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24 March 2011 Viability of sharing MEG data using minimum-norm imaging
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Cortical activation maps estimated from MEG data fall prey to variability across subjects, trials, runs and potentially MEG centers. To combine MEG results across sites, we must demonstrate that inter-site variability in activation maps is not considerably higher than other sources of variability. By demonstrating relatively low inter-site variability with respect to inter-run variability, we establish a statistical foundation for sharing MEG data across sites for more powerful group studies or clinical trials of pathology. In this work, we analyze whether pooling MEG data across sites is more variable than aggregating MEG data across runs when estimating significant cortical activity. We use data from left median nerve stimulation experiments on four subjects at each of three sites on two runs occurring on consecutive days for each site. We estimate cortical current densities via minimum-norm imaging. We then compare maps across machines and across runs using two metrics: the Simpson coefficient, which admits equality if one map is equal in location to the other, and the Dice coefficient, which admits equality if one map is equal in location and size to the other. We find that sharing MEG data across sites does not noticeably affect group localization accuracy unless one set of data has abnormally low signal power.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Syed Ashrafulla, Dimitrios Pantazis, John Mosher, Matti Hämäläinen, Brent Liu, and Richard M. Leahy "Viability of sharing MEG data using minimum-norm imaging", Proc. SPIE 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 79670F (24 March 2011);

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