Abstract
Epilepsy can be regarded as a network phenomenon with functionally and/or structurally aberrant connections in the brain. Over the past years, concepts and methods from network theory substantially contributed to improve the characterization of structure and function of these epileptic networks and thus to advance understanding of the dynamical disease epilepsy. We extend this promising line of research and assess—with high spatial and temporal resolution and using complementary analysis approaches that capture different characteristics of the complex dynamics—both strength and direction of interactions in evolving large-scale epileptic brain networks of 35 patients that suffered from drug-resistant focal seizures with different anatomical onset locations. Despite this heterogeneity, we find that even during the seizure-free interval the seizure onset zone is a brain region that, when averaged over time, exerts strongest directed influences over other brain regions being part of a large-scale network. This crucial role, however, manifested by averaging on the population-sample level only – in more than one third of patients, strongest directed interactions can be observed between brain regions far off the seizure onset zone. This may guide new developments for individualized diagnosis, treatment and control.
Highlights
Assessed properties of brain interactions using EEG data from selected recording sites and only investigated selected epochs of pathophysiological activities
Selections were mostly based on various cortical zones as used in the presurgical evaluation[9], but it is not yet fully clear, if and how the various zones and their dynamics match the modern concepts of a large-scale functional epileptic network
Highest strengths of interactions were confined to the seizure onset zone (SOZ; f–f) and they tended to decrease with an increasing distance to the SOZ
Summary
Assessed properties of brain interactions using EEG data from selected recording sites and only investigated selected epochs of pathophysiological activities (such as seizures and/or epileptiform discharges). Different analysis techniques—that are based on different concepts and that may be affected differently by various aspects of the recording—were used to characterize either aspects of the strength or of the direction of an interaction Concerning the latter, quite often has an estimator’s modulus been interpreted as some strength of an interaction (the sign indicates the direction), which might not generally be valid and can lead to severe misinterpretations for uncoupled and strongly coupled systems[34,35,36]. IA consists of estimating the strength of an interaction with the order parameter γ42 and the direction of an interaction with directionality index T that is based on symbolic transfer entropy[43] Despite their conceptional and methodological differences, both estimators for the strength of an interaction assign a low/high weight to an edge that connects weakly/strongly coupled, interacting brain regions. This assignment, incorporates the actual coupling strength (as assessed with the respective estimator for the strength of an interaction) to avoid misinterpretations about directionality in regimes of zero and strong couplings
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