High-frequency oscillations as biomarkers of ictogenesis and epileptogenesis

Epilepsy is a severe neurological disorder characterized by recurrent seizures that affect 1% of the population worldwide. Traumatic brain injury (TBI) is the primary cause of the acquired epilepsy that 16% of severe TBIs can develop to post-traumatic epilepsy (PTE). The biomarkers that can objectively indicate the epileptogenesis and ictogenesis of the brain tissues are critically crucial for clinical treatments to prevent seizures and the development of PTEs. High-frequency oscillations (HFOs) in the 80~500 Hz range recorded in animal and human electroencephalography (EEG) studies are believed to reflect the ictogenesis and epileptogenesis of brain tissues. This project will develop a machine-learning algorithm to detect animal HFOs automatically. With the detected HFOs, we will conduct the quantitative analysis of HFOs in an animal cohort with TBIs. The alterations of HFOs among different conditions or treatments and the longitudinal analysis of HFOs will be investigated to evaluate whether HFOs are biomarkers for ictogenesis and epileptogenesis of PTE.