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基于参考信号跟踪的失神发作闭环控制器。

Closed-loop controller based on reference signal tracking for absence seizures.

机构信息

School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China.

出版信息

Sci Rep. 2022 Apr 25;12(1):6730. doi: 10.1038/s41598-022-10803-x.

Abstract

Absent epilepsy is a kind of refractory epilepsy, which is characterized by 2-4 Hz spike and wave discharges (SWDs) in electroencephalogram. Open-loop deep brain stimulation (DBS) targeting the thalamic reticular nucleus (TRN) is an effective method to treat absent epilepsy by eliminating SWDs in the brain. Compared with open-loop DBS, closed-loop DBS has been recognized by researchers for its advantages of significantly inhibiting seizures and having fewer side effects. Since traditional trial-and-error methods for adjusting closed-loop controller parameters are too dependent on the experience of doctors, in this paper we designed two proportional integral (PI) controllers based on the basal ganglia-cortical-thalamic model, whose PI parameters are calculated from the stability of the system. The two PI controllers can automatically adjust the frequency and amplitude of DBS respectively according to the change of the firing rate detected by substantia nigra pars reticulata (SNr). The parameters of the PI controller are calculated based on the Routh-Hurwitz stability criterion of a linear system which transformed by the original system using controlled auto-regressive (CAR) model and recursive least squares (RLS) method. Numerical simulation results show that both PI controllers significantly destroy the SWDs of the cerebral cortex and restore it to the other two normal discharge modes according to the different target firing rate, which supplies a promising brain stimulation strategy.

摘要

失神癫痫是一种难治性癫痫,其脑电图特征为 2-4Hz 棘慢波放电(SWD)。针对丘脑网状核(TRN)的开环深部脑刺激(DBS)是通过消除大脑中的 SWD 来治疗失神癫痫的有效方法。与开环 DBS 相比,闭环 DBS 因其具有显著抑制癫痫发作和副作用少的优点而受到研究人员的认可。由于传统的闭环控制器参数调整试错方法过于依赖医生的经验,因此本文设计了两种基于基底节-皮质-丘脑模型的比例积分(PI)控制器,其 PI 参数是根据系统的稳定性计算得出的。这两个 PI 控制器可以根据检测到的黑质网状部(SNr)的放电率变化,自动调整 DBS 的频率和幅度。PI 控制器的参数是根据受控自回归(CAR)模型和递归最小二乘(RLS)方法对原始系统进行变换后的线性系统的劳斯-胡尔维茨稳定性准则计算得出的。数值模拟结果表明,这两个 PI 控制器都能根据不同的目标放电率显著破坏大脑皮层的 SWD,并将其恢复为另外两种正常放电模式,为脑刺激策略提供了一种有前途的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eab7/9038751/81a5acc77d7e/41598_2022_10803_Fig1_HTML.jpg

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