Epilepsy is one of the most serious neurological disorders, with a low rate of successful treatment, and pharmacoresistant epilepsy is a major health burden on society. Preventive treatment is one way to make treatment more efficient and is why there is a need for biomarkers capable of predicting the development of epilepsy during its earlier stages. Early in our experiments, we discovered pathological high-frequency oscillations (pHFOs), which are reliable biomarkers of epileptogenesis. They are generated by clusters of pathologically interconnected neurons (PIN clusters) and reflect bursts of population spikes. In this proposal, we plan to analyze the mechanisms of the formation of PIN cluster networks, and anticipate that this study will improve our understanding of the mechanisms of epileptogenesis (Aim 1). However, a significant limitation of pHFOs as biomarkers for clinical use is that they require the implantation of electrodes into the brain. The current proposal also focuses on the search for noninvasive biomarkers, which could potentially be translated to clinical application.
In Aim 2, we plan to investigate whether functional magnetic resonance imaging (fMRI) and diffusion tension imaging (DTI) parameters, such as fractional anisotropy (FA), are biomarkers of epileptogenesis. During data analysis, we will investigate whether changes of imaging parameters are better predictors of epileptogenesis than pHFOs. In our earlier publications we showed that pHFOs initially appear in the perilesional area.
In Aim 3, we will test the hypothesis that the suppression of neuronal activity within the perilesional area will prevent the development of epileptogenesis. For this purpose, we will apply a new, recently developed DREADD technology that suppresses the discharges of neurons after binding with the adenovirus attached channels. This approach might open a new approach to the prevention of epilepsy development and identify novel targets for interventions to treat, prevent, and cure epilepsy.
Current treatment of patients with epilepsy fails to control seizures in 30-40% of cases. There is no treatment to prevent epilepsy itself. We propose to discover new noninvasive biomarkers to predict the development of epilepsy using multidisciplinary electrophysiological and neuroimaging studies of rat models of chronic epilepsy, and to describe new targets for the prevention of epileptogenesis.
