Work focusing on the combination of EMG and fMRI in skeletal muscle. / Two commonly used diagnostic techniques for examining muscle function in vivo are functional magnetic resonance imaging (fMRI) and electromyography (EMG). EMG allows for examination of the functional, electrical activity of muscle during force production. Comparatively, fMRI or more specifically blood oxygen level dependant imaging can be applied to visualize muscle activation and recovery post-exercise. It is a combination of oxygenation, metabolism, blood flow and blood volume. The proposed method combines both techniques in simultaneous data acquisition to provide greater muscle physiological information during exercise. Additionally, both techniques are non-invasive making repeated measurements feasible. EMG hardware filtering was designed and constructed to facilitate EMG measurements alongside MRI scans during simultaneous acquisition. Next, a complex artifact subtraction method called fMRI artifact slice template removal (FASTR) was implemented. With custom scripts and small adaptations to FASTR, it was modified for use with EMG/fMRI, specifically, with a echo planar imaging (EPI) BOLD sequence. Several experiments were then performed to test it's capabilities improving the signal-to-noise ratio (SNR) of the EMG data from 2.8 to 46 in one case. After EMG hardware and software were developed and implemented, a simple exercise protocol was developed to investigate changes in concurrent BOLD/EMG, recording before, during and following exercise. A linear correlation analyses was performed to compare EMG and BOLD results. A strong correlation between the EMG root-mean-square (RMS) peak amplitude and the length of time to recover back to baseline was noted (r=0.681, n=3). For future studies, multiple EMG measurements should be applied to improve the amount of information collected during voluntary exercise. Lastly, this technique may have usage with not just BOLD MRI scans, but with various other techniques such as near infrared spectroscopy (NIRS), and diffusion tensor imaging (DTI) in order to further probe muscle physiology. / Thesis / Master of Applied Science (MASc) / Two commonly used methods for detecting disease and injury in muscle are magnetic resonance imaging (MRI), and electromyography (EMG). EMG provides information about the electrical activity of muscle during exercise, while MRI scans give two or three dimensional images of the body. Using these two techniques at the same time, provides the opportunity to obtain greater physiological information of muscle during and after exercise. The goal of this work was to design and create an EMG system that functioned alongside MRI scans. However, combining these two techniques presented several challenges that needed to be solved before this was possible. These issues were resolved and diminished by utilizing specific hardware and software solutions alongside rigorous testing. Additionally, results from the combination of these two techniques have demonstrated there is great potential for future studies. In conclusion, using EMG and MRI together is feasible, and allows for further investigation into muscle physiology.

The liver is a multi-function organ that plays important roles in nutrient metabolism, biochemical transformations and blood detoxification. The purpose of the current work was to optimize Blood Oxygen Level Dependent (BOLD) liver functional MR imaging and analysis to allow the distinction between healthy volunteers and subjects with chronic liver disorders known to lead to fibrosis and reduced liver function (in this case, Hepatitis-C). Liver BOLD signal can be modulated by breathing 100% 0 2 or through intake of a meal. Previous results using these stimuli have been inconclusive when comparing healthy and diseased livers. In addition, liver BOLD analysis has been traditionally carried out using general linear models (GLM). Since the liver has a dual blood supply (portal and arterial derived), its resultant haemodynamic response is complex. This makes it too difficult to employ GLM approaches, as they require the prediction and modeling of a response function. We chose a model-free, or data-driven approach, called principle component analysis (PCA) to analyze liver data. Initial optimization was done by determining the time of maximal hepatic portal vein (HPV) blood flow following ingestion of a controlled meal (235 mL of Ensure Plus®). Statistically significant increases in HPV flow resulted at all measurement intervals, with the maximal postprandial change (71% increase in comparison to the baseline flow) at thirty minutes after ingestion. Implementing acquisition and analysis optimizations with our dual liver challenge model (hyperoxia cycling in pre- and postprandial states), the PCA approach was able to detect all of the diseased livers (n=6), while missing four of the healthy subjects (n=ll). The GLM technique, on the other hand, did not detect two of the patients and two of the healthy subjects. Thus, if this liver challenge is to be used as a screening tool, a model-free data analysis approach is suggested as more appropriate since it minimizes the chances of reporting false-negative results (based on this preliminary cohort). Although more false positives were detected with this method, it is of less concern seeing as these inaccuracies can be screened using simple blood tests. Promising results were obtained in this project, however, further studies using data-driven approaches such as partial least squares (PLS) are needed. / Thesis / Master of Science (MSc)

Les modalités d'imagerie fonctionnelle et de perfusion sont étroitement liées car les deux mesurent, directement ou indirectement, le débit sanguin cérébral. D’une part, en utilisant le contraste BOLD (Blood-Oxygen-Level-Dependent), l'imagerie fonctionnelle par résonance magnétique (IRMf) exploite les propriétés magnétiques du sang (oxy et désoxyhémoglobine) pour y mesurer les changements locaux de concentration en oxygène: ce couplage neurovasculaire permet de déduire le fonctionnement du cerveau à partir des images IRMf. D’autre part, l'IRM de perfusion reflète le fonctionnement du système vasculaire cérébral en mesurant directement le débit sanguin cérébral. En particulier, l’IRM du marquage de l’eau artérielle (ASL) n'a pas besoin d'agents de contraste: le traceur est remplacé par des spins de protons endogènes d'eau. Habituellement l’ASL est utilisée pour mesurer la perfusion basale au repos. Toutefois, ces dernières années, il a également été utilisé comme une modalité d'imagerie fonctionnelle (comme fASL) en mesurant les variations de perfusion cérébrale induites par la réalisation de tâches cognitives. Contrairement à l'IRMf standard basée sur le contraste BOLD, les résultats sont quantitatifs, ce qui rend ce type de données intéressantes pour son utilisation dans la recherche clinique.Cette thèse porte sur l’étude de la modalité fASL et sur le développement de nouvelles méthodes pour l'analyser. Comme précédemment réalisé pour les données BOLD, un cadre bayésien est développé pour l'analyse des données fASL. Il fournit un moyen de modéliser les valeurs d'activation et les fonctions de réponse hémodynamique et de perfusion en tant que variables probabilistes dans l’approche de Détection-Estimation Conjointe. Les modèles bayésiens utilisent une connaissance a priori pour l'estimation des paramètres inconnus à travers la spécification de distributions de probabilité. Dans ce travail, nous exploitons cette fonction pour incorporer au modèle des informations physiologiques, afin de rendre l'estimation plus robuste. En particulier, nous utilisons des modèles physiologiques basés sur le modèle de ballon pour obtenir un lien entre les réponses hémodynamiques et de perfusion, puis nous utilisons ce lien dans une distribution a priori pour régulariser l'estimation des réponses. En utilisant information physiologique a priori, une solution de type Markov Chain Monte Carlo (MCMC) a été proposée pour l'estimation des quantités contenues dans le signal IRMf. Étant donné que le coût de calcul de cet algorithme est très élevé, nous reformulons le problème pour utiliser une approche variationnelle (VEM) qui fournit un algorithme beaucoup plus rapide avec des résultats similaires. Dans ce cadre, l'introduction d'information a priori et de contraintes est également plus simple.Ces méthodes ont été évaluées sur deux ensembles de données différentes en utilisant des paradigmes événementiels et du bloc, pour des tâches cognitives très simples. Nous montrons les bonnes performances des méthodes proposées par rapport aux méthodes standards, au niveau des sujets et du groupe. Les résultats expérimentaux montrent que les probabilités a priori physiologiques améliorent l'estimation d'une fonction de réponse de perfusion. Ces résultats démontrent également que le contraste BOLD a une meilleure sensibilité pour la détection de l'activité cérébrale évoquée que fASL, bien que la fASL donne une activation plus localisée, ce qui est conforme à la littérature existante. A partir de ces résultats, nous discutons l'impact de la modélisation de la corrélation spatiale, ainsi que l'impact de l'estimation des réponses temporelles.Ce travail propose de nouvelles contributions méthodologiques pour l'étude de la fASL, et les met en perspective avec les techniques existantes. Ainsi, nous proposons de nouveaux outils pour la communauté neuroscientifique, mis en œuvre en python dans le package PyHRF, pour étudier et comprendre le fonctionnement du cerveau. / Functional and perfusion imaging modalities are closely related since they both measure, directly or indirectly, blood flow in the brain. Functional Magnetic Resonance Imaging (fMRI) using the blood oxygen level dependent (BOLD) contrast exploits the magnetic properties of blood (oxy- and deoxyhemoglobin) to measure local changes in blood oxygen concentration in the brain. The neurovascular coupling allows us to infer brain function from fMRI images. Perfusion MRI images the cerebral vascular system by directly measuring blood flow. In particular, Arterial Spin Labeling (ASL) does not need contrast agents; it uses spins of endogenous water protons as a tracer instead. Usually ASL is used to probe the basal perfusion at rest. However, in the recent years, it has also been used as a functional imaging modality (as fASL) by tracking task-related perfusion changes. In contrast to the standard BOLD fMRI, results are quantitative, making this type of data attractive for use in clinical research.This thesis focuses on the investigation of the fASL modality and the development of new methods to analyze it. As previously done for BOLD data, a Bayesian framework is proposed for the analysis of fASL data. It provides a way of modeling activation values and both hemodynamic and perfusion response functions as probabilistic variables in the so-called joint detection estimation (JDE) framework. Bayesian models use a priori knowledge in the estimation of unknown parameters through the specification of probability distributions. In this work, we exploit this feature to incorporate physiological information to make the estimation more robust. In particular, we use physiological models based on the balloon model to derive a link between hemodynamic and perfusion responses and we turn this link into a prior distribution to regularize the estimation of the responses. A Markov Chain Monte Carlo solution with prior physiological knowledge has been first proposed for the estimation of the quantities contained in the fMRI signal. Since the computational cost of this algorithm is very high, we then reformulate the problem to use a variational expectation maximization approach that provides a much faster algorithm with similar results. The use of priors and constraints in this setting is also more straightforward.These methods have been evaluated on two different datasets using event-related and block designs with very simple experimental tasks. We show the performance of the methods investigated in comparison to standard methods at the subject and group levels. Experimental results show the utility of using physiological priors for improving the recovery of a perfusion response function. They also demonstrate that BOLD fMRI achieves better sensitivity to detect evoked brain activity as compared to fASL although fASL gives a more localized activation, which is in line with the existing literature. From the results, we discuss the impact of the modelling of spatial correlation, as well as the impact of the estimation of temporal responses.This work proposes new methodological contributions in the study of a relatively new fMRI modality that is functional ASL, and puts it into perspective with the existing techniques. Thus, we provide new tools for the neuroscientific community to study and understand brain function. These tools have been implemented in python in the PyHRF package.

Les ganglions de la base (GB) sont des structures cérébrales profondes participant à la sélection de comportements adaptés, avec ses composantes motrices, cognitives et émotionnelles. L’étude par IRMf BOLD de ces structures présente un grand intérêt pour explorer leur rôle et leur dysfonctionnement dans certaines pathologies, comme la maladie de Parkinson (MP). Cette technique permet, par l’étude du signal BOLD, de mettre en évidence des activations cérébrales suite à une activation neuronale. Or l’IRMf BOLD a été optimisée pour l’étude des activations corticales, et la mise en évidence d’activations dans les GB est difficile, surtout au niveau individuel. Ceci est en parti lié au fait que le signal BOLD est plus faible dans ces structures par rapport au cortex. Plusieurs raisons peuvent expliquer ce faible signal BOLD. Ainsi la charge en fer de ses structures, modifiant le paramètre de relaxation T 2 *, peut en être une des causes. En effet, la sensibilité de mesure du signal BOLD est optimale lorsque le temps d’écho (TE) de la séquence d’acquisition égale le T 2 * de la structure cérébrale d’intérêt. Notre premier travail a consisté à étudier l’hétérogénéité du T 2 * dans différentes structures cérébrales en tenant compte des effets de la MP, pathologie connue pour entrainer des accumulations de fer dans certaines régions. Nous avons par ailleurs étudié l’évolution du T 2 * de manière longitudinale, et ce paramètre est apparu comme un biomarqueur intéressant de l’évolutivité de la MP. Le deuxième travail a été consacré à étudier les activations des GB en tenant compte de l’hétérogénéité du T 2 *. Nous avons étudié les activations cérébrales suite à la réalisation d’une tâche motrice, en explorant entre autres l’effet TE. Nous avons montré que le choix du TE a finalement peu d’impact sur la capacité de détection des activations au niveau des GB. Nous proposons une stratégie pour l’étude individuelle de l’activité cérébrale au niveau des GB en utilisant le pourcentage de changement du signal BOLD dans des régions cérébrales d’intérêt préalablement définies sur l’analyse de groupe. / The basal ganglia (BG) are deep brain structures involved in the selection of appropriate behavior, with motor, cognitive and emotional components. The BOLD fMRI study of these structures is of great interest to explore their role and dysfunction in certain diseases, such as Parkinson's disease (PD). By studying the BOLD signal, this technique allows to identify brain activation following neuronal activation. However BOLD fMRI has been optimized for the study of cortical activations and detection of activations in the BG is difficult, mainly at the individual level. This is partly due to the fact that the BOLD signal is lower in these structures in relation to the cortex. Several reasons may explain the BOLD signal attenuation. Thereby, iron load in its structures, which changes the relaxation parameter T 2 *, may be a cause. Indeed, the BOLD signal is optimal when the echo time (TE) of the MRI acquisition sequence equal T 2 * of the considered brain structure. Our first work was to study the heterogeneity of T 2 * in different brain structures, taking into account the effects of PD. Indeed, PD is known to induce iron accumulation some regions. We also studied the evolution of T 2 * longitudinally, and this parameter has emerged as an interesting biomarker to track PD progression. The second work was to study the activation of BG taking into account T 2 * heterogeneity. We studied brain activation during a motor task, exploring in particular the effect of TE. We showed that the choice of TE has a low impact on BG activation detection sensitivity. We propose a strategy for individual quantification of neuronal activity in the BG, using the BOLD percentage signal change in pre-defined regions of interest, obtained from the group analysis.

Master's thesis focuses on processing fMRI data, which are mapping blood oxygenation level dependence in a state of brain activity. Usable and necessarily preprocessing tech- niques of the data, together with two main analysis approaches are introduced. The area of univariate methods, especially general linear model and multivariate principal or independent component analysis is explained. Practical application of the methods involved on the real fMRI data set is implemented. Relevant results as well as theirs mutual possible comparison is presented.

This thesis describes the development, implementation and application of various quantitative functional magnetic resonance imaging (fMRI) approaches at ultra-high magnetic field including the assessment with regards to applicability and reproducibility. Functional MRI (fMRI) commonly uses the blood oxygenation level dependent (BOLD) contrast to detect functionally induced changes in the oxy-deoxyhaemoglobin composition of blood which reflect cerebral neural activity. As these blood oxygenation changes do not only occur at the activation site but also downstream in the draining veins, the spatial specificity of the BOLD signal is limited. Therefore, the focus has moved towards more quantitative fMRI approaches such as arterial spin labelling (ASL), vascular space occupancy (VASO) or calibrated fMRI which measure quantifiable physiologically and physically relevant parameters such as cerebral blood flow (CBF), cerebral blood volume (CBV) or cerebral metabolic rate of oxygen (CMRO2), respectively. In this thesis a novel MRI technique was introduced which allowed the simultaneous acquisition of multiple physiological parameters in order to beneficially utilise their spatial and temporal characteristics. The advantages of ultra-high magnetic field were utilised to achieve higher signal-to-noise and contrast-to-noise ratios compared to lower field strengths. This technique was successfully used to study the spatial and temporal characteristics of CBV, CBF and BOLD in the visual cortex. This technique is the first one that allows simultaneous acquisition of CBV, CBF and BOLD weighted fMRI signals in the human brain at 7 Tesla. Additionally, this thesis presented a calibrated fMRI technique which allowed the quantitative estimation of changes in cerebral oxygen metabolism at ultra-high field. CMRO2 reflects the amount of thermodynamic work due to neural activity and is therefore a significant physical measure in neuroscience. The calibrated fMRI approach presented in this thesis was optimised for the use at ultra-high field by adjusting the MRI parameters as well as implementing a specifically designed radio-frequency (RF) pulse. A biophysical model was used to calibrate the fMRI data based on the simultaneous acquisition of BOLD and CBF weighted MRI signals during a gas-breathing challenge. The reproducibility was assessed across multiple brain regions and compared to that of various physiologically relevant parameters. The results indicate that the degree of intra-subject variation for calibrated fMRI is lower than for the classic BOLD contrast or ASL. Consequently, calibrated fMRI is a viable alternative to classic fMRI contrasts with regards to spatial specificity as well as functional reproducibility. This calibrated fMRI approach was also compared to a novel direct calibration technique which relies on complete venous oxygenation saturation during the calibration scan via a gas-breathing challenge. This thesis introduced several reliable quantitative fMRI approaches at 7 Tesla and the results presented are a step forward to the wider application of quantitative fMRI.:1 Introduction 3 2 Background to Functional Magnetic Resonance Imaging 7 2.1 Magnetic Resonance 7 2.1.1 Quantum Mechanics 7 2.1.2 The Classical Point of View 10 2.1.3 Radio Frequency Pulses 12 2.1.4 Relaxation Effects 13 2.1.5 The Bloch Equations 15 2.2 Magnetic Resonance Imaging 16 2.2.1 Data Acquisition 16 2.2.2 Image Formation 17 2.2.2.1 Slice Selection 17 2.2.2.2 Frequency Encoding 18 2.2.2.3 Phase Encoding 19 2.2.2.4 Mathematics of Image Formation 20 2.2.2.5 Signal Formation 22 2.3 Advanced Imaging Methods 24 2.3.1 Echo-Planar Imaging (EPI) 24 2.3.2 Partial Fourier Acquisition 25 2.3.3 Generalised Autocalibrating Partially Parallel Acquisition (GRAPPA) 25 2.3.4 Inversion Recovery (IR) 26 2.3.5 Adiabatic Inversion 26 2.3.5.1 Hyperbolic Secant (HS) RF pulses 28 2.3.5.2 Time Resampled Frequency Offset Corrected Inversion (tr-FOCI) RF Pulses 28 2.4 Physiological Background 29 2.4.1 Neuronal Activity 30 2.4.2 Energy Metabolism 31 2.4.3 Physiological Changes During Brain Activation 32 2.4.4 The BOLD Contrast 34 2.4.5 Disadvantages of the BOLD Contrast 35 2.5 Arterial Spin Labelling (ASL) 35 2.5.1 Pulsed Arterial Spin Labelling 37 2.5.2 Arterial Spin Labelling at Ultra-High Field 41 2.6 Vascular Space Occupancy (VASO) 42 2.6.1 VASO at Ultra-High Field 44 2.6.2 Slice-Saturation Slab-Inversion (SS-SI) VASO 45 2.7 Calibrated Functional Magnetic Resonance Imaging 47 2.7.1 The Davis Model 47 2.7.2 The Chiarelli Model 50 2.7.3 The Generalised Calibration Model (GCM) 52 3 Materials and Methods 53 3.1 Scanner Setup 53 3.2 Gas Delivery and Physiological Monitoring System 53 3.3 MRI Sequence Developments 55 3.3.1 Tr-FOCI Adiabatic Inversion 55 3.3.2 Optimisation of the PASL FAIR QUIPSSII Sequence Parameters 60 3.3.3 Multi-TE Multi-TI EPI 64 4 Experiment I: Comparison of Direct and Modelled fMRI Calibration 68 4.1 Background Information 68 4.2 Methods 69 4.2.1 Experimental Design 69 4.2.2 Visuo-Motor Task 70 4.2.3 Gas Manipulations 71 4.2.4 Scanning Parameters 71 4.2.5 Data Analysis 72 4.2.6 M-value Modelling 72 4.2.7 Direct M-Value Estimation 73 4.3 Results 74 4.4 Discussion 79 4.4.1 M-value Estimation 79 4.4.2 BOLD Time Courses 82 4.4.3 M-Maps and Single Subject Analysis 82 4.4.4 Effects on CMRO2 Estimation 83 4.4.5 Technical Limitations and Implications for Calibrated fMRI 84 4.5 Conclusion 89 5 Experiment II: Reproducibility of BOLD, ASL and Calibrated fMRI 90 5.1 Background Information 90 5.2 Methods 91 5.2.1 Experimental Design 91 5.2.2 Data Analysis 91 5.2.3 Reproducibility 93 5.2.4 Learning and Habituation Effects 95 5.3 Results 95 5.4 Discussion 101 5.4.1 Breathing Manipulations 102 5.4.2 Functional Reproducibility 107 5.4.3 Habituation Effects on Reproducibility 109 5.4.4 Technical Considerations for Calibrated fMRI 110 5.5 Conclusion 112 6 Experiment III: Simultaneous Acquisition of BOLD, ASL and VASO Signals 113 6.1 Background Information 113 6.2 Methods 114 6.2.1 SS-SI VASO Signal Acquisition 114 6.2.2 ASL and BOLD Signal Acquisition 114 6.2.3 Experimental Design 114 6.2.4 Data Analysis 115 6.3 Results 115 6.4 Discussion 116 6.5 Conclusion 120 7 Conclusion and Outlook 121

Echo-planar Imaging (EPI) erzeugt durch schnell wechselnde Gradienten beträchtliche Schallemissionen. Dies führt nachgewiesenermaßen bei funktionellen Magnet-Resonanz-Tomographie- (fMRT-) Studien zu einer Aktivierung des auditiven Systems, insofern dieses beim jeweiligen Probanden in der Lage ist zu reagieren. Sowohl für auditive wie auch für nicht-auditive Untersuchungen wurden verschiedenste Anstrengungen unternommen, diese Interferenzen zu minimieren. Anstatt den Lärm des Scanners zu reduzieren oder die Transmission des Schalls zu behindern, war es nun das Ziel, eben diesen Schall zur Aktivierung des auditiven Kortex zu benutzen und diese mit fMRT-Untersuchungen nachzuweisen. Dieses geschieht schlicht durch das Auslassen von Read-Outs aus der Gradientenfolge der Pulssequenz. Diese Pulse sind die Hauptemissionsquellen von Schall des EPI, sie verursachen sowohl den Spitzenschallpegel als auch die Grundfrequenz, welche im umgekehrten Verhältnis zum Echo-Spacing steht. Durch eine Modell-gestützte Analyse wird gezeigt, dass das Auslassen von Read-Outs nach einem vordefinierten Schema verlässlich dazu geeignet ist, eine hämodynamische Blood-Oxygenation-Level-Dependent- (BOLD-) Signalveränderung im auditiven Kortex von normal hörenden Probanden (n=60) zu evozieren. Um den Nutzen der Technik beim auditiven fMRI zu zeigen, werden auf der Ebene der Einzelanalysen das traditionelle Family-Wise-Error-Rate- (FWER-) korrigierte Maximum Height Thresholding mit dem Spatial Mixture Modelling (SMM) verglichen. Mit Letzterem können so in 95 % der Fälle eine adäquate, bilaterale, auditive Aktivierung nachwiesen werden, wohingegen das FWER-basierte Voxel-Thresholding nur in 72 % aller Probanden eine solche Aktivierung zeigt. Um die klinische Anwendbarkeit der Technik unter pathologischen Bedingungen zu demonstrieren, wird ein Fallbericht einer Patientin vorgestellt, die an einem schweren, beidseitigen Sensorineural Hearing Loss (SNHL) aufgrund bilateraler Large Vestibular Aqueducts (LVAs) leidet. Dabei wird eben diese Modifikation benutzt, um präoperativ vor Cochlear Implantation (CI) zu zeigen, dass ein zentrales Resthörvermögen vorhanden ist. Da die Untersuchung völlig unabhängig von der Compliance des Patienten und kein zusätzliches Zubehör zum Scanner vonnöten sind, eignet sie sich hervorragend zu auditiven Untersuchungen, um so schnell das Hörvermögen zu prüfen. Dabei funktioniert die Methode unabhängig von äußerlichen Bedingungen: Bei hörgesunden Probanden ebenso wie bei Hörgeschädigten, bei Kindern, Jugendlichen und Erwachsenen aller Altersstufen sowie unabhängig von einer Sedierung während der Untersuchung. Beide benutzten Scanner zeigten unabhängig vom Gradienten oder der verwendeten Spule ein gleiches Ergebnis. / Echo-planar Imaging (EPI) induces considerable sound emissions by steep gradient pulses. This leads evidentially to an activation of the auditory system, as much it is able to response in that particular subject. For auditory as well as non-auditory investigations, various efforts have been undertaken to minimize those interferences. Instead of reducing the scanner noise or cumbering its transmission, the goal was now to utilize it to activate the auditory cortex and detect it later on by functional magnetic resonance imaging (fMRI). This was achieved by simply omitting read-outs from the gradient train of an EPI pulse sequence. Those pulses are the primary noise determinant in EPI, they induce both the peak sound level and the fundamental frequency peak, which relates inversely to the echo spacing. By hypothesis-driven analyses it is demonstrated that withholding read-out gradients in a defined scheme reliably evokes hemodynamic Blood Oxygenation Level Dependent (BOLD) signal modulations in the auditory cortex of normal hearing subjects (n=60). To show the value of this new method, the first level analyses of the single subjects with the traditional Family-Wise-Error-Rate (FWER-) corrected Maximum Height Thresholding are compared with Spatial Mixture Modelling (SMM). This way in 95 % of all subjects an appropriate, bilateral auditory activation was detected with SMM, whereas the FWER-based Voxel-Thresholding revealed such activation in only 72 %. To show the clinical practicability of the new technique under pathological conditions the case report of a patient with severe, binaural Sensoneurinal Hearing Loss (SNHL) due to bilateral Large Vestibular Aqueducts (LVA) is presented. Thereby this modification is used to confirm residual audition prior to cochlear implantation (CI). As the investigation is totally independent of the patient's compliance and no additional equipment other than the scanner is necessary, it is suited well as a quick testing for central audition. At the same time the approach is absolutely independent from other conditions: It works with normal hearing subjects as well as with hearing impaired patients; with children, adolescents as well as adults of all age brackets and regardless of sedation during the test. Both scanners, that were used, showed independent from the gradient or the coil the same results.

Magnetic source magnetic resonance imaging (msMRI) is an fMRI technique that has been under development for direct detection of neuronal magnetic fields to map brain activity and has been shown to be experimentally detectable using conventional means, but there is debate on the detection of the msMRI signal since it can be only a 0.2% change. Detection of its temporal characteristics has yet to be reported and may strengthen the case for msMRI detection. The temporal characteristics of the detected msMRI signal were examined in this work, but it was found that the sensitivity of conventional analysis techniques are low within the context of msMRI, preventing consistent msMRI signal detection and analysis of its temporal characteristics. Examination of blood oxygen level dependent (BOLD) contrast contamination and application of mean-shift clustering (MSC) to fMRI analysis were performed to look into the possibility of improving the low sensitivity. fMRI analysis is commonly performed with cross correlation analysis (CCA) and techniques based on the General Linear Model (GLM), but both CCA and GLM techniques typically perform calculations on a per-voxel basis and do not consider relationships neighboring voxels may have. MSC is a technique to consider for this purpose and shows improved activation detection for both simulated and real BOLD fMRI data. To consider the issue of BOLD contamination, the hemodynamic response over time was examined using repeated median nerve stimulation. On average, the results show the BOLD signal is not detectable after the second fMRI run. The results are consistent with previous hemodynamic habituation effect studies with other types of stimulation, but they do not completely agree with findings of evoked potential studies. Overall, this work shows that the low detection sensitivity may be able to be addressed with the purpose of furthering msMRI research.

CSI at UBC: How David Sweet is using dental forensics to pit modern science against criminals.

Typescript (Photocopy) / Bibliography: leaves 166-189 / 2 v. : ill., maps ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--Dept. of Botany, University of Adelaide, 1991