NeuroImage
-
Although functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) signal changes is a sensitive tool for mapping brain activation, quantitative studies of the physiological effects of pharmacological agents using fMRI alone are difficult to interpret due to the complexities inherent in the BOLD response. Hypercapnia-calibrated BOLD methodology is potentially a more powerful physiological probe of brain function, providing measures of the changes in cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO(2)). In this study, we implemented a quantitative R(2)* approach for assessing the BOLD response to improve the stability of repeated measurements, in combination with the calibrated BOLD method, to examine the CBF and CMRO(2) responses to caffeine ingestion. ⋯ For a region of interest defined by CBF activation to the visual stimulus, the results were: hypercapnia increased CBF (+46.6%, +/-11.3, mean and standard error), visual stimulation increased both CBF (+47.9%, +/-2.9) and CMRO(2) (+20.7%, +/-1.4), and caffeine decreased CBF (-34.5%, +/-2.6) with a non-significant change in CMRO(2) (+5.2%, +/-6.4). The coupling between CBF and CMRO(2) was significantly different in response to visual stimulation compared to caffeine consumption. A calibrated BOLD methodology using R(2) * is a promising approach for evaluating CBF and CMRO(2) changes in response to pharmacological interventions.
-
Independent component analysis (ICA) of fMRI data generates session/individual specific brain activation maps without a priori assumptions regarding the timing or pattern of the blood-oxygenation-level-dependent (BOLD) signal responses. However, because of a random permutation among output components, ICA does not offer a straightforward solution for the inference of group-level activation. In this study, we present an independent vector analysis (IVA) method to address the permutation problem during fMRI group data analysis. ⋯ Compared to GLM, IVA successfully captured activation patterns even when the functional areas showed variable hemodynamic responses that deviated from a hypothesized response. We also showed that IVA effectively inferred group-activation patterns of unknown origins without the requirement for a pre-processing stage (such as data concatenation in ICA-based GIFT). IVA can be used as a potential alternative or an adjunct to current ICA-based fMRI group processing methods.
-
Neuropathological examination in Friedreich ataxia (FRDA) reveals neuronal loss in the gray matter (GM) nuclei and degeneration of the white matter (WM) tracts in the spinal cord, brainstem and cerebellum, while the cerebral hemispheres are substantially spared. Tract-based spatial statistics (TBSS) enables an unbiased whole-brain quantitative analysis of the fractional anisotropy (FA) and mean diffusivity (MD) of the brain WM tracts in vivo. ⋯ TBSS enables in vivo demonstration of degeneration of the brainstem and cerebellar WM tracts which neuropathological examination indicates to be specifically affected in FRDA. TBSS complements VBM and might be a more sensitive tool to detect WM structural changes in degenerative diseases of the CNS.
-
While conventional magnetic resonance imaging (MRI) has long been used to study multiple sclerosis (MS), more sensitive and specific approaches to studying both MS lesions and normal appearing white matter (NAWM) are needed to gain a better understanding of the pathogenesis of the disease. Two MRI techniques thought to offer insight regarding myelin and axonal integrity are T(2) relaxation and diffusion tensor imaging (DTI). ⋯ All of the diffusion metrics were significantly different in lesions with a long-T(2) signal than in those without. While no significant correlations were found between MWC and
, lambda(||) or lambda(perpendicular) in NAWM (R(2)=0.02-0.04, p>0.07), and only weak correlations were found in lesions without long-T(2) signal (R(2)=0.05-0.14, p<0.04), strong correlations were observed in lesions exhibiting long-T(2) signal (R(2)=0.54-0.61, p<0.0001). -
Detecting neuronal activity by functional magnetic resonance imaging (fMRI) based on the blood oxygenation level dependent (BOLD) contrast can be problematic since the contrast reflects changes in blood oxygenation which can be distant from the activated site, e.g. in the presence of large veins. In this work, a novel approach is presented to increase specificity, i.e. to confine the origin of the BOLD contrast to the microvasculature, by predicting the average venous vessel radius in activated voxels, and to filter out those voxels whose contrast is dominated by large veins. ⋯ Due to the high temporal and spatial resolution, this sequence is suitable for routine fMRI applications. In addition, the technique provides additional insight into the origin of the BOLD contrast, such as the impact of the significance threshold on the macrovascular contribution to the fMRI signal.