Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients

TL;DR

This paper applies symbolic analysis to EEG data to assess the directionality and strength of brain region interactions in epilepsy, revealing complex interdependencies that contribute to seizure generation.

Contribution

It introduces a time-resolved symbolic analysis method for evaluating directed interactions in EEG data, advancing understanding of epileptic network dynamics.

Findings

Revealed complex spatial-temporal interdependencies in epileptic networks

Identified potential roles of interdependencies in seizure generation

Demonstrated effectiveness of symbolic analysis despite data reduction

Abstract

Inferring strength and direction of interactions from electroencephalographic (EEG) recordings is of crucial importance to improve our understanding of dynamical interdependencies underlying various physiologic and pathophysiologic conditions in the human epileptic brain. We here use approaches from symbolic analysis to investigate---in a time-resolved manner---weighted and directed, short- to long-ranged interactions between various brain regions constituting the epileptic network. Our observations point to complex spatial-temporal interdependencies underlying the epileptic process and their role in the generation of epileptic seizures, despite the massive reduction of the complex information content of multi-day, multi-channel EEG recordings through symbolisation. We discuss limitations and potential future improvements of this approach.