Epilepsy is the most common neurological disease defined as a central nervous system disorder that characterized by recurrent seizures. While electroencephalography (EEG) an essential tool for monitoring epilepsy patients' brain activity and diagnosing epilepsy, Visual detection of EEG signal to identify epileptic seizures time-consuming approach might result in human error. Therefore, early pr...

Despite the success achieved in identifying mutations causing Mendelian forms of epilepsy, little progress has been made in illuminating variation contributing to the development of more common forms of the condition. The aim of this thesis was to improve methodology that would aid the detection of variation functional in the development and treatment of common forms of epilepsy. Attempted repl...

The progresses of neuroimaging have allowed an earlier detection of hypothalamic hamartoma in children presenting with gelastic or dacrystic seizures. Associated symptoms can include other types of seizures, precocious puberty, and behavioral or cognitive deterioration. Combination of all these features is not constant and, when present, their evolution may be variable. When epilepsy proves int...

Electroencephalographic signal is a representative signal that contains information about brain activity, which is used for the detection of epilepsy since epileptic seizures are caused by a disturbance in the electrophysiological activity of the brain. The prediction of epileptic seizure usually requires a detailed and experienced analysis of EEG. In this paper, we have introduced a statistica...

Epilepsy affects 1 in 150 children under the age of 10 and is most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared ability different machine learning algorithms trained with resting‑state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI anatomical scans were obtained for...