SPATIOTEMPORAL IMAGING INTEGRATING ELECTROMAGNETIC, ANATOMICAL, HEMODYNAMIC DATA

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 项目3的总体目标是开发人类时空成像的方法， 大脑功能，由实验激发并验证。具体来说，我们将扩大 在解剖学和功能上受约束的MEG/EEG源模型到外部结构 皮层使用项目1中获得的准确解剖信息和生理信息， 关于合理的源强度的信息，我们将构建解剖结构 组件和生理元素的源模型，其中涵盖了大脑 皮质的其他结构，包括海马和基底神经节。 通过计算机模拟和实验，我们将研究检测和 估计皮质外结构的活动。第二，我们将继续努力， 开发新的逆模型，使用血液动力学和电磁数据， 合取我们将用实验来探索电磁场和 (MEG/EEG）和血流动力学（fMRI/DOT）数据作为组合活动估计的基础 框架.第三，我们将扩展计算功能连接性度量的方法， 非固定数据，并将制定适当的统计处理的连接 个体试验和受试者之间的信息。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The overall goal of Project 3 is to develop methods for spatiotemporal imaging of human brain function, motivated by and validated with experiments. Specifically, we will extend anatomically and functionally constrained MEG/EEG source models to structures outside the cortex. Using the accurate anatomical information obtained in Project 1 and physiological information regarding plausible source strengths we will construct the anatomical components and physiological elements of a source model which covers both the cerebral cortex other structures, including the hippocampus and the basal ganglia. With computer simulations and experiments we will study the feasibility of detecting and estimating activity in extracortical structures. Second, we will continue our work on developing new inverse models which use the hemodynamic and electromagnetic data in conjunction. We will use experiments probing the relationship between electromagnetic (MEG/EEG) and hemodynamic (fMRI/DOT) data as a basis for a combined activity estimation framework. Third, we will extend the methods to calculate functional connectivity metrics to non-stationary data and will develop proper statistical treatment of the connectivity information across individual trials and across subjects.