Abbas Babajani-Feremi - the Image Analysis Lab., Radiology Department, Henry Ford Hospital, Detroit.
Hamid Soltanian-Zadeh - Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran. Image Analysis Lab., Radiology Department, Henry Ford Hospital, Detroit,
John E. Moran - Neuromagnetism Lab., Neurology Department, Henry Ford Hospital, Detroit

Main objective of this paper is to present methods and results for estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) model. We use real auditory common MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data was gathered at different times but the stimulus profile was the same for both techniques. We use independent component analysis (ICA) to extract temporal information 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. Goodness of fit of the real data to our model confirms ability of the proposed model to simulate realistic datasets for evaluation of integrated fMRI/MEG analysis methods. It also makes it possible to use the proposed model in real applications.