PEACOC - Detecting and classifying a wide range of epileptiform activity patterns in rodents

Abstract

Epileptiform activity (EA) manifests in diverse patterns of hypersynchronous network activity. Fundamental research mostly addresses two extreme patterns, individual epileptiform spikes and seizures. We developed PEACOC to detect and classify a wide range of EA patterns in local field potentials. PEACOC delimits EA patterns as bursts of epileptiform spikes, and classifies these bursts according to spike load. In EA from kainate-injected mice, burst patterns displayed a continuum of spike loads. With PEACOC, we partitioned this continuum into bursts of high, medium and low spike load. High-load bursts resembled electrographic seizures. The EA patterns automatically retrieved by PEACOC were reproducible and comparable across animals and laboratories. PEACOC has been employed to diagnose the overall burden of EA in individual mice, and to describe epileptic dynamics at multiple time-scales. We here further report that the rate of high-load bursts was anti-correlated to granule cell dispersion in the dentate gyrus.