Fig. 1: Workflow of Virtual iEEG (ViEEG) and network model.
From: Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery
Simultaneous HDEEG and MEG were acquired from surgical candidates in presurgical evaluation for epilepsy surgery36. Ictal MEG signals from 102-channel magnetometers and 204-channel gradiometers are epoched and pre-processed for source signal reconstruction. ViEEG locations fully contain MSL solutions (early, mid and late phases of averaged ictal discharges)36 and the entire resection margin. Ictal ViEEG signals are reconstructed using a beamformer technique and a boundary element method (BEM) model generated from individual MRI scans. Functional networks are constructed using two connectivity methods, amplitude envelope correlation (AEC) and mutual information (MI), and dynamical network models are applied to evaluate how cortical excitability changes when a node is virtually removed from the network. The Virtual Ictogenic Zone (VIZ), identified by a dynamical network approach, consists of nodes that decrease cortical excitability when virtually resected from the network. We hypothesise that this VIZ helps elucidate the epileptogenic zone (EZ) and identifies non-ictogenic brain areas that are less likely to be involved in the EZ.
