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MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data

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Abstract

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes (http://cobre.mrn.org/megsim/). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.

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Acknowledgment

This work was funded by NIH grants R21MH080141-02, 1P20 RR021938-03, and R01AG029495-03. It was also supported in part by the Department of Energy under Award Number DE-FG02-99ER62764 to the Mind Research Network. We thank M. Weisend, S. Ahlfors, M. Hämäläinen, J. Mosher, A. Leuthold, and A. Georgopoulos for their help when the initial partnership between institutions was established which permitted the acquisition of these data. The content of this study is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Furthermore, the authors declare that they have no conflict of interest.

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  1. Department of Radiology, MSC10 5530, University of New Mexico School of Medicine, Albuquerque, NM, 87131, USA

    C. J. Aine, L. Sanfratello, T. Wallace, C. H. Donahue, R. Montaño & J. E. Bryant

  2. The Mind Research Network, Albuquerque, NM, USA

    C. J. Aine, L. Sanfratello, E. Best, J. A. MacArthur, K. Gilliam, A. Scott & J. M. Stephen

  3. Los Alamos National Laboratory, Los Alamos, NM, USA

    D. Ranken

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  1. C. J. Aine
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Aine, C.J., Sanfratello, L., Ranken, D. et al. MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data. Neuroinform 10, 141–158 (2012). https://doi.org/10.1007/s12021-011-9132-z

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