A method for comparing group fMRI data using independent component analysis: application to visual, motor and visuomotor tasks
A method for comparing group fMRI data using independent component analysis: application to visual, motor and visuomotor tasks
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DOI：
10.1016/j.mri.2004.09.004
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发表时间：
2004-11-01
影响因子：
2.5
通讯作者：
Pekar, JJ
中科院分区：
文献类型：
--
作者：
Calhoun, VD;Adali, T;Pekar, JJ
独立成分分析（伊卡）是一种将fMRI数据分解为空间独立的图和时间过程的方法。我们最近提出了一种伊卡的多学科数据的方法，在目前的论文中，提出了一个扩展允许伊卡组比较。该方法适用于旨在刺激视觉皮质、运动皮质或视觉和运动皮质的实验数据。提出了几个组间和组内指标，用于评估组伊卡数据比较的组件的效用。所提出的方法可能被证明是有用的，在回答需要多组比较时，需要一个灵活的建模方法的问题。(C)2004年爱思唯尔公司All rights reserved.
Independent component analysis (ICA) is an approach for decomposing fMRI data into spatially independent maps and time courses. We have recently proposed a method for ICA of multisubject data; in the current paper, an extension is proposed for allowing ICA group comparisons. This method is applied to data from experiments designed to stimulate visual cortex, motor cortex or both visual and motor cortices. Several intergroup and intragroup metrics are proposed for assessing the utility of the components for comparisons of group ICA data. The proposed method may prove to be useful in answering questions requiring multigroup comparisons when a flexible modeling approach is desired. (C) 2004 Elsevier Inc. All rights reserved.