| Literature DB >> 35401872 |
Wei Wei1,2, Zhiyuan Zhang2, Nan Chen2, Min Zuo2, Tao Yu3.
Abstract
Epilepsy is a neurological disorder resulting from a sudden development of synchronous firing in a massive group of neurons. For the particularity of the epilepsy, a neural mass model (NMM) is commonly utilized to understand and simulate the mechanism and evolution of the epilepsy. In this paper, based on a multi-coupling NMM and real EEGs of an epileptic mouse, a computational epileptic model is established to simulate the abnormal discharges of a mouse during seizures. Thus, rather than make animal experiments directly, numerical tests can be performed first. It reduces risks and helps improve the closed-loop neuromodulation. In addition, considering that no epileptic model can be utilized for neuromodulation in clinic, and even if a model exists, it still cannot describe the dynamics of the epilepsy faithfully, a scalable observer bandwidth and phase leading active disturbance rejection control (SOB-PLADRC) is proposed. Accordingly, a timelier and more accurate total disturbance estimation can be obtained by a scalable observer bandwidth and phase leading extended state observer, and an expected closed-loop neuromodulation can be realized without an accurate epileptic model. Numerical simulations based on the established model also show that the SOB-PLADRC suppresses seizures best among the PI and other active disturbance rejection approaches. More powerful disturbance rejection ability and more satisfactory closed-loop neuromodulation make the SOB-PLADRC more promising in the seizure control.Entities:
Keywords: Active disturbance rejection control; Epilepsy; Leading phase; Neural mass model; Scalable observer bandwidth
Year: 2021 PMID: 35401872 PMCID: PMC8934905 DOI: 10.1007/s11571-021-09704-y
Source DB: PubMed Journal: Cogn Neurodyn ISSN: 1871-4080 Impact factor: 5.082