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Brain Topogr (2008) 21:6174 DOI 10.1007/s10548-008-0056-3
ORIGINAL PAPER
Integrated MEG/fMRI Model Validated Using Real Auditory Data
Abbas Babajani-Feremi Hamid Soltanian-Zadeh John E. Moran
Accepted: 20 April 2008 / Published online: 14 May 2008 Springer Science+Business Media, LLC 2008
Abstract The main objective of this paper is to present methods and results for the estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) model. We use real auditory MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data were acquired at different times, but the stimulus prole was the same for both techniques. We use independent component analysis (ICA) to extract activation-related signal from the MEG data. The stimulus-correlated ICA component is used to estimate MEG parameters of the model. The temporal and spatial information of the fMRI datasets are used to estimate fMRI parameters of the model. The estimated parameters have reasonable means and standard deviations for all subjects. Goodness of t of the real data to our model shows the possibility of using the proposed model to simulate realistic datasets for evaluation of integrated MEG/fMRI analysis methods.
Keywords Electroencephalography (EEG) Magnetoencephalography (MEG) functional magnetic resonance imaging (fMRI)
Integrated modeling
Independent component analysis (ICA)
Introduction
Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have complementary spatial and temporal resolutions. fMRI has good spatial resolution, but poor temporal resolution due to the limited rate of change in the hemodynamic response. On the other hand, MEG has good temporal resolution, but its spatial resolution is poor due to the inverse problem being ill-posed (Hamalainen et al. 1993). Integrated MEG/fMRI analysis should improve the overall spatiotemporal resolution of the results based on the fact that MEG and fMRI are different views of a common source (neural activity) (Dale and Halgeren 2001; Dale et al. 2000; Horwitz and Poeppel 2002; Korvenoja et al. 2001; Liu et al. 1998, 2006; Martinez-Montes et al. 2004).
Although MEG and fMRI signals originate from common sources (neural activities), there may be differences between the spatiotemporal responses of the two techniques (Nunez and Silberstein 2000). An integrated bottom-up model based on physiological principles can illustrate the relationship between MEG and fMRI. However, there are limited works about MEG,...