Blind source separation for group fMRI signals using a new independent component analysis algorithm

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

Research output: Contribution to journalArticle

Abstract

Independent component analysis (ICA) has been used effectively for processing the functional magnetic resonance imaging (fMRI) data, but usually the data come from one subject. To process the signals from a group of subjects, an extended independent component analysis method, Group ICA is proposed. The results show that this method can reduce the data and receive the statistical result fast. In the processing, an independent component analysis method named new fixed-point is used, and the results show that the new method is superior to the FastICA on the accuracy of estimating the temporal dynamics of activations.

Original languageEnglish
Pages (from-to)773-776
Number of pages4
JournalDalian Ligong Daxue Xuebao/Journal of Dalian University of Technology
Volume47
Issue number5
StatePublished - Sep 2007

Keywords

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

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