Semi-blind ICA of FMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis

V. Calhoun, T. Adali

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

Abstract

Independent component analysis (ICA), a data-driven approach utilizing high-order statistical moments to find maximally independent sources, has found fruitful application in functional magnetic resonance imaging (fMRI). ICA, being a blind source separation technique, does not require any explicit constraints upon the fMRI time courses. In some cases, such as for the analysis of a rapid eventrelated paradigm, it would be useful to incorporate paradigm information into the ICA analysis in a flexible way. In this paper, we present an approach for constrained or semi-blind ICA (sbICA) analysis of fMRI data. We demonstrate the performance of our approach using simulations and fMRI data of an auditory oddball paradigm. Simulation results suggest that 1) a regression approach slightly outperforms ICA when prior information is accurate and ICA outperforms the general linear modeling (GLM) approach when prior information is not completely accurate, 2) prior information improves the robustness of ICA in the presence of noise, and 3) and ICA analysis using prior information with weak constraints can outperform a regression approach when the prior information is not completely accurate.

Original languageEnglish (US)
Title of host publicationMachine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop
EditorsA. Barros, J. Principe, J. Larsen, T. Adali, S. Douglas
Pages443-452
Number of pages10
StatePublished - 2004
Externally publishedYes
EventMachine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop - Sao Luis, Brazil
Duration: Sep 29 2004Oct 1 2004

Publication series

NameMachine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop

Other

OtherMachine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop
CountryBrazil
CitySao Luis
Period9/29/0410/1/04

ASJC Scopus subject areas

  • Engineering(all)

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