Flexible complex ICA of FMRI data

Hualiang Li, Tülay Adali, Nicolle Correa, Pedro A. Rodriguez, Vince D. Calhoun

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

Abstract

Data-driven analysis methods, in particular independent component analysis (ICA) has proven quite useful for the analysis of functional magnetic imaging (fMRI) data. In addition, by enabling one to work in its native, complex form, complex-valued ICA algorithms provide better estimation performance compared to the traditional approach that uses only the magnitude data. In the complex domain, circularity has been a common assumption even though most data acquisition methods collect fMRI data that end up being noncircular when saved in complex form. In this paper, we show that a complex ICA approach that does not assume circularity and also adapts to the source density is the more desirable one for performing ICA of complex fMRI data. We show that by adaptively matching the underlying fMRI density model, the analysis performance can be improved in terms of both the estimation of the task-related time courses and in the spatial activation.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages2050-2053
Number of pages4
DOIs
StatePublished - Nov 8 2010
Externally publishedYes
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

Keywords

  • Complex analysis
  • ICA
  • Independent component analysis
  • fMRI

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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