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Virtual brain twins for stimulation in epilepsy

Wang, H. E.; Dollomaja, B.; TRIEBKORN, J. P.; Duma, G. M.; WILLIAMSON, A.; Makhalova, J.; LEMARERECHAL, J.-d.; BARTOLOMEI, F.; Jirsa, V.

2024-07-27 neurology
10.1101/2024.07.25.24310396 medRxiv
Show abstract

Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and plays a pivotal role in treatment and intervention. Virtual brain twins based on personalized whole brain modeling provides a formal method for personalized diagnosis by integrating patient-specific brain topography with structural connectivity from anatomical neuroimaging such as MRI and dynamic activity from functional recordings such as EEG and stereo-EEG (SEEG). Seizures demonstrate rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. In our modeling process, we consider invasive SEEG stimulation as the most practical current approach, and temporal interference (TI) stimulation as a potential future approach for non-invasive diagnosis and treatment. This paper offers a virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. This framework estimates the EZN and validated the results on synthetic data with ground-truth. It provides an important methodological and conceptual basis for a series of ongoing scientific studies and clinical usage, which are specified in this paper. This framework also provides the necessary step to go from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy.

Published in Nature Computational Science (predicted rank #2) · training set

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