Space-Time analysis of 4-dimensional data of the blood flow measurement in brains

大脑血流测量的 4 维数据的时空分析

• 批准号: 13650475
• 负责人: OZAKI Tohru
• 金额: $ 2.3万
• 依托单位: Institute of Statistical Mathematics
• 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 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13650475/
• 关键词: Hemodynamics; fMRI modeling; Spatial time series model; Innovation Approach; EEG modeling; Inverse Problem; Dynamic Inverse problem; Space-tine Kalman filter; 脳データ; 非線形; fMR1

Although fMRI data is time-dependent data, it has been analyzed by spatial statisticians without proper attention to the dynamic part. This is because the data is also spatial data at the same time and the statistical analysis has been done by specialists of spatial statistics in the early stage of the development. In the present study, we take a reversal approach, where we treat the data as a 140,000 dimensional time series and tried to find some causal structure in the data using the innovation approach in time series analysis. We also applied the same idea to the solution of inverse problem for EEG data using spatial Kalman filtering scheme. This provides us with a useful tool for dynamic extension of Inverse Solution of ill-posed problems.

虽然fMRI数据是时间相关的数据，但空间统计学家对其进行分析时却没有注意到动态部分。这是因为这些数据同时也是空间数据，并且在开发的早期阶段就由空间统计专家完成了统计分析。在本研究中，我们采用反转方法，将数据视为一个14万维的时间序列，并试图使用时间序列分析中的创新方法在数据中找到一些因果结构。我们还将同样的思想应用于利用空间卡尔曼滤波方案求解脑电数据的逆问题。这为病态问题逆解的动态扩展提供了一个有用的工具。

项目成果

Peng H., Ozaki T, et al.: "Modeling and control System with signal Dependant nonlinear dinamics"Proceedings of European Control Conference. 42-47 (2001)

Peng H.、Ozaki T 等人：“具有信号相关非线性动力学的建模和控制系统”欧洲控制会议论文集。

Takizawa Y, Fukasawa A: "Sampling and Band limitation of Nonstationary Time Signals"Advances in System Science, Measurement, Circult & control, "Electricall Computer Engineering Series". 533-537 (2001)

Takizawa Y、Fukasawa A：“非平稳时间信号的采样和频带限制”系统科学、测量、电路的进展

F.Miwakeishi, R.Ramirez-Pardon, P.Valdes-Sosa, T.Ozaki: "A comparison of non-linear non-parametric models for epilepsy data"Computers in Biology and Medicine. 31. 41-57 (2001)

F.Miwakeishi、R.Ramirez-Pardon、P.Valdes-Sosa、T.Ozaki：“癫痫数据非线性非参数模型的比较”生物学和医学计算机。

T.Ozaki, M.Iino: "An innovation approach to non-Gaussian time series analysis"Journal of Application and Probability. v.38A. 78-92 (2001)

T.Ozaki、M.Iino：“非高斯时间序列分析的创新方法”应用与概率杂志。

A.Galka, T.Ozaki: "Testing for Nonlinearity in High-Dimensional Time series from continuous Dynamics"physica. D158. 32-44 (2001)

A.Galka、T.Ozaki：“连续动力学中高维时间序列的非线性测试”物理学。