Joint independent component analysis for simultaneous EEG–fMRI: Principle and simulation

An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD–fMRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible t...

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Bibliographic Details
Published inInternational journal of psychophysiology Vol. 67; no. 3; pp. 212 - 221
Main Authors Moosmann, Matthias, Eichele, Tom, Nordby, Helge, Hugdahl, Kenneth, Calhoun, Vince D.
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.03.2008
Subjects
Algorithms
Brain Mapping - instrumentation
Brain Mapping - methods
Cerebral Cortex - blood supply
Cerebral Cortex - metabolism
Cerebrovascular Circulation
Computer Simulation
Data fusion
EEG-fMRI
Electroencephalography - instrumentation
ERP
Humans
ICA
Magnetic Resonance Imaging - instrumentation
Modelling
Oxygen - metabolism
Principal Component Analysis
Reproducibility of Results
Signal Processing, Computer-Assisted
Simulation
Data fusion
ERP
Modelling
EEG-fMRI
Simulation
ICA
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ISSN0167-8760
1872-7697
DOI10.1016/j.ijpsycho.2007.05.016

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Summary:An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD–fMRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible to identify features of latent neural sources whose trial-to-trial dynamics are jointly reflected in both modalities. We present a joint independent component analysis (jICA) model for analysis of simultaneous single trial EEG–fMRI measurements from multiple subjects. We outline the general idea underlying the jICA approach and present results from simulated data under realistic noise conditions. Our results indicate that this approach is a feasible and physiologically plausible data-driven way to achieve spatiotemporal mapping of event related responses in the human brain.
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MM and TE contributed equally to this work
ISSN:0167-8760
1872-7697
DOI:10.1016/j.ijpsycho.2007.05.016