Phase Synchronization Dynamics of Neural Network during Seizures

المؤلفون المشاركون

Zhang, Pu-Ming
Liu, Hao

المصدر

Computational and Mathematical Methods in Medicine

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-9، 9ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-10-15

دولة النشر

مصر

عدد الصفحات

9

التخصصات الرئيسية

الطب البشري

الملخص EN

Epilepsy has been considered as a network-level disorder characterized by recurrent seizures, which result from network reorganization with evolution of synchronization.

In this study, the brain networks were established by calculating phase synchronization based on electrocorticogram (ECoG) signals from eleven refractory epilepsy patients.

Results showed that there was a significant increase of synchronization prior to seizure termination and no significant difference of the transitions of network states among the preseizure, seizure, and postseizure periods.

Those results indicated that synchronization might participate in termination of seizures, and the network states transitions might not dominate the seizure evolution.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Liu, Hao& Zhang, Pu-Ming. 2018. Phase Synchronization Dynamics of Neural Network during Seizures. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1131773

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Liu, Hao& Zhang, Pu-Ming. Phase Synchronization Dynamics of Neural Network during Seizures. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1131773

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Liu, Hao& Zhang, Pu-Ming. Phase Synchronization Dynamics of Neural Network during Seizures. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1131773

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1131773