Computational analysis reveals amplified epileptogenic zone network markers during slow-wave sleep in focal epilepsy, highlighting sleep-dependent electrophysiological localization targets.
Analysis code accompanying Nadig et al., "Slow-wave sleep selectively amplifies network signatures of the presumed epileptogenic zone in focal epilepsy" Contents: electrode classification into anatomical regions and presumed epileptogenic / irritative / non-involved zones; automatic intracranial sleep staging and confidence-based epoch selection; the lab's general iEEG/MEG processing toolbox (subject and session bookkeeping, preprocessing, event/marker extraction, ICA-based artefact rejection, and connectivity calculation); group-level connectivity reduction; graph-theoretical metrics; FOOOF/specparam aperiodic exponent estimation; PALM permutation-test design construction for the zonal and interaction analyses; and the nested leave-one-subject-out elastic-net classifier with permutation testing. All scripts are deidentified and path-free: subject identifiers, file paths and site-specific settings have been removed, and each script takes its data as explicit input variables. Dependencies not included: FieldTrip, Brain Connectivity Toolbox, PALM, FOOOF/specparam (Python), SleepSEEG_models.mat Raw intracranial EEG and imaging data cannot be shared publicly under the applicable data protection regulations and the terms of the ethics approval;
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Vismitha Nadig (2026) studied this question.
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