Maris Luisa Saggio | “Epidynamics: Seizures in the Unfolding of a High Codimension Singularity”
Details
Epilepsy is one of the most common neurological disorders. Around one third of epileptic patients are drug resistant and these patients may be candidates for surgery. Different treatment strategies can be tested computationally using personalized large-scale brain models, providing in silico tools for testing clinical hypothesis and performing virtual surgeries. Electrographic seizures can be classified using knowledge from dynamical system theory in a taxonomy of sixteen possible seizure classes. In this Ph.D. project we created a single model able to produce bursting activity for most of the classes of the taxonomy, with the aim of further personalizing the large-scale brain model using the patient specific class. We validated the taxonomy based on dynamics on a large cohort of human data. Results are consistent with the theoretical framework inspired by our model, which we called Epidynamics, in particular the most surprising finding is that most patients have more than one class of seizures contrary to standard clinic teachings, and that transitions between classes can occur during a single seizure. The Epidynamics framework highlights the role of processes acting on at least three different timescales in the generation, evolution and termination of a seizure. We performed an initial exploration of the impact of the class on recruitment, that is a key feature determining seizure propagation.
Jury Composition
Rapporteurs
BRAZDIL MILAN, Masaryk University, Brno, Czech Republic
TERRY JOHN, University of Exeter, UK
Examinateur
DESTEXHE ALAIN, Unité de Neurosciences, Information & Complexité, Gif-sur-Yvette, France
MCGONIGAL AILEEN, Hôpital de la Timone, Marseille, France
BERNARD CHRISTOPHE, Aix-Marseille Université (INS)
Directeur de thèse
JIRSA VIKTOR, Aix-Marseille Université (INS)