A simple, automated method of seizure detection in mouse models of temporal lobe epilepsy

Abstract

The lack of preventive and disease modifying therapies for temporal lobe epilepsy (TLE) is a major unmet medical need. Search for such therapies utilize mouse models and require detection of seizures in electroencephalography (EEG) recordings. The labor-intensive nature of reviewing EEGs spanning many weeks underscores the need for a method of automated detection. Here we report a simple automated method of detecting seizures in long term EEG recordings from electrodes implanted in the hippocampus in animal models of TLE. We utilize a 2-pronged approach that relies on the increase in power within the gamma band range (20-50hz) during the seizure followed by suppression of activity following the seizure (post-ictal suppression [PIS]). We demonstrate the utility of this method for detecting seizures in hippocampal and amygdala EEG recordings from multiple models of TLE.

Keywords: Automated seizure detection; Post-ictal suppression; Rodent epilepsy models.