Abstracts

Rationale:
Stereoelectroencephalography (SEEG) is a powerful intracerebral EEG recording method for the presurgical evaluation of epilepsy. It consists in implanting depth electrodes in the patient's brain to record electrical activity and map the epileptogenic zone, which should be resected to render the patient seizure-free. SEEG has high spatial accuracy and signal-to-noise ratio but remains limited in the coverage of the explored brain regions. Thus, the implantation might provide a suboptimal sampling of epileptogenic regions. Source localization methods in SEEG has been proposed to overcome this limitation and recover the activity from regions not sampled with SEEG. (López-Madrona et al. Neuroimage. 2023, Satzer et al. Clin Neurophysiol. 2022)

Methods:
We investigated the potential of improving a suboptimal SEEG recording by performing source localization on SEEG signals. We proposed to compute Independent Component Analysis (ICA) which allows disentangling the multiple local and remote sources recorded by the SEEG electrodes and provide a temporal course and a spatial map for each source. Then, by combining visual analysis and connectivity measures on the temporal courses, we identified the components of interest containing pathological activities and leading the functional connectivity. Finally, we applied distributed source modelling on the associated topographies. This approach was tested on two patients with two implantations each, the first failing to characterize the epileptogenic zone and the second giving a better diagnosis. The computation was made on the first one; the second one served as reference.

Results:
We demonstrated that source localization of independent components obtained from both ictal and interictal data of the first SEEG recordings matches the findings of the second SEEG exploration.

Conclusions:
Our findings suggest that Independent Component Analysis followed by source localization on the topographies of interest is a promising method for retrieving the epileptogenic zone in case of suboptimal implantation. It allows resuming epileptic activities in some components of interest and localize them even if the regions were not sampled.

Funding: This work was funded by the French National Research Agency (ANR) as part of the second “Investissements d’Avenir” program (ANR-17-RHUS-0004, EPINOV), by the FLAG-ERA Grant SCALES  (ANR-17-HBPR-0005), an ILCB grant to VLM (ANR-16-CONV-0002), and by the European grant ERC Synergy GALVANI (ERC-SyG 2019, Grant Agreement No. 855109).