Multivariate analysis of fMRI group data using independent vector analysis

Jong-Hwan Lee, Te W. Lee, Ferenc A. Jolesz, Seung Schik Yoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

A multivariate non-parametric approach for the processing of fMRI group data is important to address variability of hemodynamic responses across subjects, sessions, and brain regions. Independent component analysis (ICA) has a limitation during the inference of group effects due to a permutation problem of independent components. In order to address this limitation, we present an independent vector analysis (IVA) for the processing of fMRI group data. Compared to the ICA, the IVA offers an extra dimension for the dependent parameters, which can be assigned for the automated grouping of dependent activation patterns across subjects. The IVA was applied to the fMRI data obtained from 12 subjects performing a left-hand motor task. In comparison with conventional univariate methods, IVA successfully characterized the group-representative activation time courses (as component vectors) without extra data processing schemes to circumvent the permutation problem, while effectively detecting the areas with hemodynamic responses deviating from canonical, model-driven ones.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages633-640
Number of pages8
Volume4666 LNCS
Publication statusPublished - 2007 Dec 1
Externally publishedYes
Event7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007 - London, United Kingdom
Duration: 2007 Sep 92007 Sep 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4666 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007
CountryUnited Kingdom
CityLondon
Period07/9/907/9/12

Fingerprint

Functional Magnetic Resonance Imaging
Multivariate Analysis
Magnetic Resonance Imaging
Hemodynamics
Independent component analysis
Independent Component Analysis
Activation
Permutation
Chemical activation
Hand
Canonical Model
Dependent
Extra Dimensions
Processing
Grouping
Brain
Univariate

Keywords

  • fMRI
  • Group study
  • Independent vector analysis
  • Multivariate analysis
  • Neuroimaging

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Lee, J-H., Lee, T. W., Jolesz, F. A., & Yoo, S. S. (2007). Multivariate analysis of fMRI group data using independent vector analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 633-640). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4666 LNCS).

Multivariate analysis of fMRI group data using independent vector analysis. / Lee, Jong-Hwan; Lee, Te W.; Jolesz, Ferenc A.; Yoo, Seung Schik.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS 2007. p. 633-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4666 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, J-H, Lee, TW, Jolesz, FA & Yoo, SS 2007, Multivariate analysis of fMRI group data using independent vector analysis. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4666 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4666 LNCS, pp. 633-640, 7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007, London, United Kingdom, 07/9/9.
Lee J-H, Lee TW, Jolesz FA, Yoo SS. Multivariate analysis of fMRI group data using independent vector analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS. 2007. p. 633-640. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Lee, Jong-Hwan ; Lee, Te W. ; Jolesz, Ferenc A. ; Yoo, Seung Schik. / Multivariate analysis of fMRI group data using independent vector analysis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS 2007. pp. 633-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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