Modeling seizures with a conductance-based integrate-and-fire neuronal network model

Abstract

Imaging research of seizures in Zebrafish brains involves tracing calcium levels as a by-product of neuronal firing using genetically encoded fluorescent calcium indicators. The imaging data suggests the seizures move in a wave-like pattern through the various parts of the brain. Using this data, researchers can predict the frequency of firing rates within the brain. The purpose of this thesis is to create a mathematical model that demonstrates a similar wave-like pattern at similar firing rate frequencies using a neuronal network of integrate-and-fire neurons. Calcium and its emission ratio are also modeled to connect the simulated data with the experimental data.