课题基金 / 基金详情

FMRI task design and statistical analysis software

FMRI task design and statistical analysis software
FMRI任务设计和统计分析软件
批准号:
6338416
负责人:
Eric Halgren
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-01 至 2002-02-28

项目摘要

项目成果

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中文摘要
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英文摘要
DESCRIPTION (Provided by Applicant): The overall goal of the project is to develop a new generation of functional MRI design and analysis software. The proposed software is designed to lead to an order of magnitude improvement over current methods in the estimation and detection of fMRI activation. The software will generate optimal rapid-presentation event-related (RPER) fMRI designs. Such designs allow for new classes of functional imaging experiments and permit comparisons between fMRI and traditional electrophysiological or behavioral studies. The software will also incorporate methods to greatly increase the statistical power and reliability for detecting task-related physiological responses with fMRl, including the use of correlated noise compensation, and optimal spatial filtering. These methods will be applicable to both blocked and event-related paradigms. While the software will be usable and available in a stand-alone version, it will also be designed to be interoperable with our suite of structural MRI software tools. In particular, the results will be able to be presented on flattened and inflated cortical sw-laces for superior visualization. The area of multi-modal brain imaging (fMRI, EEG, MEG) will be greatly advanced by supporting rapid-presentation event-related designs and cortical surface formats within a single computational platform. PROPOSED COMMERCIAL APPLICATION: The proposed product would be of interest to researchers using functional MRI, i.e., over 1000 worldwide and glowing rapidly. The proposed software will increase the functionality of fMRI by at least 20% but we propose to sell it for only about 0.1% of the fMRI equipment cost. Put another way, the proposed software could halve the number of fMRI sessions needed to achieve a given level of significance, and thus would pay for itself after about 10 sessions.
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