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

  • Authors:

  • Jörn Anemüller;Jeng-Ren Duann;Terrence J. Sejnowski;Scott Makeig

  • Affiliations:

  • Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA and Computational Neurobiology Laboratory, The Salk Institute ...;Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA;Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA and Computational Neurobiology Laboratory, The Salk Institute ...;Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA

  • Venue:
  • Neurocomputing
  • Year:
  • 2006

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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 0.10Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.