Intracranial Validation of Magnetoencephalography Across Oscillatory Frequency and Depth
Non-invasive, whole-brain neuroimaging methods such as functional magnetic resonance imaging, electroencephalography (EEG), and magnetoencephalography (MEG) are essential tools for studying the basis of human cognition in health and disease. MEG offers the opportunity to study neural activity at its intrinsic timescale, by recording the magnetic fields generated by electrical currents within the brain from outside the skull. Moreover, recently developed optically pumped magnetometers (OPMs) allow these recordings to take place in new settings, for example during naturalistic behaviour and in previously inaccessible populations. These breakthroughs have led to a shift in the neuroimaging landscape, with a global increase in the adoption of MEG. Crucially, however, the extent to which MEG recordings can measure different features of neural activity remains unclear. To address this issue, we leveraged a unique and rare dataset of concurrent MEG and intracranial EEG recordings from a cohort of epileptic patients. We found that group-level inferences of spontaneous oscillatory dynamics made with source-localised MEG, i.e. estimates of power and bursts, accurately reflected the underlying neural activity. As expected, the agreement was strongest for lower-frequency activity (delta, theta, and alpha) and superficial sources, and weakest in the gamma range. Crucially, however, MEG was also sensitive to deep structures: it captured oscillatory power and burst dynamics in the hippocampus, most robustly in the theta band. These findings demonstrate that MEG is sensitive to physiologically meaningful activity in cortical and subcortical regions and establish a foundation for the interpretation of future MEG studies across a wide range of research domains.