Coherence analysis of fMRI data

fMRI 数据的相干性分析

• 批准号: 6692297
• 负责人: FELICE T SUN
• 金额: $ 1.51万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-03-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6692297
• 关键词: brain electrical activity; brain imaging /visualization /scanning; brain mapping; central neural pathway /tract; clinical research; computer data analysis; electroencephalography; functional magnetic resonance imaging; human subject; magnetoencephalography; method development; neural information processing; predoctoral investigator

DESCRIPTION (provided by applicant): The goal of this project is to develop a generalized method for estimating functional connectivity between interacting brain regions using functional magnetic resonance imaging (fMRI) data. The development and validation of a generalized method for estimating functional connectivity using fMRI data will be addressed in the following steps. First, I present a bivariate analysis method using coherence as a measure of connectivity between regions. This method is similar to many of the current correlation methods, however functional connectivity in fMRI data using coherence has not been tested. Then, I will test the analysis method on fMRI data acquired while subjects perform a series of bimanual tasks. Bimanual tasks are chosen because the cortical motor system is well studied and basic theories of connectivity within the bilateral primary motor areas and supplementary motor areas exist, based on primate, lesion, EEG, MEG, and fMRI studies. Finally, the results for the new technique will be compared against the standard univariate approach as well as results from other brain imaging modalities.

描述（由申请人提供）： 该项目的目标是开发一种通用的方法，用于使用功能性磁共振成像（fMRI）数据来估计相互作用的大脑区域之间的功能连接。开发和验证的一个通用的方法来估计功能连接使用功能磁共振成像数据将在以下步骤中解决。首先，我提出了一个双变量分析方法，使用的连贯性作为衡量区域之间的连接。这种方法是类似于许多目前的相关性方法，但功能性连接的功能磁共振成像数据使用的一致性还没有被测试。然后，我将测试分析方法的功能磁共振成像数据采集时，受试者执行了一系列的双手任务。选择双手任务是因为皮质运动系统得到了很好的研究，并且基于灵长类动物、病变、EEG、MEG和fMRI研究，存在双侧主运动区和辅助运动区之间的连接的基本理论。最后，新技术的结果将与标准单变量方法以及其他脑成像模式的结果进行比较。