NeuroImage
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FMRI modelling requires flexible haemodynamic response function (HRF) modelling, with the HRF being allowed to vary spatially and between subjects. To achieve this flexibility, voxelwise parameterised HRFs have been proposed; however, inference on such models is very slow. An alternative approach is to use basis functions allowing inference to proceed in the more manageable General Linear Model (GLM) framework. ⋯ Here we extend the work of Penny et al. to give inference on the GLM with constrained HRF basis functions and with spatial Markov Random Fields on the autoregressive noise parameters. Constraining the subspace spanned by the basis set allows for far superior separation of activating voxels from nonactivating voxels in FMRI data. We use spatial mixture modelling to produce final probabilities of activation and demonstrate increased sensitivity on an FMRI dataset.
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A method for quantitative determination of the glutamate (Glu) concentration in human brain using PRESS-based single voxel MR spectroscopy (MRS) at 3 T has been developed and validated by repeatedly analyzing voxels comprising the anterior cingulate cortex (acc) and the left hippocampus (hc) in 40 healthy volunteer brains. At an optimum echo time of 80 ms, the C4 resonance of Glu appears well resolved and separated from major interferents, that is, glutamine and N-acetylaspartate. As a complementary method, a multiple quantum coherence filter sequence for Glu was employed. ⋯ When the concentrations were corrected by individual cerebrospinal fluid fractions obtained by segmentation using spm, CVs tended to increase and the correlation coefficients for the two MRS sessions tended to decrease, indicating that this type of correction adds uncertainty to the data. The concentrations of Glu in the two voxels studied were found to be significantly different (11.6 mmol/l in acc, 10.9 mmol/l in hc, P = 0.023) and decrease with age (P < 0.04). These concentrations agreed well with those determined using the quantum coherence filter method although the uncertainty of the latter limits reliable analysis.