Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis

Jörn Anemüller*, Jeng Ren Duann, Terrence J. Sejnowski, Scott Makeig

*Corresponding author for this work

Research output: Contribution to journalArticle

19 Scopus citations

Abstract

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatio-temporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10 Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.

Original languageEnglish
Pages (from-to)1502-1512
Number of pages11
JournalNeurocomputing
Volume69
Issue number13-15
DOIs
StatePublished - Aug 2006

Keywords

  • Biomedical signal analysis
  • Complex independent component analysis (complex ICA)
  • Convolution model
  • Functional magnetic resonance imaging (fMRI)
  • Hemodynamic response
  • Primary visual cortex (VI)
  • Spatio-temporal dynamics
  • Statistical signal processing

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