Magnetoencephalography (MEG) is widely used for studying resting-state brain connectivity. However, MEG source imaging is ill posed and has limited spatial resolution. This introduces source-leakage issues, making it challenging to interpret MEG-derived connectivity in resting states. To address this, we validated MEG-derived connectivity from 45 healthy participants using a normative intracranial EEG (iEEG) atlas. The MEG inverse problem was solved using the wavelet-maximum entropy on the mean method. We computed four connectivity metrics: amplitude envelope correlation (AEC), orthogonalized AEC (OAEC), phase locking value (PLV), and weighted-phase lag index (wPLI). We compared spatial correlation between MEG and iEEG connectomes across standard canonical frequency bands. We found moderate spatial correlations between MEG and iEEG connectomes for AEC and PLV. However, when considering metrics that correct/remove zero-lag connectivity (OAEC/wPLI), the spatial correlation between MEG and iEEG connectomes decreased. MEG exhibited higher zero-lag connectivity compared with iEEG. The correlations between MEG and iEEG connectomes suggest that relevant connectivity patterns can be recovered from MEG. However, since these correlations are moderate/low, MEG connectivity results should be interpreted with caution. Metrics that correct for zero-lag connectivity show decreased correlations, highlighting a trade-off; while MEG may capture more connectivity due to source-leakage, removing zero-lag connectivity can eliminate true connections.

The ill-posed nature and low spatial resolution of EEG/magnetoencephalography (MEG) source imaging affects functional connectivity estimates, which become more complicated in the resting state due to the low signal-to-noise ratio. Several connectivity metrics have been proposed to address source leakage by removing zero-lag connectivity, although this can eliminate true neuronal zero-lag connections. Intracranial EEG (iEEG) is the gold standard for validating noninvasive measurements. In this study, we validated MEG-estimated connectivity for healthy subjects using the iEEG atlas of normal brain activity (Frauscher et al., 2018) as ground truth at a group level. We employed two amplitude-based metrics and two phase-based metrics. Our findings highlight how MEG connectivity compares with the iEEG atlas and provide valuable insights for resting-state EEG/MEG connectomic studies, particularly in the choice of connectivity metrics.

This content is only available as a PDF.

Competing Interests

Competing Interests: The authors have declared that no competing interests exist.

Author notes

Handling Editor: Cornelis Jan Stam

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.

Supplementary data