Using dynamical metrics hypergraphs to study epilepsy dynamics.

DALMA BILBAO; HUGO ALEJANDO ANTONIO; MATEOS DIEGO MARTIN

Buenos Aires

Congreso; SAN 2022; 2022

Universidad NAcional de Buenos Aires UBA

The analysis of connectivity networks is one of the fundamental tools in the study of neuroscience. Generally, this analysis is carried out using graph theory, which describes the pairwise relationship between the components of a network. However, in the brain, the relationship between its components (neurons, brain areas, etc.) has more complex relationships. To address this problem, hypergraph theory can represent the multiple relationships between its components. In this work, we use the metric hypergraph method to study brain dynamics during an epileptic seizure. Initially, we applied the basic Kuramoto model, which simulates a hypersynchronisation of the system (seizure). Subsequently, magnetoencephalography signals from two particular cases of generalized epilepsy were analyzed. Through this analysis, we can study the dynamics of the synchronization phenomenon in an epileptic seizure.