neurons onto a single cell. With the improved patch-clamp efficiency using our automated system, we efficiently mapped a significant number of neurons in different experimental conditions/treatments. This approach yielded large datasets, with sufficient power to make meaningful comparisons between groups.</p> <p>Using this method, we first studied visual experience-dependent circuit plasticity in the primary visual cortex. We measured the connectivity of local feedback and recurrent neural projections in a Fragile X syndrome mouse model and their healthy counterparts, with or without a specific visual experience. We found that repeated visual experience led to increased excitatory drive onto inhibitory interneurons and intrinsically bursting neurons in healthy animals. Potentiation at these synapses was absent or abnormal in Fragile X animals. Furthermore, recurrent excitatory input onto regular spiking neurons within the same layer remained stable in healthy animals but was depressed in Fragile X animals following repeated visual experience. These results support the hypothesis that visual experience leads to selective circuit plasticity which may underlie the mechanism of visual learning. This circuit plasticity process is impaired in a mouse model of Fragile X syndrome. </p> <p>In a separate study, in collaboration with the laboratory of Dr. Gong Chen, we applied the circuit-mapping method to measure the effect of a novel brain-repair therapy on functional circuit recovery following ischemic injury, which locally kills neurons and creates a glial scar. By directly reprogramming astrocytes into neurons within the region of the glial scar, this gene-therapy technology aims to restore the local circuit and thereby dramatically improve behavioral function after devastating neurological injury. We found that direct reprogramming converted astrocytes into neurons, and importantly, we found that these newly reprogrammed neurons integrated appropriately into the local circuit. The reprogramming also improved connections between surviving endogenous neurons at the injury site toward normal healthy levels of connectivity. Connections formed onto the newly reprogrammed neurons spontaneously remodeled, the process of which resembled neural development. By directly demonstrating functional connectivity of newly reprogrammed neurons, our results suggest that this direct reprogramming gene-therapy technology holds significant promise for future clinical application to restore circuit connectivity and neurological function following brain injury.</p>

Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue information. In quantitative MRI, different physical quantities are estimated from a set of collected images. The optimization problems solved are typically nonlinear, and require intelligent and application-specific algorithms to avoid suboptimal local minima. This thesis presents several methods for efficiently solving different parameter estimation problems in MRI, such as multi-component T2 relaxometry, temporal phase correction of complex-valued data, and minimizing banding artifacts due to field inhomogeneity. The performance of the proposed algorithms is evaluated using both simulation and in-vivo data. The results show improvements over previous approaches, while maintaining a relatively low computational complexity. Using new and improved estimation methods enables better tissue characterization and diagnosis. Furthermore, a sequence design problem is treated, where the radio-frequency excitation is optimized to minimize image artifacts when using amplifiers of limited quality. In turn, obtaining higher fidelity images enables improved diagnosis, and can increase the estimation accuracy in quantitative MRI.

Le cerveau est un organe complexe composé de neurones et des cellules non-neuronales. La communication entre les neurones a lieu via les synapses, dont le remodelage morphologique est considéré essentiel pour le traitement et le stockage des informations dans le cerveau des mammifères. Récemment, ce point de vue neuro-centré de la fonction synaptique a évolué, en prenant également en compte les processus gliaux à proximité immédiate de la synapse. Cependant, comme leur structure est bien en deçà de la résolution spatiale de la microscopie optique conventionnelle, les progrès dans les enquêtes dans leur environnement physiologique, le cerveau intact, ont été entravés. En effet, on sait peu sur les variations nanométriques de la morphologie des épines dendritiques et l'interaction avec les processus gliaux, et, finalement, comment elles affectent la transmission synaptique in vivo. Dans cette thèse, nous cherchons à visualiser la dynamique de la nano-morphologie des épines dendritiques et les processus gliaux dans le cortex à tonneaux de souris in vivo. Nous avons donc mis en place l’imagerie super-résolution 2P-STED en temps réel, ce qui permet une haute résolution spatiale et la pénétration profonde des tissus, chez la souris anesthésiée in vivo. Nous montrons que la nano-morphologie des épines est diversifiée, variable, mais globalement stable, et que les différences dans la morphologie des épines peut avoir un effet sur leur compartimentation in vivo. En outre, la mise en œuvre de l’imagerie super-résolution en double couleur in vivo et le développement d'une approche de marquage astrocytaire, nous ont permis de fournir la caractérisation à l'échelle nanométrique des interactions neurone-glie. Ces résultats apportent un aperçu sans précédent dans la dynamique de la synapse à l'échelle nanométrique in vivo, et ouvrent la voie à une meilleure compréhension de la façon dont les réarrangements morphologiques des synapses contribuent à la physiologie du cerveau. / The brain is a complex organ consisting of neurons and non-neuronal cells. Communication between neurons takes place via synapses, whose morphological remodeling is thought to be crucial for information processing and storage in the mammalian brain. Recently, this neuro-centric view of synaptic function has evolved, also taking into account the glial processes in close vicinity of the synapse. However, as their structure is well below the spatial resolution of conventional light microscopy, progress in investigating them in a physiological environment, the intact brain, has been impeded. Indeed, little is known on the nanoscale morphological variations of dendritic spines, the interaction with glial processes, and how these affect synaptic transmission in vivo. Here, we aim to visualize the dynamic nano-morphology of dendritic spines in mouse somatosensory cortex in vivo. We implemented super-resolution 2P-STED time-lapse imaging, which allows for high spatial resolution and deep tissue penetration, in anesthetized mice, and show that the nano-morphology of spines is diverse, variable, but on average stable, and that differences in spine morphology can have an effect on spine biochemical compartmentalization in vivo. Moreover, implementation of dual color in vivo super-resolution imaging and a novel astrocytic labeling approach provided the first steps towards nanoscale characterization of neuron-glia interactions in vivo. These findings bring new insights in synapse dynamics at the nanoscale in vivo, and our methodological endeavors help pave the way for a better understanding of how nanoscale aspects of spine morphology and their dynamics might contribute to brain physiology and animal behavior.