Modeling seizures: From single neurons to networks

Dynamical system tools offer a complementary approach to detailed biophysical seizure modeling, with a high potential for clinical applications. This review describes the theoretical framework that provides a basis for theorizing certain properties of seizures and for their classification according to their dynamical properties at onset and offset. We describe various modeling approaches spanning different scales, from single neurons to large-scale networks. This narrative review provides an accessible overview of this field, including non-exhaustive examples of key recent works.

Automated summary

Dynamic system tools serve as complementary approach to detailed biophysical seizure modeling, showing high potential for clinical applications. This review outlines the theoretical framework for theorizing seizure properties and their classification based on dynamical properties. Various modeling approaches across different scales are discussed, providing an accessible overview of the field with examples of recent key works.