@phdthesis{Dieler2011,
  author    = {Dieler, Alica Christina},
  title     = {Investigation of variables influencing cognitive inhibition: from the behavioral to the molecular level},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-65955},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {The present work investigated the neural mechanisms underlying cognitive inhibition/thought suppression in Anderson's and Green's Think/No-Think paradigm (TNT), as well as different variables influencing these mechanisms at the cognitive, the neurophysiological, the electrophysiological and the molecular level. Neurophysiological data collected with fNIRS and fMRI have added up to the existing evidence of a fronto-hippocampal network interacting during the inhibition of unwanted thoughts. Some evidence has been presented suggesting that by means of external stimulation of the right dlPFC through iTBS thought suppression might be improved, providing further evidence for an implication of this region in the TNT. A combination of fNIRS with ERP has delivered evidence of a dissociation of early condition-independent attentional and later suppression-specific processes within the dlPFC, both contributing to suppression performance. Due to inconsistencies in the previous literature it was considered how stimulus valence would influence thought suppression by manipulating the emotional content of the to-be-suppressed stimuli. Findings of the current work regarding the ability to suppress negative word or picture stimuli have, however, been inconclusive as well. It has been hypothesized that performance in the TNT might depend on the combination of valence conditions included in the paradigm. Alternatively, it has been suggested that inconsistent findings regarding the suppression of negative stimuli or suppression at all might be due to certain personality traits and/or genetic variables, found in the present work to contribute to thought inhibition in the TNT. Rumination has been shown to be a valid predictor of thought suppression performance. Increased ruminative tendencies led to worse suppression performance which, in the present work, has been linked to less effective recruitment of the dlPFC and in turn less effective down-regulation of hippocampal activity during suppression trials. Trait anxiety has also been shown to interrupt thought suppression despite higher, however, inefficient recruitment of the dlPFC. Complementing the findings regarding ruminative tendencies and decreased thought inhibition a functional polymorphism in the KCNJ6 gene, encompassing a G-to-A transition, has been shown to disrupt thought suppression despite increased activation of the dlPFC. Through the investigation of thought suppression at different levels, the current work adds further evidence to the idea that the TNT reflects an executive control mechanism, which is sensitive to alterations in stimulus valence to some extent, neurophysiological functioning as indicated by its sensitivity to iTBS, functional modulations at the molecular level and personality traits, such as rumination and trait anxiety.},
  subject      = {Kognitiver Prozess},
  language  = {en}
}
@phdthesis{Seiberlich2008,
  author    = {Seiberlich, Nicole},
  title     = {Advances in Non-Cartesian Parallel Magnetic Resonance Imaging using the GRAPPA Operator},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-28321},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2008},
  abstract  = {Magnetic Resonance Imaging (MRI) is an imaging modality which provides anatomical or functional images of the human body with variable contrasts in an arbitrarily positioned slice without the need for ionizing radiation. In MRI, data are not acquired directly, but in the reciprocal image space (otherwise known as k-space) through the application of spatially variable magnetic field gradients. The k-space is made up of a grid of data points which are generally acquired in a line-by-line fashion (Cartesian imaging). After the acquisition, the k-space data are transformed into the image domain using the Fast Fourier Transformation (FFT). However, the acquisition of data is not limited to the rectilinear Cartesian sampling scheme described above. Non-Cartesian acquisitions, where the data are collected along exotic trajectories, such as radial and spiral, have been shown to be beneficial in a number of applications. However, despite their additional properties and potential advantages, working with non-Cartesian data can be complicated. The primary difficulty is that non-Cartesian trajectories are made up of points which do not fall on a Cartesian grid, and a simple and fast FFT algorithm cannot be employed to reconstruct images from non-Cartesian data. In order to create an image, the non-Cartesian data are generally resampled on a Cartesian grid, an operation known as gridding, before the FFT is performed. Another challenge for non-Cartesian imaging is the combination of unusual trajectories with parallel imaging. This thesis has presented several new non-Cartesian parallel imaging methods which simplify both gridding and the reconstruction of images from undersampled data. In Chapter 4, a novel approach which uses the concepts of parallel imaging to grid data sampled along a non-Cartesian trajectory called GRAPPA Operator Gridding (GROG) is described. GROG shifts any acquired k-space data point to its nearest Cartesian location, thereby converting non-Cartesian to Cartesian data. The only requirements for GROG are a multi-channel acquisition and a calibration dataset for the determination of the GROG weights. Chapter 5 discusses an extension of GRAPPA Operator Gridding, namely Self-Calibrating GRAPPA Operator Gridding (SC-GROG). SC-GROG is a method by which non-Cartesian data can be gridded using spatial information from a multi-channel coil array without the need for an additional calibration dataset, as required in standard GROG. Although GROG can be used to grid undersampled datasets, it is important to note that this method uses parallel imaging only for gridding, and not to reconstruct artifact-free images from undersampled data. Chapter 6 introduces a simple, novel method for performing modified Cartesian GRAPPA reconstructions on undersampled non-Cartesian k-space data gridded using GROG to arrive at a non-aliased image. Because the undersampled non-Cartesian data cannot be reconstructed using a single GRAPPA kernel, several Cartesian patterns are selected for the reconstruction. Finally, Chapter 7 discusses a novel method of using GROG to mimic the bunched phase encoding acquisition (BPE) scheme. In MRI, it is generally assumed that an artifact-free image can be reconstructed only from sampled points which fulfill the Nyquist criterion. However, the BPE reconstruction is based on the Generalized Sampling Theorem of Papoulis, which states that a continuous signal can be reconstructed from sampled points as long as the points are on average sampled at the Nyquist frequency. A novel method of generating the "bunched" data using GRAPPA Operator Gridding (GROG), which shifts datapoints by small distances in k-space using the GRAPPA Operator instead of employing zig-zag shaped gradients, is presented in this chapter. With the conjugate gradient reconstruction method, these additional "bunched" points can then be used to reconstruct an artifact-free image from undersampled data. This method is referred to as GROG-facilitated Bunched Phase Encoding, or GROG-BPE.},
  subject      = {NMR-Tomographie},
  language  = {en}
}