On complex infomax applied to functional MRI data

V. Calhoun, T. Adali, G. Pearlson, J. Pekar

Research output: Contribution to journalConference articlepeer-review

11 Scopus citations


Functional magnetic resonance imaging (fMRI) is a technique which produces complex data; however the vast majority of functional magnetic resonance imaging analyses utilize only magnitude images. In this paper, we derive a complex-valued independent component analysis (ICA) algorithm using the infomax approach which we then apply to fMRI analysis. Theoretical and empirical results demonstrate an improved sensitivity to functional changes when utilizing the complex data. Additionally, the complex infomax algorithm developed provides a powerful method for exploratory analysis of fMRI data.

Original languageEnglish (US)
Pages (from-to)I/1009-I/1012
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2002
Event2002 IEEE International Conference on Acustics, Speech, and Signal Processing - Orlando, FL, United States
Duration: May 13 2002May 17 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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