Virtual intracranial electroencephalography for epilepsy surgery using ictal magnetoencephalography

Abstract

Modelling the interactions that arise from neural dynamics in seizure genesis is challenging but important in the effort to improve the success of epilepsy surgery. Dynamical network models developed from physiological evidence offer insights into rapidly evolving brain networks in the epileptic seizure. A major limitation of previous studies in this field is the dependence on invasive cortical recordings with constrained spatial sampling of brain regions that might be involved in seizure dynamics. Here, we propose a novel approach, virtual intracranial electroencephalography (ViEEG), that combines non-invasive ictal magnetoencephalographic imaging (MEG), dynamical network models and a virtual resection technique. In this proof-of-concept study, we show that ViEEG signals reconstructed from MEG alone preserve critical temporospatial characteristics for dynamical approaches to identify brain areas involved in seizure generation. Our findings demonstrate the advantages of non-invasive ViEEG over the current presurgical ‘gold-standard’ – intracranial electroencephalography (iEEG). Our approach promises to optimise the surgical strategy for patients with complex refractory focal epilepsy.