Functional connectivity in the resting brain: an analysis based on ICA

Authors:
Xia Wu;Li Yao;Zhi-ying Long;Jie Lu;Kun-cheng Li
Affiliations:
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China;State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China;Center for Human Development, University of California at San Diego, CA;Department of Radiology, Xuan Wu Hospital of Beijing, Beijing, China;Department of Radiology, Xuan Wu Hospital of Beijing, Beijing, China
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

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Abstract

The functional connectivity of the resting state, or default mode, of the human brain has been a research focus, because it is reportedly altered in many neurological and psychiatric disorders. Among the methods to assess the functional connectivity of the resting brain, independent component analysis (ICA) has been very useful. But how to choose the optimal number of separated components and the best-fit component of default mode network are still problems left. In this paper, we used three different numbers of independent components to separate the fMRI data of resting brain and three criterions to choose the best-fit component. Furthermore, we proposed a new approach to get the best-fit component. The result of the new approach is consistent with the default-mode network.