Basic and clinical studies on cerebral circulatory fluctuations using magnetic resonance imaging and near infrared spectroscopy

点击翻译按钮获取中文摘要

1.Cerebral circulatory fluctuations in rat brain : We studied signal fluctuations in rat brain by echo-planar MRI combined with blood pressure and capnometric measurements. Globally (the bilateral parietal cortex, hippocampus and basal ganglia) synchronized low-frequency (near 0.1 Hz) signal fluctuations were found in isoflurane-anesthetized rats. Neither changes in blood pressure nor those in expiratory CO_2 concentration were related to MR signal changes in such frequencies. A significant relation was found between spectral power of low-frequency signal fluctuations and sympathetic nervous activity determined by blood pressure variability during deep anesthesia. These findings suggest that sympathetic nervous activity may play a part in synchronous low-frequency fluctuations in cerebral circulation.2.Method for separating and extracting information on physiological functions : Signal components of different physiological origins are accurately separated and information about each com … More ponent is provided, even when a signal change related to local neuronal activity and signal fluctuations related to other physiological origins coexist. It is achieved by a method for separating and extracting information on physiological functions, wherein a mathematical model is built to describe an input/output relationship for functional measurement data on a pixel or channel basis, and information on signal components of various physiological origins is separated and extracted from the functional measurement data.3.A dynamic system model-based technique for functional MRI data analysis : We applied a dynamic system model-based technique to human visual fMRI experiments to determine the validity and feasibility of this technique for fMRI data analysis. Local signal changes were appropriately predicted by autoregressive model with two exogenous inputs, a visual stimulation paradigm and a global reference signal. A significant linear relationship was found between model static gain based on the dynamic system modeling and beta coefficient based on a general linear model analysis for active voxels in the primary visual cortex. This dynamic system model-based technique is sufficiently accurate and feasible for use in extracting signal changes related to brain activation inputsfrom measured signals with physiological fluctuations. Less