Suppressing seizure via optimal electrical stimulation to the hub of epileptic brain network

TL;DR

This paper presents a network control theory-based platform that uses optimal electrical stimulation of the epileptic brain network hub to effectively suppress seizures, offering an alternative to direct SOZ stimulation.

Contribution

It introduces a novel platform combining system identification and control strategies to validate network-level stimulation for seizure suppression.

Findings

Electrical stimulation of the network hub effectively suppresses seizures.

The platform accurately predicts neural dynamics for targeted stimulation.

Network control theory provides a general validation tool for neural stimulation strategies.

Abstract

The electrical stimulation to the seizure onset zone (SOZ) serves as an efficient approach to seizure suppression. Recently, seizure dynamics have gained widespread attendance in its network propagation mechanisms. Compared with the direct stimulation to SOZ, other brain network-level approaches that can effectively suppress epileptic seizures remain under-explored. In this study, we introduce a platform equipped with a system identification module and a control strategy module, to validate the effectiveness of the hub of the epileptic brain network in suppressing seizure. The identified surrogate dynamics show high predictive performance in reconstructing neural dynamics which enables the model predictive framework to achieve accurate neural stimulation. The electrical stimulation on the hub of the epileptic brain network shows remarkable performance as the direct stimulation of SOZ in suppressing seizure dynamics. Underpinned by network control theory, our platform offers a general tool for the validation of neural stimulation.