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、分析和评估估计位置的方法， 皮层神经元群的范围和动态行为 事件相关脑电(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 它们能够定位皮质中的局灶性神经元群体。我们还有 发展了基于边界元方法的快速、准确的正演模型 (BEMS)这些发展体现在交互软件包中， 集思广益，现已向研究界提供。对我们的评估 方法和软件一直基于理论和蒙特卡罗研究， 利用在该项目下开发的人-头骨模型进行的研究，以及 应用于与事件相关的EIMEG数据。一个高分辨率的皮质表面， 以及用于边界元计算的头骨、头皮和大脑表面，使用 应用于解剖磁共振成像的一系列自动化处理步骤 包含在第二个软件包BrainSuite中。对于建议的项目 在此期间，我们计划继续研究E/MEG的理论基础 源估计，目标是更好地了解潜力和 医疗模式的局限性。我们的理论研究将导致 正演和反演方法的改进，更重要的是，更好的 了解这些估计中隐含的不确定性。在诗句中 方法将基于正则化的信号子空间局部化的使用 可以代表分布的神经元群体的多极源。 通过将多极源重新映射到皮质，将获得皮质图像。我们 将开发用于直接从 测量数据和估计来源。这些方法将基于 Bootstrap方法在统计学中的应用及插件逼近Cramer 拉奥的下限。皮质重新映射方法将可选地允许使用 作为关于可能来源位置的先验信息。一个 将开发一种新的方法来选择RAW中的事件相关组件 用于刺激锁定平均模糊信号源的情况下的数据 高度可变的延迟。改进的正演模型将基于有限元 元素法(FEMS)在受试者精确分割磁共振成像中的应用 头。对于无法获得核磁共振成像的受试者，我们将开发一种通用的 基于边界元或有限元的头部模型在平均翘曲头部中的应用 数字化头皮地标。评估将基于继续进行 理论、模拟和体模研究。这些技术发展将 整合到我们的BrainStorm和BrainSuite软件包中 将在项目的整个生命周期内继续维护和加强。有限 使用功能磁共振成像、脑磁共振仪和脑电图仪对人体运动功能进行的研究计划在此进行。 这些方法在功能映射和功能映射中的更广泛应用 我们的合作者将通过使用我们的软件来实现癫痫 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.