  Epilepsy is a neurological disease characterized by recurrent and spontaneous
seizures. It affects approximately 50 million people worldwide. In majority of
the cases accurate diagnosis of the disease can be made without using any
technologically advanced techniques and seizures are controlled using standard
treatment in the form of regular use of anti-epileptic drugs. However,
approximately 30% of the patients suffer from medically refractory epilepsy,
wherein seizures are not controlled by the use of anti-epileptic drugs.
Understanding the mechanisms underlying these forms of drug resistant epileptic
seizures and the development of alternative effective treatment strategies is a
fundamental challenge in modern epilepsy research. In this context, the need
for integrative approaches combining various modalities of treatment strategies
is high. Computational modeling has gained prominence in recent years as an
important tool for tackling the complexity of the epileptic phenomenon. In this
review article we present a survey of different computational models for
epilepsy and discuss how computer models can aid in our understanding of brain
mechanisms in epilepsy and the development of new epilepsy treatment protocols.

Quantitative Methods;Neurons and Cognition