SPATIOTEMPORAL IMAGING INTEGRATING ELECTROMAGNETIC, ANATOMICAL, HEMODYNAMIC DATA

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 项目3的总体目标是开发人脑功能的时空成像方法，其动机是 并通过实验进行了验证。具体地说，我们将扩展解剖和功能受限的脑磁图/脑电图源模型 到大脑皮层外的结构。使用项目1中获得的准确解剖信息和生理信息 关于可信来源强度的信息，我们将构建解剖组件和生理元素 这是一个涵盖大脑皮层和其他结构的源模型，包括海马体和基底节。 通过计算机模拟和实验，我们将研究检测和估计皮层外活动的可行性。 结构。第二，我们将继续我们的工作，开发新的逆模型，使用血流动力学和 电磁数据结合在一起。我们将用实验来探索电磁与 脑磁图(MEG/EEG)和血流动力学(fMRI/DOT)数据作为综合活动评估框架的基础。第三，我们将 将计算功能连通性指标的方法扩展到非平稳数据，并将开发适当的统计 处理跨个体试验和跨受试者的连接信息。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. 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.