Abstracts

Rationale: The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Centre without walls is an NIH funded preclinical multicenter consortium that includes the University of Eastern Finland (Site 1), Monash University (Site 2) and the University of California Los Angeles (Site 3). Our objective is to create a platform for evaluating biomarkers and testing new antiepileptogenic treatments for post-traumatic epilepsy (PTE) using the lateral fluid percussion injury (FPI) model in rats. As only 30-50% of rats with severe lateral FPI develop PTE by 6 months post-TBI, prolonged video-EEG monitoring is crucial to identify animals with PTE. Here we standardized automated seizure detection for phenotyping of PTE in a rat model of TBI across three study sites. Methods: TBI was induced using lateral FPI in adult male Sprague-Dawley rats aged 11-12 weeks. Animals were divided into two cohorts. The long-term EEG follow-up Cohort 1 was implanted with EEG electrodes within 24 h after the injury and the MRI follow-up Cohort 2 at 6 months after LFPI. Four cortical epidural screw electrodes (2 ipsilateral, 2 contralateral) and three intracerebral bipolar electrodes were implanted (septal CA1 and the dentate gyrus, layers II and VI of the cortex both anterior and posterior to the injury site).  During the 7^th post-TBI month animals underwent 4 weeks of video-EEG recordings for diagnosis of PTE. Results: So far, 4-wk continuous video-EEG recordings have been collected from 63 rats in Site 1, 64 rats in Site 2, and 19 rats in Site 3, corresponding to a total of over 25,000 h of video-EEG recordings. The Kuopio algorithm detects seizures by searching all EEG channels for temporally linked power peaks. The Melbourne algorithm detects seizures in single and multiple channels using an original technique of short term spectral analysis that calculates the Fourier transform within a specific frequency band with arbitrary frequency resolution. The positive hits from both automated algorithms were confirmed by a blinded investigator. The Kuopio algorithm had 100% sensitivity and 5% specificity and the Melbourne algorithm 100% sensitivity and 12% specificity in seizure detection. Analysis of the EpiBios4Rx EEG recordings are ongoing, and the incidence of PTE and seizure types in the EpiBios4Rx animal cohort will be reported. Conclusions: Our standardized seizure detection algorithm tools provide high sensitivity for long-term EEG recordings from lateral LFPI model of PTE. Automated seizure detection will improve the efficiency and rigor in pre-clinical biomarker and therapy discovery for post-traumatic epileptogenesis and PTE. Funding: Supported by NINDS Center without Walls, U54 NS100064 (EpiBioS4Rx).