1 / 13

Viability of Sharing MEG Data using Minimum-Norm Imaging

Viability of Sharing MEG Data using Minimum-Norm Imaging. Syed Ashrafulla, Dimitrios Pantazis, John Mosher, Matti Hämäläinen, Brent Liu, Richard M. Leahy. Magnetoencephalography.

asta
Download Presentation

Viability of Sharing MEG Data using Minimum-Norm Imaging

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Viability of Sharing MEG Data using Minimum-Norm Imaging Syed Ashrafulla, Dimitrios Pantazis, John Mosher, Matti Hämäläinen, Brent Liu, Richard M. Leahy

  2. Magnetoencephalography Baillet, S., Mosher, J.C. and Leahy, R.M., “Electromagnetic brain mapping,” IEEE Signal Processing Magazine 18(6), 14-31 (2001)

  3. Multicenter Data Center 1 Center 2 Neuromag 4D UI archive archive UI CTF archive UI Can a user analyze data from multiple centers as if all data was recorded by the user’s machine? Center 3

  4. How to Test for Equivalence

  5. Re-sampling Evoked Response

  6. Estimating Activity MEG Recordings Cortical Activity ??? Forward model G Inverse estimate H Estimated Activity • Lin, F., Belliveau, J., Dale, A., and Hämäläinen, M., “Distributed current estimates using cortical orientation constraints,” Human Brain Mapping27(1), 1-13 (2006).

  7. Areas of Significant Activity Test statistic Thresholding Control familywise error rate: Significant if Pantazis, D. and Leahy, R., “Statistical inference in MEG distributed source imaging,” in [MEG: An Introduction to Methods], Hansen, P., Kringlebach, M., and Salmelin, R., eds., 257-284, Oxford University Press (2010).

  8. Results: Regions of Activity

  9. Measuring Consistency G F

  10. Results: Measuring Similarity

  11. Testing for Equivalence Dice: Simpson: 2ε 2ε ε ε 0 0 -ε -ε -2ε -2ε

  12. Results: Inter-Site Equivalence Neuromag-CTF 4D-Neuromag CTF-4D Neuromag Neuromag vs. vs. vs. CTF CTF 4D 4D 1.0 % of subject-runs admitting equivalence 0.5 0.0

  13. Conclusion • Regions agree visually • Multicenter pooling of data does not affect localization … • … except for some subjects and pairs of sites. • Our criteria is stringent: equivalence in small ε • Next steps • Test other methods to estimate activity • Ensure estimation does not affect pooling • Set up data model for multicenter pooling • Allow for search by pathology or condition

More Related