Spatiotemporal Accuracy of Gradient Magnetic-Field Topography (GMFT) Confirmed by Simultaneous Magnetoencephalography and Intracranial Electroencephalography Recordings in Patients with Intractable Epilepsy

Gradient magnetic-field topography (GMFT) is one method for analyzing magnetoencephalography (MEG) and representing the spatiotemporal dynamics of activity on the brain surface. In contrast to spatial filters, GMFT does not include a process reconstructing sources by mixing sensor signals with adequate weighting. Consequently, noisy sensors have localized and limited effects on the results, and GMFT can handle MEG recordings with low signal-to-noise ratio. This property is derived from the principle of the planar-type gradiometer, which obtains maximum gradient magnetic-field signals just above the electrical current source. We assumed that this characteristic allows GMFT to represent even faint changes in brain activities that cannot be achieved with conventional equivalent current dipole analysis or spatial filters. GMFT is thus hypothesized to represent brain surface activities from onset to propagation of epileptic discharges. This study aimed to validate the spatiotemporal accuracy of GMFT by analyzing epileptic activities using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. Participants in this study comprised 12 patients with intractable epilepsy. Epileptic spikes simultaneously detected on both MEG and iEEG were analyzed by GMFT and voltage topography (VT), respectively. Discrepancies in spatial distribution between GMFT and VT were evaluated for each epileptic spike. On the lateral cortices, areas of GMFT activity onset were almost concordant with VT activities arising at the gyral unit level (concordance rate, 66.7–100%). Median time lag between GMFT and VT at onset in each patient was 11.0–42.0 ms. On the temporal base, VT represented basal activities, whereas GMFT failed but instead represented propagated activities of the lateral temporal cortices. Activities limited to within the basal temporal or deep brain region were not reflected on GMFT. In conclusion, GMFT appears to accurately represent brain activities of the lateral cortices at the gyral unit level. The slight time lag between GMFT and VT is likely attributable to differences in the detection principles underlying MEG and iEEG. GMFT has great potential for investigating the spatiotemporal dynamics of lateral brain surface activities.