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

Xia Wu*, Li Yao, Zhi Ying Long, Jie Lu, Kun Cheng Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationNeural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
PublisherSpringer Verlag
Pages175-182
Number of pages8
ISBN (Print)3540464794, 9783540464792
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
Duration: 3 Oct 20066 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4232 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Neural Information Processing, ICONIP 2006
Country/TerritoryChina
CityHong Kong
Period3/10/066/10/06

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