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• W2912274078 abstract "Characterizing the synchronous changes of epileptic seizures in different stages between different regions is profound to understand the transmission pathways of epileptic brain network and epileptogenic foci. There is currently no adequate quantitative calculation method for describing the propagation pathways of electroencephalogram (EEG) signals in the brain network from the short and long term. The goal of this study is to explore the innovative method to locate epileptic foci, mapping synchronization in the brain networks based on EEG. Mutual information was used to analyze the short-term synchronization in the full electrodes; while nonlinear dynamics quantifies the statistical independencies in the long –term among all electrodes. Then graph theory based on the complex network was employed to construct a dynamic brain network for epilepsy patients when they were awake, asleep and in seizure, analyzing the changing topology indexes. Epileptic network achieved a high degree of nonlinear synchronization compared to awake time. and the main path of epileptiform activity was revealed by searching core nodes. The core nodes of the brain network were in connection with the onset zone. Seizures always happened with a high degree of distribution. This study indicated the path of EEG synchronous propagation in seizures, and core nodes could locate the epileptic foci accurately in some epileptic patients." @default.
• W2912274078 created "2019-02-21" @default.
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• W2912274078 date "2019-01-01" @default.
• W2912274078 modified "2023-10-18" @default.
• W2912274078 title "Epileptic foci localization based on mapping the synchronization of dynamic brain network" @default.
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• W2912274078 doi "https://doi.org/10.1186/s12911-019-0737-8" @default.
• W2912274078 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6354332" @default.
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• W2912274078 hasPublicationYear "2019" @default.
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