Magnetic resonance imaging is an essential tool for assessing soft tissues. The desire for increased signal-to-noise and improved tissue contrast has spurred development of imaging systems operating at magnetic fields exceeding 3.0 Tesla (T). Unfortunately, traditional imaging methods are of limited utility on these systems. Novel imaging methods are required to exploit the potential of high field systems and enable innovative clinical studies. This thesis presents methodological advances for human brain imaging at 4.7 T. These methods are applied to assess sub-cortical gray matter in multiple sclerosis (MS) patients. Safety concerns regarding energy deposition in the patient precludes the use of traditional fast spin echo (FSE) imaging at 4.7 T. Reduced and variable refocusing angles were employed to effectively moderate this energy deposition while maintaining high signal levels; an assortment of time-efficient FSE images are presented. Contrast changes were observed at low angles, but images maintained a clinically useful appearance. Heterogeneous transmit fields hinder the measurement of transverse relaxation times. A post-processing technique was developed to model the salient signal behaviour and enable accurate transverse relaxometry. This method is robust to transmit variations observed at 4.7 T and improves multislice imaging efficiency. Gradient echo sequences can exploit the magnetic susceptibility difference between tissues to enhance contrast, but are corrupted near air/tissue interfaces. A correction method was developed and employed to reliably produce a multitude of quantitative and qualitative image sets. Using these techniques, transverse relaxation times and susceptibility field shifts were measured in sub-cortical nuclei of relapsing-remitting MS patients. Abnormalities in the globus pallidus and pulvinar nucleus were observed in all quantitative methods; most other regions differed on one or more measures. Correlations with disease duration were not observed, reaffirming that the disease process commences prior to symptom onset. The methods presented in this thesis enable efficient qualitative and quantitative imaging at high field strength. Unique challenges, notably patient safety and field variability, were overcome via sequence implementation and data processing. These techniques enable visualization and measurement of unique contrast mechanisms, which reveal insight into neurodegenerative diseases, including widespread sub-cortical gray matter damage in MS.

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Diese kumulative Dissertation umfasst zwei Studien zu den räumlichen und zeitlichen neuronalen Dynamiken des visuellen Arbeitsgedächtnisses (VA). Die erste Studie untersuchte, wie die oberflächlichen und tiefen Schichten des präfrontalen Kortex (PFC) zur Enkodierung, Aufrechterhaltung und zum Abruf von VA-Informationen bei unterschiedlichen Gedächtnisbelastungen beitragen. Die Ergebnisse zeigten, dass die oberflächlichen PFC-Schichten bei hoher Belastung während der Verzögerung und des Abrufs stärker aktiviert waren. Multivariate Decodierungstechniken zeigten eine dynamische neuronale Kodierung mit drei Clustern generalisierter Aktivitätsmuster in den Phasen der Enkodierung, Verzögerung und des Abrufs. Es gab jedoch keine Generalisierung zwischen diesen Phasen, was auf unterschiedliche neuronale Populationen für jede Phase hinweist. Die zweite Studie untersuchte die Mechanismen, die VA bei Ablenkungen aufrechterhalten. Dabei wurden Daten aus einer früheren Studie erneut analysiert, in der die Teilnehmer drei Arten von Aufgaben ausführten: eine mit einer leeren Verzögerungsphase, eine mit einem Orientierungsablenker und eine mit einem Rauschablenker. Die Studie analysierte die zeitliche Generalisierung der neuronalen Codes in Regionen des visuellen Kortex und prüfte, ob VA und Ablenker dieselben neuronalen Subräume nutzen. Die Ergebnisse zeigten eine dynamische Kodierung während der frühen und späten Verzögerungsphasen. Zudem wurden VA und der Orientierungsablenker in getrennten, nicht überlappenden Subräumen aufrechterhalten, was auf unterschiedliche neuronale Populationen für VA und Ablenker hindeutet. Zusammenfassend erweitert die Dissertation das Verständnis darüber, wie der PFC und visuelle Areale VA-Informationen aufrechterhalten, insbesondere unter unterschiedlichen Belastungen und Ablenkungen. Sie liefert zudem neue Ansätze zur Untersuchung der zeitlichen neuronalen Dynamik dieser Prozesse. / This cumulative thesis covers two scientific studies exploring the spatial and temporal neural dynamics of visual working memory (VWM) processes. The first study examined the contributions of the prefrontal cortex (PFC) layers—superficial and deep—during VWM encoding, maintenance, and retrieval under two memory load conditions. Results revealed heightened activation in the superficial layers of the PFC during high-load trials, particularly in the maintenance and retrieval phases. Using multivariate decoding techniques, the study assessed the temporal stability of neural codes distinguishing high- and low-load trials, identifying a dynamic code with three distinct clusters of generalization during encoding, delay, and retrieval phases. Notably, there was no generalization of neural patterns across these phases, suggesting distinct neural populations for each stage. The second study focused on the mechanisms enabling VWM maintenance in the presence of distractions. Reanalyzing prior data, the study examined VWM trials featuring either a blank delay, an orientation distractor, or a noise distractor. The study explored the temporal generalization of neural codes across visual cortex regions and whether VWM and distractors shared neural subspaces. Findings indicated dynamic neural coding during early and late memory delay periods. Additionally, VWM and orientation distractors were maintained in separate, non-overlapping subspaces, suggesting distinct neural populations for VWM and perceptual distractors. Collectively, this thesis enhances our understanding of how the PFC and visual areas support VWM maintenance and control, particularly under varying loads and distractions. It also introduces novel approaches for investigating the temporal neural dynamics underlying these processes.