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 profile 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 fit 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.
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Acknowledgements
The authors thank Mostafa Ghannad-Rezaie for his help with the fMRI and MEG experiments as well as useful discussions. The authors would greatly appreciate Dr. Micah Murray as well as reviewers of the paper for their useful comments. This work was supported by grants from the University of Tehran, Tehran, Iran, and National Institutes of Health (NIH grant R01EB002450), United States and also supported by NIH/NINDS Grant R01-NS30914.
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Babajani-Feremi, A., Soltanian-Zadeh, H. & Moran, J.E. Integrated MEG/fMRI Model Validated Using Real Auditory Data. Brain Topogr 21, 61–74 (2008). https://doi.org/10.1007/s10548-008-0056-3
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DOI: https://doi.org/10.1007/s10548-008-0056-3