Udaya K. Seneviratne

This paper investigates how epilepsy patients respond to photic stimulation, finding differences in EEG biomarkers that suggest cortical excitability changes associated with seizure states.

The paper uses a mathematical model to analyze EEG data from people with epilepsy and identifies cortisol levels and sleep stages as factors explaining daily variability in epileptiform discharges.

This study analyzes long-term intracranial EEG recordings to examine variability and circadian patterns of high-frequency activity and epileptiform spikes in patients with drug-resistant epilepsy.

This paper presents a deep learning algorithm for computer-assisted EEG review in idiopathic generalized epilepsy, achieving high sensitivity and reducing human review time by 80%-99%.