Detection of the Change in Characteristics of Self-Grooming by the Neural Network in the Latent Period of the Rat Kainate Epilepsy Model

It is widely hypothesized that there is a seizure-free state, termed the “latent period,” between brain injury and the onset of symptomatic epilepsy. During the latent period, structural and functional alterations gradually mediate epileptogenesis. Kainate (KA) induces epilepsy in rats in a manner similar to that induced by human epilepsy. During the model's latent period, rats administered KA-exhibited innate behaviour such as self-grooming. We previously reported that self-grooming bouts are facilitated during the latent period in this model. Here, we investigated self-grooming changes during the latent period of the KA rat model. We analysed various parameters of self-grooming – including duration, number, and percentage of correct transitions (CT%). Self-grooming bouts included a syntactic chain consisting of CT. CT% was defined as the ratio of the number of CT scans to the total number of transitions. The results showed that CT%, number, and duration were significantly increased during the latent period in KA rats. We attempted to mine the features that detect the latent period using a neural network. Our results suggest that the CT% of self-grooming will detect changes in the latent period in the KA rat epilepsy model.