Wang JiaYi, Yang XiaoLi, Sun ZhongKui
1College of Mathematics and Information Science, Shaanxi Normal University, Xi'an, 710062 People's Republic of China.
2Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, 710072 People's Republic of China.
Cogn Neurodyn. 2018 Dec;12(6):625-636. doi: 10.1007/s11571-018-9498-9. Epub 2018 Aug 12.
Excessive synchronization of neurons in cerebral cortex is believed to play a crucial role in the emergence of neuropsychological disorders such as Parkinson's disease, epilepsy and essential tremor. This study, by constructing a modular neuronal network with modified Oja's learning rule, explores how to eliminate the pathological synchronized rhythm of interacted busting neurons numerically. When all neurons in the modular neuronal network are strongly synchronous within a specific range of coupling strength, the result reveals that synaptic plasticity with large learning rate can suppress bursting synchronization effectively. For the relative small learning rate not capable of suppressing synchronization, the technique of nonlinear delayed feedback control including differential feedback control and direct feedback control is further proposed to reduce the synchronized bursting state of coupled neurons. It is demonstrated that the two kinds of nonlinear feedback control can eliminate bursting synchronization significantly when the control parameters of feedback strength and feedback delay are appropriately tuned. For the former control technique, the control domain of effective synchronization suppression is similar to a semi-elliptical domain in the simulated parameter space of feedback strength and feedback delay, while for the latter one, the effective control domain is similar to a fan-shaped domain in the simulated parameter space.
大脑皮层中神经元的过度同步被认为在帕金森病、癫痫和特发性震颤等神经心理障碍的发生中起关键作用。本研究通过构建具有修正奥贾学习规则的模块化神经元网络，从数值上探索如何消除相互作用的爆发性神经元的病理性同步节律。当模块化神经元网络中的所有神经元在特定耦合强度范围内强烈同步时，结果表明，具有大学习率的突触可塑性可以有效抑制爆发同步。对于相对较小的、无法抑制同步的学习率，进一步提出了包括微分反馈控制和直接反馈控制在内的非线性延迟反馈控制技术，以降低耦合神经元的同步爆发状态。结果表明，当反馈强度和反馈延迟的控制参数得到适当调整时，这两种非线性反馈控制都能显著消除爆发同步。对于前一种控制技术，有效同步抑制的控制域在反馈强度和反馈延迟的模拟参数空间中类似于一个半椭圆域，而对于后一种控制技术，有效控制域在模拟参数空间中类似于一个扇形域。
