Magnetoencephalography can reveal deep brain network activities linked to memory processes. Issue 15 (29th June 2022)

• Record Type: Journal Article
• Authors: López‐Madrona, Víctor J.; Medina Villalon, Samuel; Badier, Jean‐Michel; Trébuchon, Agnès; Jayabal, Velmurugan; Bartolomei, Fabrice; Carron, Romain; Barborica, Andrei; Vulliémoz, Serge; Alario, F.‐Xavier; Bénar, Christian G.
• Is Part Of: Human brain mapping. Volume 43:Issue 15(2022)
• Page Start: 4733
• Page End: 4749
• Publication Date: 2022-06-29
• Subjects: hippocampus -- independent component analysis -- MEG -- memory -- SEEG -- simultaneous recordings -- source localization; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25987
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large‐scale neocortical networks. In the present study, we disentangled mesial activity and large‐scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo‐electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders. Abstract : Using blind source separation methods on MEG data, we obtain one BSS‐MEG component with a deep topography and a strong response during a memory task. Thanks to simultaneous intracerebral EEG and MEG recordings, we found that this component corresponds to a network composed by the hippocampus and the rhinal cortex.