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

磁共振成像和近红外光谱对脑循环波动的基础和临床研究

• 批准号: 13670940
• 负责人: KAMBE Masayuki
• 金额: $ 1.34万
• 依托单位: Hamano Life Science Research Foundation (2002-2003)Tottori University (2001)
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2001
• 资助国家: 日本
• 起止时间: 2001 至 2003
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13670940/
• 关键词: cerebral circulation; brain function; magnetic resonance imaging; near infrared spectroscopy; physiological function; autonomic nervous system; parametric model; dynamic system model; 磁気共鳴影像法; スペクトル解析

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

1.大鼠脑循环波动：利用超声平面MRI结合血压和血糖测量，研究了大鼠脑循环信号波动。异氟醚麻醉大鼠的整体（双侧顶叶皮质、海马和基底节区）出现同步的低频（近0.1 Hz）信号波动。血压和呼气CO_2浓度的变化都与MR信号在这些频率上的变化无关。深麻醉时，低频信号波动的频谱功率与由血压变异性测定的交感神经活动有显著关系。这些发现表明，交感神经活动可能在脑循环的同步低频波动中起作用。生理功能信息的分离与提取方法：准确分离出不同生理来源的信号成分，并给出每个成分的信息，即使局部神经元活动相关的信号变化与其他生理来源相关的信号波动并存，也能提供更多的成分。该方法通过生理功能信息的分离与提取方法来实现，该方法以像素或通道为基础，建立数学模型来描述功能测量数据的输入/输出关系，并从功能测量数据中分离提取各种生理源的信号分量信息。基于动态系统模型的功能MRI数据分析技术：我们将基于动态系统模型的技术应用于人类视觉功能MRI实验，以确定该技术用于功能MRI数据分析的有效性和可行性。采用视觉刺激范式和全局参考信号两种外源输入的自回归模型对局部信号变化进行了预测。基于动态系统建模的模型静态增益与基于初级视觉皮层活动体素的一般线性模型分析的β系数之间存在显著的线性关系。这种基于动态系统模型的技术在从生理波动的测量信号中提取与脑激活输入相关的信号变化方面具有足够的准确性和可行性。少

项目成果

Kamba M, Sung Y-W, Ogawa S: "A dynamic system model-based technique for functional MRI data analysis"Neuroimage. In press. (2004)

Kamba M、Sung Y-W、Okawa S：“一种基于动态系统模型的功能性 MRI 数据分析技术”Neuroimage。

Kamba M, Sung Y-W, Ogawa S.: "A dynamic system model-based technique for functional MRI data analysis."Neuroimage. 22. 179-187 (2004)

Kamba M、Sung Y-W、Okawa S.：“一种基于动态系统模型的功能性 MRI 数据分析技术。”神经影像。

Kamba M, Sung Y-W, Ogawa S: "A dynamic system model-based technique for functional MRI data analysis"Neuroimage. 22. 179-187 (2004)

Kamba M、Sung Y-W、Okawa S：“一种基于动态系统模型的功能性 MRI 数据分析技术”Neuroimage。