Zhang, L; Wang, Q; Baier, G; (2020) Spontaneous transitions to focal-onset epileptic seizures: A dynamical study. Chaos , 30 (10) , Article 103114. 10.1063/5.0021693.

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Abstract

Given the complex temporal evolution of epileptic seizures, understanding their dynamic nature might be beneficial for clinical diagnosis and treatment. Yet, the mechanisms behind, for instance, the onset of seizures are still unknown. According to an existing classification, two basic types of dynamic onset patterns plus a number of more complex onset waveforms can be distinguished. Here, we introduce a basic three-variable model with two time scales to study potential mechanisms of spontaneous seizure onset. We expand the model to demonstrate how coupling of oscillators leads to more complex seizure onset waveforms. Finally, we test the response to pulse perturbation as a potential biomarker of interictal changes. Focal epileptic seizures are characterized by complex spatiotemporal rhythms of electric brain activity. Phenomenologically, there are different types of rhythms, namely, fast-small oscillations, slow-large spiking, and complex waveforms of the voltage. The dynamics of these types are, however, still poorly understood and their clinical characterization is, therefore, mostly descriptive. We use computational modeling of macro-level electrical brain activity to study the spontaneous onset and evolution of major clinical seizure rhythms. Looking at principal models of one and two coupled oscillators with a slow driving population, we show the dynamical characteristics and relationships between basic seizure onset types. In addition, we show that pulse perturbations of background activity can serve as a biomarker for seizure onset.

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