Abstracts

Rationale: Epilepsy is a disease that affects neurons in the brain, disrupting its activity and causing seizures. In order to improve the development of anti-epileptic drugs, various mouse models of epilepsy are necessary to study the disease. In this study, we specifically study the dynamics of recurrent seizures over the course of epileptogenesis in the intra-amygdala kainic acid (IAK) model of mesial temporal lobe epilepsy. Previously recorded electroencephalograms (EEGs) of IAK mice from 90 days were observed and categorized by the shape of their seizure onset and offset, referred to as dynamotypes, based on the patterns or lack of patterns in amplitude and frequency of the EEG signal.

Methods: Eighteen mice were injected with kainic acid into the basolateral amygdala and then were observed for 90-days post-injection; 24/7 video and EEG recordings were obtained (West et al., 2022, Exp. Neurol.). The seizures were then analyzed using custom software in MATLAB and manually categorized based on pattern of onset and offset dynamotype based on previously published work (Saggio et al., 2020, eLife). There are 3 different onset dynamotypes where EEG is characterized by increasing amplitude (SupH), by increasing frequency (SNIC), or by arbitrary patterns in both amplitude and frequency (SubH). Similarly, there are 3 offsets where EEG is characterized in decreasing amplitude (SupH), by decreasing frequency (SNIC), or by arbitrary patterns in amplitude and frequency (FLC). Seizure frequencies and duration were also obtained.

Results: A total of 709 seizures were recorded for 90-days post kainic acid injections in 18 mice; mice experienced an increase in spontaneous seizures as the study progressed. There were no significant differences found between latent period (the day that the mice had their first seizure) and weekly average seizure frequency (t-test, p=0.3822) or between latent period and weekly average seizure duration (t-test, p=0.113). Early in epileptogenesis, 71% of onset dynamotypes did not have a specific pattern (SubH), but in the last 30 days of monitoring, the presence of SubH was significantly reduced to 35% (ANOVA, p=0.0183). Similarly, 79% of offset dynamotypes had arbitrary amplitude and frequency patterns (FLC) in the first 30 days, which then significantly decreased to 43% in the last 30 days (ANOVA, p=0.0005).

Conclusions: We found that onset and offset dynamotypes, based on the patterning of amplitude or frequency, of spontaneous seizures changed in IAK mice over the course of 90 days post-injection. The majority of onset and offset dynamotypes started out as SubH and FLC, which have irregular patterns in amplitude and frequency, but shifted in the last 30 days to more patterned dynamotypes such as SubH (patterns in amplitude) and SNIC (patterns in frequency). We hypothesize this increase in patterning of onset and offset dynamotypes later in the course of epilepsy indicates more stereotyped seizure networks over the course of epilepsy. In the future, we will test whether dynamotypes may change in the presence of anti-epileptic drugs or whether a drug is more effective when there is a specific dominant dynamotype present.

Funding: University of Utah funds to K.S.W.