The code used for generating and evaluating synthetic data based on empirical data from 30 patients with drug-resistant epilepsy
The dataset can be found here:
Dollomaja, B., Wang, H., & Jirsa, V. (2024). Virtual Epileptic Patient Cohort (v1.0) [Data set]. EBRAINS. https://doi.org/10.25493/XWG2-S8X
The paper describing the dataset:
Dollomaja, B., Wang, H. E., Guye, M., Makhalova, J., Bartolomei, F., & Jirsa, V. K. (2025). Virtual epilepsy patient cohort: generation and evaluation. PLOS Computational Biology, 21(4), e1012911. https://doi.org/10.1371/journal.pcbi.1012911
The code to generate synthetic spontaneous seizures: virtual_epileptic_seeg_ret_patient.py
The code to generate synthetic stimulated seizures: STIM_virtual_epileptic_seeg_ret.py
The code to generate synthetic interictal data: IIS_virtual_epileptic_seeg_ret.py
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The code used to compare each modality of synthetic activity to its empirical counterpart:
auto_compare_synthetic_empirical.py
(for spontaneous seizures)
auto_compare_synthetic_empirical_Stim.py
(for stimulated seizures)
IIS_compute_spike_frequency.py
and IIS_compare_synthetic_empirical.py
(for interictal data)
Generating simulated data with varying stimulation amplitude: STIM_virtual_epileptic_seeg_ret_ControlAmplitude.py
Generating simulated data with varying stimulation location: STIM_virtual_epileptic_seeg_ret_ControlLocation.py
Comparing empirical and simulated data in such cases: auto_compare_synthetic_empirical_Stim_ControlAmp.py
and auto_compare_synthetic_empirical_Stim_ControlLocation.py
Surrogate data are generated using random EZ hypothesis:
virtual_epileptic_seeg_ret_Control.py
,
STIM_virtual_epileptic_seeg_ret_Control.py
,
IIS_virtual_epileptic_seeg_ret_Control.py
The employed permutation test for statistical significance testing between virtual cohort and surrogate virtual data: permutation_test_comparison.py
Other files are used for managing the structure of the dataset in data_manager.py
or for plotting figures from the data in utils_figures
folder.