# AI-Based Electroencephalogram Analysis in Rodent Models of Epilepsy: A Systematic Review
###### Abstract
Although humans and rodents such as mice have different neurobiologies, mice are frequently used to model human neurological disorders [19; 20], and recently, rodents (rats and mice) have been prioritised for epilepsy research [18]. Electroencephalography (EEG), introduced by [PERSON], is a clinical procedure for reading spontaneous neural activities [21]. The ability to read the electrical signals in the brain can provide insight into the abnormalities that may occur in the brain. It may be useful in assisting with the diagnosis or assessing the presence of comorbidities in various neurological disorders. With the use of EEG, neurologists can understand the alterations in the human brain that accompany epileptic seizures. Its usage extends to rodent models of epilepsy. The analysis of the rodent brain fluctuations in rodent models of epilepsy uncovers the disease development, leading to understanding disease mechanisms and evaluating the effects of ASDs and experimental treatments. The waveforms in EEG activity that characterise seizures are known as epileptiform discharges [22]. Epileptiform discharge is a transient burst of spikes, polyspikes, and polyspike-wave and spike-wave complexes with varying shapes and amplitudes indicative of cortical hyperexcitability and disruption [22; 23]. Generally, epileptiform discharge is categorised into four states: interictal, preictal, ictal, and postictal. * Interictal discharge: Interictal spikes are the intermittent neurological discharge observed between seizures in patients and animals with epilepsy [24; 25]. Interictal spikes are noncoincidental [26] but relatable to seizures, and they are quantified as the most reliable epileptogenic biomarker [27; 28]. * Preictal discharge: The preictal state is the abnormal neural discharge just before the manifestation of a seizure event, where a patient may feel the presence of seizure aura, which are physiological changes such as muscle twitches and gastrointestinal upset [29]. The temporal and spatial changes of the preictal discharge correlate with seizure onset; towards the onset of seizure, the amplitude of preictal discharge increases, while the interval decreases [30]. Thus, understanding and detecting the preictal spike mechanism can predict the next seizure episode [31]. * Ietal discharge: This is the most symptomatic and shortest phase of the epileptiform discharge. The ictal spike represents the critical event of a seizure that characterises an active epileptic condition. * Postictal discharge: This state of the brain describes the abnormal neurological performance that begins at the end of a seizure episode; this state may last for hours before the resumption of the neural baseline activity [32]. Postictal discharge receives less attention than the interictal and preictal states. Nevertheless, the postictal characteristics may assist in distinguishing epileptic and non-epileptic seizures [33]  
Epileptiform discharge identification includes seizure detection (the identification of ictal discharges), seizure prediction (the identification of preictal discharges), and seizure type classification (the categorisation of the different types of seizures). Increasingly, epilepsy research is moving towards determining the disease-modifying effects of drugs, which requires persistent assessment of brain activities, including epileptiform discharges, through long-term recording of EEG in animal models of epilepsy [34]. Traditionally, detecting epileptiform discharges can be achieved through visual analysis of the long-term EEG signal by a team of epileptologists. However, there are certain drawbacks to the visual identification of epileptiform discharges in long-term EEG recordings. In addition to the time spent reviewing the EEG recording, the subjective seizure identification between epileptologists on the same EEG recording due to various seizure morphologies and the similarity of seizure patterns with noise and artefacts is another major challenge.