Building an Ecosystem of Seizure Localization Methods: Neural Fragility as the First Step

The current treatment for drug-resistant epilepsy is surgical intervention, which relies on accurate identification of the seizure onset zone (SOZ) using intracranial electroencephalography (iEEG) data. iEEG analysis with computational epileptogenic zone identification algorithms (CEZIAs) is a promising step toward better SOZ localization and surgical outcomes. A key step in validation and adoption of CEZIAs is to allow for widespread shared development and validation of code and data. To achieve this, we developed an ecosystem of seizure localization methods that includes a straightforward analysis pipeline, standardized data formatting and storage, and completely documented and open-source code. The TableContainer package provides standardized storage of tabular data and serves as a foundational data structure for the ecosystem. Building on this, the Epoch package enables cropping, resampling, and visualization of iEEG data and provides publicly downloadable datasets for reproducibility. The public iEEG dataset includes eight females and six males, with a total of 47 iEEG recordings. Finally, the EZFragility package uses these two foundational packages to analyze iEEGs for SOZ localization using the Neural Fragility method described by Li et al. (2021). Additionally, EZFragility provides improvements in computational efficiency and user experience. It accurately reproduces neural fragility results for both sample patients used in the original paper. This project serves as the first step toward building an open-source, reproducible ecosystem of seizure localization methods in R. Future steps include the addition of other CEZIAs using the framework and sample data already made available by these packages.