Seizure prediction and intervention. (1st August 2020) - Meisel, Christian; Loddenkemper, Tobias
Abstract: Epilepsy treatment is challenging due to a lack of essential diagnostic tools, including methods for reliable seizure detection in the ambulatory setting, to assess seizure risk over time and to monitor treatment efficacy. This lack of objective diagnostics constitutes a significant barrier to better treatments, raises methodological concerns about the antiseizure medication evaluation process and, to patients, is a main issue contributing to the disease burden. Recent years have seen rapid progress towards better diagnostics that meet these needs of epilepsy patients and clinicians. Availability of comprehensive data and the rise of more powerful computational analysis methods have driven progress in this area. Here, we provide an overview on data- and theory-driven approaches aimed at identifying methods to reliably detect and forecast seizures as well as to monitor brain excitability and treatment efficacy in epilepsy. We provide a particular account on neural criticality, the hypothesis that cortical networks may be poised in a critical state at the boundary between different types of dynamics, and discuss its role in informing diagnostics to track cortex excitability and seizure risk in recent experiments. With the further expansion of digitalization in medicine, tele-medicine and long-term, ambulatory monitoring, these computationally based methods may gain more relevance in epilepsy in the future. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century – From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'. Highlights: Improved measures to quantify seizure occurrence, seizure risk and response to ASM treatment may help to enhance treatment options in epilepsy. The increasing availability of long-term, multi-modal data along with improved data- and theory-driven analytical approaches may support the development of such diagnostic measures. As a theory-driven framework, the criticality hypothesis posits that cortical network activity is poised at the boundary between distinct types of dynamics. We here offer a survey on recent data- and theory-driven efforts for seizure detection, forecasting and ASM monitoring with an emphasis on leveraging theory-driven insights for diagnostics development.