1 Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, H3A 2B4, Canada.
2 Integrated Program in Neuroscience, McGill University, Montréal, Québec H3A 1A1, Canada.
3 Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada.
4 Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada.
5 Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec H3C 1K3, Canada.
6 Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada.
7 Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
8 Epilepsy program, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 5C1, Canada.
9 Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy.
10 Multi

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.