Model based prediction of post epilepsy surgery

• Main Author: Jain Prateek
• Other Authors: Udayappan Udhayakumari
• Format: Theses and Dissertations
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
• Online Access: http://hdl.handle.net/10356/55322
• Institution: Nanyang Technological University

In about 30% of epileptic patients, epilepsy is not controlled by medication. For some of these patients surgery is an option. However, the surgery requires accurate determination of the seizure onset zone. So the prediction of reliable epileptic brain area is of crucial importance. Here, a dynamic model is developed to predict the seizure onset zone and outcome of surgery in patients. The model uses the inter-ictal ECoG data as a connectivity to predict the seizure onset zone in the brain. The examination of betweenness centrality of the node gives the strong correlation with the seizure onset zone. Betweenness centralization of the network depends on the seizure onset zone, if seizure onset is removed the betweenness centralization of the network decreases. Increase in betweenness centralization of the network is also associated with the seizure onset zone. It is shown that the probability of seizure occurrence is less with decrease in betweenness centralization ofthe network. Hence, the model can be used to predict the seizure onset zone and outcome of surgery.