Resources

De-identified data and reproduction code for a retrospective cEEG study of ictal-interictal continuum patterns and outcomes in 121 patients with toxic-metabolic encephalopathy (MGH, 2012-2017).

MATLAB code and de-identified data for six interpretable quantitative EEG features (amplitude, duration, sharpness, slow wave, asymmetry, field) combined to classify interictal epileptiform discharges (AUC ~0.83).

R (mstate) and MATLAB code with de-identified data for a 3-state multistate survival model of time-dependent seizure risk on continuous EEG in critically ill patients (665 consecutive cEEGs).

Twenty epileptologists diagnosed 50 suspected-seizure vignettes on two occasions; a Bayesian hierarchical model decomposes diagnostic variability into signal and noise. Code + de-identified data.

Ultrafast EEG template matching under Dynamic Time Warping for rapid annotation of interictal epileptiform discharges, with an open-source Python implementation and a demo dataset.

A continuous, EEG-based index of encephalopathy severity (NESI) that maps RASS, GCS, CAM-S, and ICANS onto one physiological axis. Includes 10-minute EEG segments, MORGOTH features, trained models, derived tables, and the full analysis code.

Code and dataset used for the development of algorithms that automatically detect the frequency and spatial extent of epileptiform activity, specifically for LPD, GPD, LRDA, GRDA.

This study evaluated a technology-enhanced, retrieval-based program for teaching neurology residents to identify interictal epileptiform discharges (IEDs).

Using sleep EEG to predict future health outcomes.

Transcranial Magnetic Stimulation in Alzheimer's disease