Functional Connectivity in the Resting Brain: An Analysis Based on ICA

  • Xia Wu
  • Li Yao
  • Zhi-ying Long
  • Jie Lu
  • Kun-cheng Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4232)


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.


Functional Connectivity Independent Component Analysis fMRI Data Independent Component Analysis Posterior Cingulated Cortex 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xia Wu
    • 1
  • Li Yao
    • 1
    • 2
  • Zhi-ying Long
    • 3
  • Jie Lu
    • 4
  • Kun-cheng Li
    • 4
  1. 1.State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
  2. 2.College of Information and Computer TechnologyBeijing Normal UniversityBeijingChina
  3. 3.Center for Human DevelopmentUniversity of California at San DiegoUSA
  4. 4.Department of RadiologyXuan Wu Hospital of BeijingBeijingChina

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