User-defined virtual sensors: A new solution to the problem of temporal plus epilepsy sources

Objective: The most common medically resistant epilepsy (MRE) involves the temporal lobe (TLE), and children designated as temporal plus epilepsy (TLE+) have a five-times increased risk of postoperative surgical failure. This retrospective, blinded, cross-sectional study aimed to correlate visual and computational analyses of magnetoencephalography (MEG) virtual sensor waveforms with surgical outcome and epilepsy classification (TLE and TLE+). Methods: Patients with MRE who underwent MEG and iEEG monitoring and had at least 1 year of postsurgical follow-up were included in this retrospective analysis. User-defined virtual sensor (UDvs) beamforming was completed with virtual sensors placed manually and symmetrically in the bilateral amygdalohippocampi, inferior/middle/superior temporal gyri, insula, suprasylvian operculum, orbitofrontal cortex, and temporoparieto-occipital junction. Additionally, MEG effective connectivity was computed and quantified using eigenvector centrality (EC) to identify hub regions. More conventional MEG methods (equivalent current dipole [ECD], standardized low-resolution brain electromagnetic tomography, synthetic aperture magnetometry beamformer), UDvs beamformer, and EC hubs were compared to iEEG. Results: Eighty patients (38 female, 42 male) with MRE (mean age = 11.3 ± 6.2 years, range = 1.0-31.5) were identified and included. Twenty-five patients (31.3%) were classified as TLE, whereas 55 (68.8%) were TLE+. When modeling the association between