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Title:Neural networks approach to clustering of activity in fMRI Data
Authors: M Voultsidou ; S Dodel ; Michael Herrmann
Date: 2005
Publication Title:IEEE Transactions in Medical Imaging
Publication Type:Journal Article Publication Status:Published
Volume No:12:8 Page Nos:987-996
DOI:10.1109/TMI.2005.850542 ISBN/ISSN:0278-0062
Clusters of correlated activity in functional magnetic resonance imaging data can identify regions of interest and indicate interacting brain areas. Because the extraction of clusters is computationally complex, we apply an approximate method which is based on artificial neural networks. It allows one to find clusters of various degrees of connectivity ranging between the two extreme cases of cliques and connectivity components. We propose a criterion which allows to evaluate the relevanc of such structures based on the robustness with respect to parameter variations. Exploiting the intracluster correlations, we can show that regions of substantial correlation with an external stimulus can be unambiguously separated from other activity.
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Bibtex format
author = { M Voultsidou and S Dodel and Michael Herrmann },
title = {Neural networks approach to clustering of activity in fMRI Data},
journal = {IEEE Transactions in Medical Imaging},
year = 2005,
volume = {12:8},
pages = {987-996},
doi = {10.1109/TMI.2005.850542},

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