Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis
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 0.10Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.
spatio-temporal dynamics functional magnetic resonance imaging (fmri) complex independent component analysis (complex ica) convolution model hemodynamic response primary visual cortex (vi) biomedical signal analysis statistical signal processing