Abstract
Epilepsy is known since ancient history and affects the lives of millions. Due to various physiological and ethical reasons, it is extremely difficult to conduct thorough examination of the human brain. As a result, even after millennia of identifying epilepsy and treating it, we know relatively little about what is causing epilepsy and what is the best way to manage it. In order to meet this challenge, we develop an artificial neural network, one that allows us to mimic several aspects of the epileptic brain. Our model is based on a specially designed neuron “cell”, and the network is formed in a manner that offers several degrees of flexibility in its formation. This allows us to control the formation of the brain model in several levels: starting with the neurotransmitter and up to properties of the entire network. We compare the activity of our model to that recorded from real brains of real patients, and demonstrate resemblance in key properties of the neuronal activity. Using this artificial network offers an easier experimental platform that manifests epileptic-like behavior, which allows to investigate the underlying mechanisms causing epilepsy on one hand, and to examine potential treatments on the other hand. The model can be adopted to manifest other physiological properties that can be suitable for modeling other neurological disorders.
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