Independent component analysis algorithm for blind separation of fMRI signals

Li Li Pan, Zhen Wei Shi, Huan Wen Tang, Yi Yuan Tang, Wei Wei Zhang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

An optimization model for independent component analysis (ICA) is built. A new gradient algorithm based on the model is presented, which is called Orth-ExtBS algorithm. This algorithm combines the advantages of the FastICA and ExtBS algorithms, which is easy to use in simple form and is able to separate blindly mixed signals with sub-Gaussian and super-Gaussian source distributions. The accuracy of the Orth-ExtBS algorithm is high and its convergence speed is fast. Applying the Orth-ExtBS algorithm and two other algorithms (FastICA and ExtBS) to fMRI data, the results show that the new algorithm is superior to the other two on accuracy of estimating the temporal dynamics of activations by comparison.

Original languageEnglish
Pages (from-to)607-611
Number of pages5
JournalDalian Ligong Daxue Xuebao/Journal of Dalian University of Technology
Volume45
Issue number4
StatePublished - Jul 2005

Keywords

  • Blind source separation
  • Functional magnetic resonance imaging
  • Gradient algorithm
  • Independent component analysis

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