Magnetoencephalography can reveal deep brain network activities linked to memory processes

Abstract

Recording from deep neural structures such as hippocampus non-invasively 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 SEEG 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.

Identification of an early hippocampal recognition system using intracerebral evoked potentials in humans

“…This neuronal facilitation would be reflected in the ERP, with earlier latencies for old items (Figure 3e). Interestingly, we identified a similar facilitation pattern in magnetoencephalography (MEG) during the same task (López-Madrona et al, 2022). In that work, the combined activity of the hippocampus and the rhinal cortex presented earlier latencies for old items.…”

Cortical and Subcortical Changes in MEG Activity Reflect Parkinson’s Progression over a Period of 7 Years

“…Third, although there is increasing evidence that projecting MEG to subcortical sources is feasible, MEG is most sensitive to cortical sources (Hillebrand and Barnes 2002). The sensitivity for subcortical sources can be further improved using new analysis techniques such as 'blind source separation' (López-Madrona et al 2022;Pizzo et al 2019), methods that increase the contrast between cortical and subcortical sources (Quraan et al 2011), or in-mouth sensors (Tierney et al 2021).…”