Our group is engaged in the development of methods for magnetic resonance imaging (MRI) and spectroscopy (MRS) including pulse sequences, RF hardware and image processing. Their applications aim at a quantitative characterization of brain tissue composition or physiological processes to understand the anatomy of the brain, its metabolism, and its activity as well as the biophysical processes underlying image contrast.
Available PhD projects
1. The combination of different strategies for quantitative magnetic resonance imaging (qMRI) and magnetic resonance spectroscopic imaging (MRSI) yields multi-parametric data for the non-invasive structural and metabolic characterization of the human brain in vivo. Further expansion is possible if the MR acquisition is combined with simultaneous positron emission tomography (PET) in a multi-modal setting. The project aims at the development of suitable multi-modal acquisition strategies to assess neurotransmitter systems (e.g. glutamate, GABA and dopamine) and iron metabolism in the motor system. Implement quality control procedures are required to deal with motion artifacts for application of the methods in a movement disorder population (here, Gilles de la Tourette syndrome) for gaining insights into the pathophysiology and further correlations with default gene-expression profiles.
2. Disentangling neuronal activity as a function of cortical depth is an area of rapidly increasing interest. The majority of functional magnetic resonance imaging (fMRI) experiments are based on the blood-oxygenation level dependent (BOLD) contrast. However, BOLD signal changes cannot be easily related to underlying physiological processes and are weighted towards draining veins on the cortical surface, which limit the spatial specificity. Regional measurements of cerebral blood flow (CBF) and volume (CBV) changes are useful concepts to address these inherent limitations. Calibrated fMRI techniques yield metabolic information; however, the underlying models require adaptation to account for the conditions at laminar resolution.
3. Neural connections via axons and synapses are characterized by connection strength and delay. To study these properties, we will use diffusion-weighted (dw) magnetic resonance imaging (MRI) acquired at high spatial and angular resolution and multiple diffusion times. Additional information can be obtained from measurements of relaxation times T1, T2, and T2* as well as from quantitative susceptibility mapping (QSM). Such data can be combined to gain information on profiles of MRI parameters along fiber tracts.
4. Motion during image acquisition is a major source of artifacts in imaging data. It is planned to study the influence of motion artifacts and various correction methods on resting-state data and task-based fMRI by various approaches, e.g., by applying realistic motion parameters to artificial datasets, or by comparing the results of motion correction with data from a motion tracking system.