Authors :
Presenting Author: Paul Triebkorn, MSN – Aix Marseille Université
Huifang Wang, PhD – Aix Marseille University; Viktor Jirsa, Prof – Aix Marseille University
Rationale:
Current common treatment options for epilepsy are medication, surgical removal of the epileptic tissue, and stimulation. Success rates of surgical and stimulative interventions are in the range of 50% to 70%, leaving room for improvement. Computational modelling and dynamical systems theory can help to further our understanding of seizure dynamics and possibly provide intervention strategies.
Methods:
We built a high resolution personalized computational model of a patient with drug resistant focal epilepsy in the left temporal lobe. T1 weighted and diffusion MRI together with tractography were used to reconstruct the cortical surface and to estimate connections between points of the surface on the scale of 1mm3. We used a two-dimensional dynamical model, called the Epileptor, to model seizure dynamics.
Results:
We first simulated reentry excitation in a toy model of two delay-coupled 2D Epileptors. Then we equipped the cortical surface with the dynamical model and explored the parameter space of local and global coupling strength. We observed self-limiting excitations, spiral waves, and sustained reentry excitation. We tested two intervention strategies trying to prevent reentry. Virtual surgery was applied to the white matter by lesioning fibre tracks and removing their contribution to the connectivity of the cortex. We also demonstrated phase dependent stimulation effects through virtually implanted electrodes. Conclusions:
We demonstrated that a high resolution personalized computational model can be used to simulate epileptic dynamics and test intervention strategies at a level of high resolution, which is necessary for real world applications. Future studies should focus on fine tuning the parameters of the model to fit it to the individual observed empirical data and optimize the intervention.Funding:
This work is partially funded through the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3);