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| Content Provider | Springer Nature Link |
|---|---|
| Author | Guo, DaQing Xia, Chuan Wu, ShengDun Zhang, TianJiao Zhang, YangSong Xia, Yang Yao, DeZhong |
| Copyright Year | 2017 |
| Abstract | Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy, and provide insightful biological implications. |
| Starting Page | 995 |
| Ending Page | 1002 |
| Page Count | 8 |
| File Format | |
| ISSN | 16747321 |
| Journal | Science in China Series E: Technological Sciences |
| Volume Number | 60 |
| Issue Number | 7 |
| e-ISSN | 18691900 |
| Language | English |
| Publisher | Science China Press |
| Publisher Date | 2017-04-20 |
| Publisher Place | Beijing |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | partial epilepsy seizures dynamics Epileptor model slow permittivity variable stochastic fluctuations of permittivity coupling Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Engineering Materials Science |
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