Exploring Epilepsy: An Investigation of Heterogeneity on Seizure-Prone Networks of Neurons Through Computational Modelling

Abstract

Epilepsy is a neural disease characterized by rhythmic synchronous firing of neurons, also called seizures. These seizures can be modelled as oscillations of voltage input into neighboring neural regions. In this thesis we put forward a leaky integrate-and-fire network model to investigate how seizure-like inputs interact with heterogeneity. We find that heterogeneity supresses oscillatory behaviour of the network, linearizing the system, with large decreases seen in both resonant and higher-order harmonics. While some frequencies do not follow this trend, heterogeneity is shown to decorrelate excitatory-inhibitory networks, promoting asynchronous firing.