Student: Viesulas Sliupas
Mentor: Christian Fink (Department of Physics and Astronomy)
In order to better understand how epilepsy spreads from one area of the brain to another, we used a computational model which simulates epileptic seizures in a chunk of the brain. We then took a network of the connections in the macaque brain between fairly large chunks, and ran our model in each part. The seizure spread from one area of the brain to the rest of it, and we tried to find if there was any connection we could remove which would prevent it from spreading. We found such a connection, removed it, and as a result the seizure only happened in one small region of the brain.
Current clinical practices for treating epilepsy are fairly crude and unrefined, including the use of vaguely-targeted incisions intended to prevent the seizure from spreading. In order to work towards developing finer and more precise tools for impeding the spread of seizures, we simulated seizures in a network model of the brain. Using the “Epileptor” dynamical model (developed via a phenomenological analysis of voltage traces, V.K. Jirsa et al 2014), we modelled a seizure event on the coarse connectome of a macaque brain in which the seizure generalized.l We were able to show that the seizure was prevented from spreading with minimal damageto neuronal connections by removing a single connection. This provides further proof to our hypothesis that we might be able to use this to develop targeted tools to prevent epilepsy from spreading in a real brain.