Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas

Afnan, J.; von Ellenrieder, N.; Lina, J.-M.; Pellegrino, G.; Arcara, G.; Cai, Z.; Hedrich, T.; Abdallah, C.; Khajehpour, H.; Frauscher, B.; Gotman, J.; Grova, C.

doi:10.1101/2022.10.03.510665

bioRxiv · 10.1101/2022.10.03.510665

Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas

Afnan, J.·von Ellenrieder, N.·Lina, J.-M.·Pellegrino, G.·Arcara, G.·Cai, Z.·Hedrich, T.·Abdallah, C.·Khajehpour, H.·Frauscher, B.·Gotman, J.·Grova, C.

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Abstract

BackgroundMagnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation. MethodWe validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (IEEG) atlas (https://mni-open-ieegatlas.research.mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space, by applying a forward model to the MEG reconstructed source maps and estimated virtual IEEG (VIEEG) potentials on each IEEG channel location and quantitatively compared those with actual IEEG signals from the atlas for 38 regions of interest in the canonical frequency bands. ResultsThe MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the VIEEG than in the IEEG were more accurately recovered. In the deep regions, MEG estimated amplitudes were largely underestimated and the spectra were poorly recovered. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of IEEG but detected by MEG. Importantly, we found that MEG estimated spectra were more comparable to spectra from the IEEG atlas after the aperiodic components were removed. ConclusionThis study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies. HighlightsO_LIValidation of MEG source imaging with intracranial EEE atlas C_LIO_LIAssessment of resting state human brain oscillations from healthy brain C_LIO_LIAdapted source imaging method, wMEM, to localize resting state oscillations C_LIO_LIIdentified brain regions with oscillations accurately estimated by MEG C_LIO_LIMEG estimated spectra dominated by oscillations in the alpha band C_LI

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Afnan, J., von Ellenrieder, N., Lina, J.-M., Pellegrino, G., Arcara, G., Cai, Z., Hedrich, T., Abdallah, C., Khajehpour, H., Frauscher, B., Gotman, J., Grova, C.. 2022-10-04. Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas. https://doi.org/10.1101/2022.10.03.510665

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