Magnetic resonance imaging
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Noninvasive functional studies on human spinal cord by means of magnetic resonance imaging (MRI) are gaining attention because of the promising applications in the study of healthy and injured central nervous system. The findings obtained are generally consistent with the anatomic knowledge based on invasive methods, but the origin and specificity of functional contrast is still debated. In this paper, a review of current knowledge and major issues about functional MRI (fMRI) in the human spinal cord is presented, with emphasis on the main methodological and technical problems and on forthcoming applications as clinical tool.
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Different brain imaging devices are presently available to provide images of the human functional cortical activity, based on hemodynamic, metabolic or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions are interconnected. The concept of brain connectivity plays a central role in the neuroscience, and different definitions of connectivity, functional and effective, have been adopted in literature. ⋯ The statistical analysis returned that during simulations, both SEM and DTF estimators were able to correctly estimate the imposed connectivity patterns under reasonable operative conditions, that is, when data exhibit an SNR of at least 3 and a LENGTH of at least 75 s of nonconsecutive EEG recordings at 64 Hz of sampling rate. Hence, effective and functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high-resolution EEG techniques and linear inverse estimation with SEM or DTF methods. We conclude that the estimation of cortical connectivity can be performed not only with hemodynamic measurements, but also with EEG signals treated with advanced computational techniques.
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A quantitative analysis of cerebellar metabolites in normal subjects has been performed by proton MR spectroscopy (MRS) with relaxation time correction. Quantitation was carried out in seven healthy human subjects with the well-established LCModel program. The prior knowledge utilized for quantitation was obtained from solutions containing the major brain metabolites and MRS investigated under the same experimental conditions. ⋯ Both in vitro (for the prior knowledge template) and in vivo data were acquired separately at 1.5 T by PRESS sequence (TR, 1500 ms; TE, 30 ms). The absolute concentration of main cerebellar metabolites was corrected for relaxation time effects. Different noise and line broadening conditions were considered and simulated in the spectral processing in order to evaluate the effect of spectral quality on the concentration estimates.
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Comparative Study
Cortex-based independent component analysis of fMRI time series.
The cerebral cortex is the main target of analysis in many functional magnetic resonance imaging (fMRI) studies. Since only about 20% of the voxels of a typical fMRI data set lie within the cortex, statistical analysis can be restricted to the subset of the voxels obtained after cortex segmentation. While such restriction does not influence conventional univariate statistical tests, it may have a substantial effect on the performance of multivariate methods. ⋯ A comparison between cbICA and conventional hypothesis-driven statistical methods shows that cortical surface maps and component TCs blindly obtained with cbICA reliably reflect task-related spatiotemporal activation patterns. Furthermore, the advantages of using cbICA when the specification of a temporal model of the expected hemodynamic response is not straightforward are illustrated and discussed. A comparison between cbICA and anatomically unconstrained ICA reveals that--beside reducing computational demand--the cortex-based approach improves the fitting of the ICA model in the gray matter voxels, the separation of cortical components and the estimation of their TCs, particularly in the case of fMRI data sets with a complex spatiotemporal statistical structure.
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In the present paper, for the first time, the feasibility to detect primary magnetic field changes caused by neuronal activity in vivo by spin-echo (SE) magnetic resonance imaging (MRI) is investigated. The detection of effects more directly linked to brain activity than secondary hemodynamic-metabolic changes would enable the study of brain function with improved specificity. However, the detection of neuronal currents by MRI is hampered by such accompanying hemodynamic changes. ⋯ At this aim, we propose the combined use of visual evoked potential (VEP) recordings and BOLD-fMRI measurements prior to SE MRI scanning. Moreover, we exemplify by theory and experimentation how the control of artefactual signal changes due to BOLD and movement effects may be further improved by the experimental design. Finally, results from a pilot study using the proposed combination of VEP recordings and MRI techniques are reported, suggesting the feasibility of this method.