Transition of brain networks from an interictal to a preictal state preceding a seizure revealed by scalp EEG network analysis

  • Fali Li
  • Yi Liang
  • Luyan Zhang
  • Chanlin Yi
  • Yuanyuan Liao
  • Yuanling Jiang
  • Yajing Si
  • Yangsong Zhang
  • Dezhong Yao
  • Liang YuEmail author
  • Peng XuEmail author
Research Article


Epilepsy is a neurological disorder in the brain that is characterized by unprovoked seizures. Epileptic seizures are attributed to abnormal synchronous neuronal activity in the brain. To detect the seizure as early as possible, the identification of specific electroencephalogram (EEG) dynamics is of great importance in investigating the transition of brain activity as the epileptic seizure approaches. In this study, we investigated the transition of brain activity from interictal to preictal states preceding a seizure by combining EEG network and clustering analyses together in different frequency bands. The findings of this study demonstrated the best clustering performance of k-medoids in the beta band; in addition, compared to the interictal state, the preictal state experienced increased synchronization of EEG network connectivity, characterized by relatively higher network properties. These findings can provide helpful insight into the mechanism of epilepsy, which can also be used in the prediction of epileptic seizures and subsequent intervention.


Epileptic seizure EEG network K-medoids Preictal state Synchronization 



This work was supported by the National Natural Science Foundation of China (#61522105, #61603344, #81330032, #71601136, and #81771925), the Open Foundation of Henan Key Laboratory of Brain Science and Brain–Computer Interface Technology (No. HNBBL17001), and the Longshan academic talent research supporting program of SWUST (#17LZX692).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.Department of NeurologySichuan Academy of Medical Sciences and Sichuan Provincial People’s HospitalChengduChina
  3. 3.Department of NeurologyAffiliated Hospital of University of Electronic Science and Technology of ChinaChengduChina
  4. 4.School of Computer Science and TechnologySouthwest University of Science and TechnologyMianyangChina
  5. 5.School of Life Science and Technology, Center for Information in MedicineUniversity of Electronic Science and Technology of ChinaChengduChina

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