Mapping and mining interictal pathological gamma (30–100 Hz) oscillations with clinical intracranial EEG in patients with epilepsy

Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30–100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG (<100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) postsurgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain.

► Standard presurgical evaluation for epilepsy needs objective decision-support.
► Pattern-detection and data-mining provide objective decision-support for neurologists.
► Combining hypothesis-testing and detection-theory allows robust pattern-detection.
► Pathological gamma oscillations may partially identify seizure-generating brain.
► Treating brain with pathological oscillations and seizures may better help patients.