Abstract

One of the main tools for diagnosing and studying epilepsy is electroencephalography (EEG), which can be used right after a possible first seizure. The most settled biomarker of epilepsy, in the event that seizures are not recorded, are interictal epileptiform releases (IEDs). However, in clinical practice, IEDs are not always present, and the EEG may appear normal despite an underlying epileptic disorder, making the diagnosis of the disease frequently challenging. As a result, it would be extremely beneficial to discover additional biomarkers that can accurately predict whether a person has epilepsy even in the absence of obvious epileptic activity. These biomarkers have the potential to shorten the period of diagnostic uncertainty and, as a result, reduce the risk of seizures. EEG features other than IEDs appear to be the only ones capable of distinguishing between epilepsy, which has a risk of > 60% of recurrent seizures, and other (pathological) conditions at this time. The purpose of this narrative review is to provide an overview of the methods used to identify the EEG-based biomarker candidates for epilepsy.