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 have developed an artificial neural network, one that allows us to mimic several aspects of the epileptic brain. Our model is based upon a specially designed neuron “cell”, and the network is formed in a manner that offers several degrees of flexibility in its formation: 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 epilepsy 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. Нe cause of most epilepsy cases is unknown. Few cases are genetically related, and some people develop epilepsy as a result of brain injury, stroke, brain tumor, or drug abuse. Recent research also connects epilepsy with autoimmune diseases. Нe diagnosis typically involves ruling out other conditions known to cause similar symptoms, such as syncope. Epilepsy is oÑ–en conÙ½rmed by electroencephalography (EEG), but a normal test is not enough to rule out the disease. Other than the actual seizure and the risks involved in it, the sudden and unpredictable nature of the seizure is one of the most disabling aspects of epilepsy. Нus Ù½nding a method capable of predicting epileptic seizures would open new therapeutic possibilities, and this can be attempted by analyzing network activity. Нe human brain is the most difficult organ in our body to experiment with, due to physiological and ethical reasons. Нis fact, along with the variability in epilepsy pathogenesis and the diوٴerence in epilepsy manifestation, is making clinical research very limited, which reduces the quality of care for epilepsy patients.