A taxonomy of seizure dynamotypes

Maria Luisa Saggio,Viktor Jirsa,Dakota Crisp,Stephen V Gliske,Matthias Dümpelmann,Tomohiko Murai,Christophe Bernard,Levin Kuhlmann,Jared M Scott,Jack Lin,Mitsuyoshi Nakatani,Philippa Karoly,Akio Ikeda,Andreas Schulze-Bonhage,Mark Cook,William C Stacey

doi:10.7554/elife.55632

Abstract

Seizures are a disruption of normal brain activity present across a vast range of species and conditions. We introduce an organizing principle that leads to the first objective Taxonomy of Seizure Dynamics (TSD) based on bifurcation theory. The 'dynamotype' of a seizure is the dynamic composition that defines its observable characteristics, including how it starts, evolves and ends. Analyzing over 2000 focal-onset seizures from multiple centers, we find evidence of all 16 dynamotypes predicted in TSD. We demonstrate that patients' dynamotypes evolve during their lifetime and display complex but systematic variations including hierarchy (certain types are more common), non-bijectivity (a patient may display multiple types) and pairing preference (multiple types may occur during one seizure). TSD provides a way to stratify patients in complement to present clinical classifications, a language to describe the most critical features of seizure dynamics, and a framework to guide future research focused on dynamical properties.

Highlights

Epilepsy is one of the most common neurological disorders with an estimated prevalence of 50 million worldwide (World Health Organization, 2020)
These results show that the chosen features are capable of distinguishing the different bifurcations reliably for both human visualization and algorithms, that human seizure dynamics are consistent with the modeled bifurcations, and that human reviewers can use the methods described in the paragraphs to classify onset and offset bifurcations reliably
Real clinical data are challenging: the lack of DC shift makes it difficult to distinguish some bifurcations, and the noisiness of EEG is hard to distinguish from arbitrary dynamics

Summary

Introduction

Epilepsy is one of the most common neurological disorders with an estimated prevalence of 50 million worldwide (World Health Organization, 2020). It is characterized by spontaneously recurring seizures, which are ‘a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain’ (Fisher et al, 2005). Seizure classifications to date have been purely descriptive of empirical data: clinical manifestations (e.g. focal vs generalized) that are based upon the region of brain affected rather than the seizure itself, and visual descriptions of electroencephalogram (EEG) waveforms.

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Discussion

Conclusion