Abstracts

Rationale: Recurrent epileptic seizures interrupt normal brain activity, and this abnormal electrographic activity can be visualized using electroencephalograms (EEGs). Epilepsy treatment is complicated by the fact that patients with similar phenotypes and seizure classifications do not respond similarly to the same treatments, suggesting subtler differences exist that cannot be accounted for by our currently-limited classification system. Investigating seizure onset and offset patterns in models of epilepsy and their response to anti-seizure medications may provide additional metrics to quantify drug efficacy and could lead to improvements in how epilepsy is classified and treated.

Methods: Mice were injected with kainic acid into the basolateral amygdala and observed with 24/7 video and EEG recordings (West et al., 2022, Exp. Neurol.). We analyzed seizure frequency, duration, and dynamotype for 639 spontaneous seizures from 14 animals in the 240 mg/kg valproic acid (VPA) cohort, and 824 seizures from 21 animals in the 40mg/kg phenytoin (PHT) cohort. Onset and offset patterns, or “dynamotypes,” of each seizure were visually categorized in a randomized, blinded fashion by trained human raters for VPA, and by a custom machine learning script for PHT. There are three onset dynamotypes: SupH, characterized by increasing amplitude; SNIC, characterized by increasing frequency; and SubH, characterized by arbitrary patterns in amplitude and frequency. There are three offsets: SupH—decrease in amplitude, SNIC—decrease in frequency, and FLC—arbitrary amplitude and frequency.

Results: For the PHT Cohort, SubH onset was dominant in both baseline and drug dosing but no significant change in onset occurred during dosing (ANOVA, ns). For the VPA cohort, dominant onset was SubH at baseline, and did not significantly change following VPA. FLC offset was the dominant dynamotype during baseline, but SNIC significantly increased (ANOVA, p = 0.04) and dominated during VPA dosing. Figure 1 summarizes PHT onset and VPA offset findings.

Conclusions: The IAK model is resistant to PHT but sensitive to VPA. Seizure frequency during vehicle and PHT were not significantly different (Wilcoxon Test, ns). Seizure frequency significantly decreased during VPA dosing (Wilcoxon Test, p = 0.0001). Previously we have shown that SNIC offset, characterized by decreasing spike frequency before termination, became the dominant dynamotype during VPA dosing while FLC significantly decreased (Wilcoxon Test, p = 2.1E-5). In contrast, we did not observe any dynamotype changes in the PHT cohort. We hypothesize that seizures with SNIC offset are pharmacoresistant to valproic acid, and that dynamotype will not be altered by drugs that the IAK model is resistant to.

Funding: This project has been partly funded by Federal funds from the National Institute of Neurological Disorders and Stroke, Epilepsy Therapy Screening Program, National Institutes of Health, and Department of Health and Human Services, under Contract No. HHS 75N95022C00007. Also by: the Undergraduate Research Opportunities Program at the University of Utah, and NIH NINDS: F32 NS114322 awarded to Daria Anderson.