Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Magnetic Resonance Imaging of concrete

http://www-civ.eng.cam.ac.uk/cjb/papers/cp88.pdf

Magnetic susceptibility and electron magnetic resonance study of monovalent potassium doped manganites Pr0.6Sr0.4-xK xMnO3

The monovalent potassium doped manganites Pr0.6Sr 0.4-xKxMnO3 (x = 0.05-0.2) are characterized using the complementary magnetic susceptibility and electron resonance methods. In paramagnetic phase the temperature variations of the inverse magnetic susceptibility and the inverse intensity of resonance signal obey the Curie-Weiss law. A similarity in temperature variation of resonance signal width and the adiabatic polaron conductivity points to the polaron mechanism controlling the resonance linewidth. The low temperature limit of the pure paramagnetic phase is determined from the electron resonance spectra revealing the mixed phase spread down to the Curie temperature. © 2013 Elsevier B.V. All rights reserved.

Functional magnetic resonance imaging of impaired sensory prediction in schizophrenia.

IMPORTANCE: Forward models predict the sensory consequences of planned actions and permit discrimination of self- and non-self-elicited sensation; their impairment in schizophrenia is implied by an abnormality in behavioral force-matching and the flawed agency judgments characteristic of positive symptoms, including auditory hallucinations and delusions of control. OBJECTIVE: To assess attenuation of sensory processing by self-action in individuals with schizophrenia and its relation to current symptom severity. DESIGN, SETTING, AND PARTICIPANTS: Functional magnetic resonance imaging data were acquired while medicated individuals with schizophrenia (n = 19) and matched controls (n = 19) performed a factorially designed sensorimotor task in which the occurrence and relative timing of action and sensation were manipulated. The study took place at the neuroimaging research unit at the Institute of Cognitive Neuroscience, University College London, and the Maudsley Hospital. RESULTS: In controls, a region of secondary somatosensory cortex exhibited attenuated activation when sensation and action were synchronous compared with when the former occurred after an unexpected delay or alone. By contrast, reduced attenuation was observed in the schizophrenia group, suggesting that these individuals were unable to predict the sensory consequences of their own actions. Furthermore, failure to attenuate secondary somatosensory cortex processing was predicted by current hallucinatory severity. CONCLUSIONS AND RELEVANCE: Although comparably reduced attenuation has been reported in the verbal domain, this work implies that a more general physiologic deficit underlies positive symptoms of schizophrenia.

Adapting data processing to compare model and experiment accurately: A discrete element model and magnetic resonance measurements of a 3d cylindrical fluidized bed

Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. © 2013 American Chemical Society.