Article published by Medical Xpress
Epilepsy is a serious neurological disease. More than 50% patients experience onset during childhood. Effective treatment of epilepsy can prevent serious long-term effects such as brain dysfunction.
Recent studies have shown that epilepsy is a brain network disease. The construction of epilepsy networks is therefore significant to the mechanism research as well as clinical diagnosis and treatment of epilepsy.
Researchers from the Suzhou Institute of Biomedical Engineering and Technology (SIBET) of the Chinese Academy of Sciences recently proposed a whole-brain dynamic resting-state functional network (DFN) computation method to better construct epilepsy brain networks. The method is based on resting-state, low-density electroencephalogram (EEG) recordings in scalp space.
Their study was published in IEEE Journal of Biomedical and Health Informatics.
At present, functional magnetic resonance imaging (fMRI) and EEG are commonly used to construct the epilepsy brain networks. EEG is non-invasive, wearable, cost-effective, and especially suitable for children’s brain function monitoring.
Benign epilepsy with centrotemporal spikes (BECTS) is the most common type of epilepsy among children. Both fMRI and EEG source imaging (ESI) studies have indicated that BECTS is associated with static resting-state functional network (SFN) alterations (e.g., decreased global efficiency) in source space.