In this lecture we will focus on a paper called “The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread”. Within their work, the authors used the epileptor model to simulate a patient's individual seizure.
To understand the concept we will have a closer look at the equations of the epileptor model and particular the epileptogenicity index which controls the excitability of each brain region.
Subsequently, we will begin to setup the epileptogenic zone in our own brain network model with TVB.
Topics covered in this lesson by Paul Triebkorn
- Local epileptor model and epileptogenic zone
- Setting up a brain network for epilepsy
The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread, published in NeuroImage, January 2017 by V.K. Jirsa, T. Proix, D. Perdikis, M.M. Woodman, H. Wanga, J. Gonzalez-Martinez, C. Bernard, C.Bénar, M. Guye, P. Chauvela, F. Bartolomei
Individual variability has clear effects upon the outcome of therapies and treatment approaches. The customization of healthcare options to the individual patient should accordingly improve treatment results.
We propose a novel approach to brain interventions based on personalized brain network models derived from non-invasive structural data of individual patients.
Along the example of a patient with bitemporal epilepsy, we show step by step how to develop a Virtual Epileptic Patient (VEP) brain model and integrate patient-specific information such as brain connectivity, epileptogenic zone and MRI lesions.
Using high-performance computing, we systematically carry out parameter space explorations, fit and validate the brain model against the patient's empirical stereotactic EEG (SEEG) data and demonstrate how to develop novel personalized strategies towards therapy and intervention.