A method for comparing group fMRI data using independent component analysis: application to visual, motor and visuomotor tasks

by: Vince D Calhoun, Tulay Adali, James J Pekar

Magnetic Resonance Imaging, Vol. 22, No. 9. (November 2004), pp. 1181-1191.

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Abstract

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.

@article{citeulike:1088311, abstract = {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.}, author = {Calhoun, Vince D. and Adali, Tulay and Pekar, James J. }, citeulike-article-id = {1088311}, doi = {http://dx.doi.org/10.1016/j.mri.2004.09.004}, journal = {Magnetic Resonance Imaging}, keywords = {fmri, fnak, group, ica}, month = {November}, number = {9}, pages = {1181--1191}, posted-at = {2007-06-22 16:56:02}, priority = {5}, title = {A method for comparing group fMRI data using independent component analysis: application to visual, motor and visuomotor tasks}, url = {http://dx.doi.org/10.1016/j.mri.2004.09.004}, volume = {22}, year = {2004} }

RIS record

TY - JOUR ID - citeulike:1088311 L3 - citeulike-article-id:1088311 TI - A method for comparing group fMRI data using independent component analysis: application to visual, motor and visuomotor tasks JF - Magnetic Resonance Imaging VL - 22 IS - 9 SP - 1181 EP - 1191 N2 - 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. KW - fmri KW - fnak KW - group KW - ica AU - Calhoun, Vince AU - Adali, Tulay AU - Pekar, James PY - 2004/11// UR - http://dx.doi.org/10.1016/j.mri.2004.09.004 ER -

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