Modeling Seizure Initiation and Spread

Abstract

Epilepsy is a devastating condition, impacting over 50 million people worldwide. Understanding and treating this disease remains a challenge because of its heterogeneous manifestations. A deeper understanding of the underlying biological mechanisms will help pinpoint regions for resection and offer novel targets for pharmacologic or stimulation-based therapies. Here, we present a biophysically and anatomically-motivated model that simulates intracranially-recorded epileptic activity in patients. Our model consists of two components: a mean field model that accounts for the folded geometry of the cortex and electrodes that capture appropriate electrical contributions from neighboring neuronal sources. We also include three elements that were previously proposed to play important roles in seizure dynamics: fast-spiking interneuron population, depolarization block, and evolving extracellular potassium that modulates neural excitability and gap-junction coupling. This model captures several important findings from patient electrographic data of seizures that have been analyzed in previous studies: (1) An ictal wavefront slowly propagates outwards from the epileptogenic focus, recruiting neighboring areas into abnormal activity. Traveling waves emerge within the recruited area and propagate much faster than the ictal wavefront. (2) Contradictory studies proposed that the source of traveling waves is either a stationary cortical source or a moving ictal wavefront. Our model suggests that both cases are plausible and the former happens when the focus is persistent and highly excitable. (3) Seizure terminates spontaneously and synchronously and the frequency of traveling waves decreases before termination. (4) Network coupling increases shortly after seizure onset, decreases during propagation and increases again approaching termination. (5) Consistency of wave direction gradually increases, but the direction can occasionally undergo sudden changes. Overall, the model serves as a means to begin understanding various mechanisms underlying seizure initiation, propagation and termination. It is also greatly customizable and can be adapted to a wide range of unique clinical cases, providing a first step in quick and cost-effective development of personalized therapies.