Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Abstract

Brain Connectivity Analysis based on Stereoelectroencephalography (SEEG) has been increasingly explored as a tool for studying Epileptogenic Networks and supporting therapies for Refractory Epilepsy. In this Review, we summarize recent methodologies and findings on SEEG-based Functional and Effective Connectivity, which aim to define the dependence and influence between spatially distributed neurophysiological events. After briefly outlining the network analysis measurements used to interpret connectivity, we detail the mathematical principles underlying the 11 reviewed connectivity methods, along with the main findings characterizing the epileptogenic network for each method. Based on their principles, these methods can be organized into four classes: Signal Interaction, Signal Synchronization, Causality, and Other Nonlinear methods. Across these methods, consistent network signatures emerge, including functional isolation of the Epileptogenic Zone during interictal periods and complex hypersynchronization dynamics during seizures. As there is no single best method, we present a methodological framework that summarizes the relationship assumptions, computational costs, signal-processing requirements, and clinical use cases for each method. Finally, we discuss current challenges and future trends in this field.