" Virtual Brain "-Based Interpretation of Electrophysiological Signals in Epilepsy
" Virtual Brain "-Based Interpretation of Electrophysiological Signals in Epilepsy
Epilepsy is a major neurological disorder, affecting of the order of 0.5 to 1% of the
 population. It is a very invalidating disease, with high impact on quality of life. In a
 large proportion of cases, medication cannot prevent seizures; surgical removal of the
 regions responsible for seizures is then the only way to cure patients. However, results
 crucially depend on the correct delineation of the epileptogenic zone.

 In this context, computational modeling, under the form of a "virtual brain" is a powerful
 tool to investigate the impact of different configurations of the sources on the measures, in
 a well-controlled environment.

 In this project, the simulate in a biologically realistic way MEG (Magnetoencephalography)
 and EEG (Electroencephalography) fields produced by different configurations of brain
 sources, which will differ in terms of spatial and dynamic characteristics will be offered to
 participants. The research hypothesis is that computational and biophysical models can bring
 crucial information to clinically interpret the signals measured by MEG and EEG. In
 particular, the hypothesis can help to efficiently address some complementary questions faced
 by epileptologists when analyzing electrophysiological data.

 The strategy will be three-fold:

 i) Construct a virtual brain models with both dynamic aspects (reproducing both
 hyperexcitability and hypersynchronisation alterations observed in the epileptic brain) and a
 realistic geometry based on actual tractography measures performed in patients ii) Explore
 the parameter space though large-scale simulations of source configurations, using parallel
 computing implemented on a computer cluster.

 iii) Confront the results of these simulations to simultaneous recordings of EEG, MEG and
 intracerebral EEG (stereotactic EEG, stereoelectroencephalography (SEEG)). The models will be
 tuned on SEEG signals, and tested versus the surface signals in order to validate the ability
 of the models to represent real MEG and EEG signals.

 The project constitutes a translational effort from theoretical neuroscience and mathematics
 towards clinical investigation. A first output of the project will be a database of
 simulations, which will permit in a given situation to assess the number of configurations
 that could have given rise to the observed signals in EEG, MEG and SEEG. A second - and major
 - output of the project will be to give the clinician access to a software platform which
 will allow for testing possible configurations of hyperexcitable regions in a user-friendly
 way. Moreover, representative examples will be made available to the community through a
 website, which will permit its use in future studies aimed at confronting the results of
 different signal processing methods on the same 'ground truth' data.
Inclusion Criteria:

 -  Epilepsy patients with planned intracerebral exploration (SEEG)

 -  informed patient

 -  patient affiliated to French social security

 Exclusion Criteria:

 -  Patients under 18

 -  Pregnant or breastfeeding women

 -  Patients deprived of liberty by legal decision

 -  Patients not covered by social security

 -  Patients who did not sign informed consent

 -  patients who cannot undertake MRI exam