Rezvani-Ardakani Samira, Mohammad-Ali-Nezhad Sajad, Ghasemi Reza
Department of Electrical & Electronics Engineering, University of Qom, Qom, Iran.
Department of Electrical & Electronics Engineering, University of Qom, Qom, Iran.
Comput Methods Programs Biomed. 2020 Oct;195:105665. doi: 10.1016/j.cmpb.2020.105665. Epub 2020 Jul 22.
Epilepsy is a dynamic disease of neuronal networks and epileptic activity in the brain should be suppressed quickly in the shortest possible time with minimum control signal. Thus, a closed-loop feedback control by using the fixed-time integral super-twisting sliding-mode controller via an optogenetic method is employed for suppressing seizures in the Pinsky-Rinzel (PR) model as a dynamic model of the hippocampus CA3 region where epileptic seizures occur. The control signal is applied to the PR model through the ChR2 channel model in the form of light photons using the optogenetic method. The present study aimed to determine the controller robustness against parameter changes and disturbances in order to reduce the control time, approach the zero tracking error of the normal desired state in a fixed time, and finally, converge the epileptic state to the normal desired state.
In order to apply the control signal to the Pinsky-Rinzel model in the optogenetic method, the dynamic model of the ion current generated by channelrhodopsin 2 (ChR2) as a light-sensitive protein model in the optogenetic method was first applied to the PR model. Then, a fixed-time integral super-twisting sliding-mode controller was designed for the system, which is the combination of PR and ChR2 models.
After applying the proposed controller, the simulation results indicated that the control signal was -0.7 mV, the tracking error of the normal desired state could reach zero within 1.5 milliseconds, and the problems of singularity and chattering were solved.
A reduction occurred in the control signal reduced regarding the objectives of the study and comparing the proposed controller with the classical sliding-mode controller. Thus, this method can produce a safe control input for brain. In addition, both types of sliding mode controllers are robust against the parameters variations and external disturbances. Thus, they are superior to non-robust and simple controllers. Finally, based on the results, the validity of the fixed-time integral super-twisting sliding mode controller is confirmed for epilepsy control.
癫痫是一种神经网络的动态疾病，大脑中的癫痫活动应以最小的控制信号在尽可能短的时间内迅速得到抑制。因此，通过光遗传学方法利用固定时间积分超扭曲滑模控制器进行闭环反馈控制，用于抑制作为癫痫发作发生的海马CA3区动态模型的平斯基 - 林泽尔（PR）模型中的癫痫发作。控制信号通过光遗传学方法以光量子的形式通过ChR2通道模型施加到PR模型上。本研究旨在确定控制器针对参数变化和干扰的鲁棒性，以减少控制时间，在固定时间内接近正常期望状态的零跟踪误差，并最终使癫痫状态收敛到正常期望状态。
为了以光遗传学方法将控制信号应用于平斯基 - 林泽尔模型，首先将作为光遗传学方法中光敏蛋白模型的通道视紫红质2（ChR2）产生的离子电流动态模型应用于PR模型。然后，为该系统设计了一个固定时间积分超扭曲滑模控制器，该系统是PR和ChR2模型的组合。
应用所提出的控制器后，仿真结果表明控制信号为 -0.7 mV，正常期望状态的跟踪误差可在1.5毫秒内达到零，并且解决了奇异性和抖振问题。
就研究目标而言，控制信号有所降低，并且将所提出的控制器与经典滑模控制器进行了比较。因此，该方法可为大脑产生安全的控制输入。此外，两种类型的滑模控制器对参数变化和外部干扰均具有鲁棒性。因此，它们优于非鲁棒和简单的控制器。最后，基于结果，证实了固定时间积分超扭曲滑模控制器用于癫痫控制的有效性。
