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

1.大鼠脑内的脑循环波动：我们通过回波平面MRI结合血压和二氧化碳测量研究了大鼠脑内的信号波动。在异氟烷麻醉的大鼠中发现了全局（双侧顶叶皮层、海马和基底神经节）同步低频（近0.1 Hz）信号波动。血压和呼气CO_2浓度的变化与这些频率的MR信号变化无关。一个显着的关系被发现之间的频谱功率的低频信号波动和交感神经活动确定的血压变异性在深麻醉。这些结果表明，交感神经活动可能在脑循环的同步低频波动中起作用。2.分离和提取生理功能信息的方法：准确地分离出不同生理来源的信号成分， ...更多信息 即使当与局部神经元活动相关的信号变化和与其他生理起源相关的信号波动共存时，也提供了该分量。这是通过一种用于分离和提取关于生理功能的信息的方法来实现的，其中，建立数学模型以描述基于像素或通道的功能测量数据的输入/输出关系，并且从功能测量数据中分离和提取关于各种生理来源的信号分量的信息。3.一种用于功能MRI数据分析的基于动态系统模型的技术：我们应用动态系统模型为基础的技术，人类视觉功能磁共振成像实验，以确定这种技术的有效性和可行性的功能磁共振成像数据分析。局部信号的变化进行了适当的预测自回归模型与两个外源性输入，视觉刺激范式和全球参考信号。一个显着的线性关系被发现之间的模型静态增益的基础上的动态系统建模和β系数的基础上的一般线性模型分析的活性体素在初级视皮层。这种基于动态系统模型的技术是足够准确和可行的，用于从具有生理波动的测量信号中提取与大脑激活输入相关的信号变化。少

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