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Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.
Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng.
Afiliação
  • Zhang L; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.
  • Liang Y; Department of Neurology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's HospitalChengdu, China.
  • Li F; Department of Neurology, Affiliated Hospital of University of Electronic Science and Technology of ChinaChengdu, China.
  • Sun H; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.
  • Peng W; Department of Neurology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's HospitalChengdu, China.
  • Du P; Department of Neurology, Affiliated Hospital of University of Electronic Science and Technology of ChinaChengdu, China.
  • Si Y; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.
  • Song L; Department of Neurology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's HospitalChengdu, China.
  • Yu L; Department of Neurology, Affiliated Hospital of University of Electronic Science and Technology of ChinaChengdu, China.
  • Xu P; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.
Front Comput Neurosci ; 11: 77, 2017.
Article em En | MEDLINE | ID: mdl-28867999
ABSTRACT
The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Comput Neurosci Ano de publicação: 2017 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Comput Neurosci Ano de publicação: 2017 Tipo de documento: Article País de afiliação: China