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fMRI Detection by Clustering Model Fitting Parameters

通过聚类模型拟合参数进行fMRI检测

基本信息

批准号：
7465350
负责人：
THOMAS M TALAVAGE
金额：
$ 7.11万
依托单位：
PURDUE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-08-01 至 2009-07-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): The project proposed herein will develop a flexible analytical framework for functional magnetic resonance imaging (fMRI) data that will identify multi-voxel regions of activation through statistical evaluation of hemodynamic response model fits to the observed blood-oxygenation level-dependent effect responses. The proposed framework will allow the incorporation of multiple hemodynamic response models that may be used to evaluate fMRI responses both on a single-trial and averaged (blocked) basis. In addition to an expected improvement in the identification of "true" fMRI activation, this framework is expected to be capable of reducing the background noise level in summary images by breaking from the tradition of analyzing each individual voxel for its statistical significance and subsequently grouping "significant" voxels into regions of activation. Finally, this framework will also allow us to identify regions that are co-activated, or at least exhibit similar temporal structure in response to the stimulation, independent of the amplitude of the individual responses, thus contributing a new tool to studies of functional connectivity. Aim: Develop a novel framework for fMRI data analysis that uses a priori knowledge of both the experimental paradigm and hemodynamic response to detect activation on a regional basis. Achievement of the specific aim of this proposal will provide a powerful tool that may greatly enhance the future results obtained by the functional MRI community. Development of an analytical procedure that focuses on (potentially disjoint) multi-voxel regions of interest as the fundamental activation unit to be detected will increase the probability of a detected voxel being a true detection, enhancing the usefulness of fMRI in furthering our understanding of both normal and disordered cortical activity.

描述(由申请人提供)：本文提出的项目将为功能磁共振成像(FMRI)数据开发一个灵活的分析框架，该框架将通过对符合观察到的血氧水平依赖效应反应的血流动力学响应模型的统计评估来识别多体素激活区域。建议的框架将允许合并多个血流动力学反应模型，这些模型可用于在单次试验和平均(阻断)基础上评估功能磁共振反应。除了在识别“真正的”fMRI激活方面的预期改进之外，该框架有望通过打破分析每个单独的体素的统计意义并随后将“重要的”体素分组为激活区域的传统，来降低汇总图像中的背景噪声水平。最后，这个框架还将使我们能够识别共同激活的区域，或者至少显示出与刺激反应类似的时间结构，而不依赖于单个反应的幅度，从而为功能连接的研究贡献了一个新的工具。目的：开发一种新的fMRI数据分析框架，该框架使用实验范式和血流动力学响应的先验知识来检测区域激活。这项提议的具体目标的实现将提供一个强大的工具，可以极大地提高功能磁共振学界未来取得的成果。开发一种分析程序，将重点放在(可能不相交的)感兴趣多体素区域作为要检测的基本激活单元，将增加检测到的体素是真正检测到的可能性，增强功能磁共振成像在进一步了解正常和无序皮质活动方面的有用性。