Spatio-Temporal MEG and EEG Source Estimation

描述（申请人提供）：本项目的目的是开发， 实施、分析和评估估算位置的方法， 程度和动态行为的皮质神经元群体，引起 事件相关脑电图（EEG）和脑磁图（MEG） （E/MEG）信号。在这个项目的生命周期中，我们开发了贝叶斯 皮质成像方法和多极源定位方法，两者都是 其能够定位皮质中的局灶性神经元群体。我们还 开发了基于边界元法的快速、精确的正演模型 （BEM）。这些发展体现在一个交互式软件包中， BrainStorm，现在可供研究社区使用。评估我们的 方法和软件基于理论和蒙特卡罗研究， 使用在该项目下开发的人类头骨模型进行研究， 事件相关的EIMEG数据的应用。一个高分辨率的皮层表面， 以及用于BEM计算的头骨、头皮和大脑表面，使用 应用于解剖MRI的一系列自动处理步骤， 包含在第二个软件包BrainSuite中。就拟议工程计划 在此期间，我们计划继续研究E/MEG的理论基础 源估计，目的是更好地了解潜力， 模式的局限性。我们的理论研究将导致 改进了正向和反向方法，重要的是， 理解这些估计中隐含的不确定性。用韵文 方法将基于正则化信号子空间定位的使用， 多极源，可以代表分布式神经元群体。 将通过将多极源重新映射到皮质来获得皮质图像。我们 将开发工具，用于直接从 测量数据和估计来源。这些方法将基于 统计学中的自举方法和Cramer插入式近似的使用 Rao下界。皮质重映射方法将可选地允许使用 作为可能的源位置的先验信息。一 提出了一种新的事件相关成分选择方法， 在刺激锁定平均值掩盖源的情况下使用的数据， 高度可变的延迟。改进的正演模型将基于有限 元素方法（FEM）应用于受试者的准确分割MRI 头对于MRI不可用的受试者，我们将开发一种通用的 基于BEM或FEM的头部模型，应用于扭曲为系列的平均头部 数字化的头皮标志评价将基于持续的 理论、模拟和体模研究。这些技术发展将 被纳入我们的BrainStorm和BrainSuite软件包， 将在项目的生命周期内继续保持和增强。有限 为此，计划使用功能磁共振成像、脑磁图和脑电图对人体运动功能进行研究 项目;这些方法在功能绘图和 癫痫将通过我们的合作者使用我们的软件来实现， 其他注册用户。

DESCRIPTION (Provided by Applicant): The purpose of this project is to develop, implement, analyze and evaluate methodologies for estimating the location, extent, and dynamic behavior of cortical neuronal populations that give rise to event-related electroencephalographic (EEG) and magnetoencephalographic (MEG) (E/MEG) signals. During the lifetime of this project we have developed Bayesian cortical imaging methods and multipolar source localization methods, both of which are able to localize focal neuronal populations in cortex. We have also developed fast, accurate forward models based on boundary element methods (BEMs). These developments are embodied in an interactive software package, BrainStorm, which is now available to the research community. Evaluation of our methods and software has been based on theoretical and Monte Carlo studies, studies using a human-skull phantom developed under this project, and applications to event-related EIMEG data. A high-resolution cortical surface, and skull, scalp, and brain surfaces for BEM calculations, are found using a series of automated processing steps applied to anatomical MRIs which are embodied in a second software package BrainSuite. For the proposed project period we plan to continue our investigations of the theoretical basis of E/MEG source estimation with the goal of better understanding the potentials and limitations of the modality. Our theoretical investigations will lead to improvements in forward and inverse methods and, importantly, a better understanding of the uncertainties implicit in these estimates. In verse methods will be based on the use of regularized signal-subspace localization of multipolar sources that can represent distributed neuronal populations. Cortical images will be obtained by re-mapping multipolar sources to cortex. We will develop tools for estimating location uncertainty directly from the measured data and estimated sources. These methods will be based on the bootstrap method in statistics and use of plug-in approximations to the Cramer Rao lower bounds. The cortical remapping methods will optionally allow the use of fMRI activation sites as prior information on possible source locations. A novel method will be developed for selection of event-related components in raw data for use in cases where stimulus-locked averaging obscures sources with highly variable latency. Improved forward models will be based on finite element methods (FEMs) applied to accurately segmented MRIs of the subjects head. For subjects for whom MRIs are not available, we will develop a generic head model based on BEM or FEM applied to an averaged head warped to a series of digitized scalp landmarks. Evaluation will be based on continued theoretical, simulation, and phantom studies. These technical developments will be incorporated in our BrainStorm and BrainSuite software packages which we will continue to maintain and enhance over the life of the project. Limited human studies of motor function using fMRI, MEG and EEG are planned for this project; broader applications of these methods in functional mapping and epilepsy will be realized through use of our software by our collaborators and other registered users.