Neural mechanisms and modulations of epilepsy: from experimental and clinical data to computational modelling evidence

Epilepsy is a chronic noncommunicable disorder of the brain, mainly characterized by a long-term risk of recurrent seizures. Statistically, there are more than 50 million epileptic patients in the world, making it rank the second highest morbidity disease occurring in the central nervous system. In clinics, epileptic seizures are divided into several types, which vary from the briefest lapses of attention or muscle jerks to severe and prolonged convulsions. Accumulating evidence suggests long-term recurrent unprovoked seizures can cause seriously cognitive impairment, such as memory deficits, learning disabilities, behavioral problems, and poor social outcome. Understanding how epileptic seizures arise as well as their modulation mechanisms in the brain is therefore an important topic in neuroscience. Although the genesis of epilepsy is believed to be highly associated with abnormal, excessive or hypersynchronous discharges of neurons in the brain, so far the detailed neural mechanisms and modulations of different types of epilepsy and seizures still remain unknown and debate.

This research topic of Frontiers in Computational Neuroscience aims at investigating neural mechanism and modulations of epilepsy from experimental, clinical and computational approaches. We welcome research and methodology papers, mini-reviews, conceptual generalizations and opinions on the following issues:
1. Statistics analysis of experimental and clinical data on epilepsy
2. Multiscale computational models of epilepsy using experimental or clinical data
3. Lesion localization from clinical data
4. Dynamical modelling and transition mechanism of epilepsy
5. Modulation mechanisms of epilepsy
Other relevant issues on epilepsy are also welcome. Studies by combining either experimental or clinical data and computational modelling are of particular encouraged to submit to this research topic.