A Classification of Seizures Based on Dynamics
Jasper's Basic Mechanisms of the Epilepsies · 2024
Auteurs
Sheheitli H, Wang H, Lemarechal JD, Bernard C, Jirsa VK
Les auteurs en lien sont membres de l'INS.
Équipes
Résumé
Abstract Patient stratification according to seizure types is a pivotal step in the diagnosis and treatment of epilepsy. Great progress has been made in the understanding of the pathology and physiological substrates of epilepsy, leading to formal classification schemes based on empirical clinical features. However, much remains elusive regarding the mechanisms underlying seizures and the heterogeneity of its manifestations, which formal classification schemes attempt to capture. In the pursuit of a fundamental theory of seizure dynamics, dynamical systems theory provides the mathematical framework for a mechanistic understanding for the underlying dynamical processes. Within this framework, the need for a classification of seizures based on dynamics becomes evident. The diverse types of seizure onset and offset patterns are shown to be captured mathematically by different types of bifurcations that exhibit canonical invariant dynamical features. A seizure can then be classified into a corresponding “dynamotype” consisting of its onset and offset pair of bifurcations. Sixteen dynamotypes arise as combinations of the simplest relevant bifurcations, resulting in an organizational tax
Abstract Patient stratification according to seizure types is a pivotal step in the diagnosis and treatment of epilepsy. Great progress has been made in the understanding of the pathology and physiological substrates of epilepsy, leading to formal classification schemes based on empirical clinical features. However, much remains elusive regarding the mechanisms underlying seizures and the heterogeneity of its manifestations, which formal classification schemes attempt to capture. In the pursuit of a fundamental theory of seizure dynamics, dynamical systems theory provides the mathematical framework for a mechanistic understanding for the underlying dynamical processes. Within this framework, the need for a classification of seizures based on dynamics becomes evident. The diverse types of seizure onset and offset patterns are shown to be captured mathematically by different types of bifurcations that exhibit canonical invariant dynamical features. A seizure can then be classified into a corresponding “dynamotype” consisting of its onset and offset pair of bifurcations. Sixteen dynamotypes arise as combinations of the simplest relevant bifurcations, resulting in an organizational tax