Comparison of temporal and spatial ica in fmri data analysis

Silke Dodel, J Michael Herrmann, Theo Geisel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Independent Component Analysis (ICA) has recently drawn attention also in analyzing data from functional Magnetic Resonance Imaging (fMRI). fMRI is a promis- ing method to determine noninvasively the spatial dis- tribution of brain activity in a given situation, e.g. in response to a given stimulus. ICA reflects the underly- ing statistically independent processes of the activity. We compare the results of applying both, temporal and spatial ICA, on the data of a motor task experi- ment. It turns out that none of the two ways is a priori superior over the other, so in order to get fuller insight into the activity distribution both should be applied and their implications be determined from the features of interest in the results.
Original languageEnglish
Title of host publicationProceedings of ICA2000, the Second International Conference on Independent Component Analysis and Signal Separation
Pages543-548
Number of pages6
Publication statusPublished - 2000

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