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控制神经元水平群体模型中的同步

Controlling synchronization in a neuron-level population model.

作者信息

Chakravarthy Niranjan, Sabesan Shivkumar, Iasemidis Leon, Tsakalis Kostas

机构信息

Department of Electrical Engineering, Arizona State University, Tempe, Arizona, USA.

出版信息

Int J Neural Syst. 2007 Apr;17(2):123-38. doi: 10.1142/S0129065707000993.

Abstract

We have studied coupled neural populations in an effort to understand basic mechanisms that maintain their normal synchronization level despite changes in the inter-population coupling levels. Towards this goal, we have incorporated coupling and internal feedback structures in a neuron-level population model from the literature. We study two forms of internal feedback--regulation of excitation, and compensation of excessive excitation with inhibition. We show that normal feedback actions quickly regulate/compensate an abnormally high coupling between the neural populations, whereas a pathology in these feedback actions can lead to abnormal synchronization and "seizure"-like high amplitude oscillations. We then develop an external control paradigm, termed feedback decoupling, as a robust synchronization control strategy. The external feedback decoupling controller acts to achieve the operational objective of maintaining normal-level synchronous behavior irrespective of the pathology in the internal feedback mechanisms. Results from such an analysis have an interesting physical interpretation and specific implications for the treatment of diseases such as epilepsy. The proposed remedy is consistent with a variety of recent observations in the human and animal epileptic brain, and with theories from nonlinear systems, adaptive systems, optimization, and neurophysiology.

摘要

我们研究了耦合神经群体,旨在理解尽管群体间耦合水平发生变化,但仍能维持其正常同步水平的基本机制。为实现这一目标,我们在文献中的神经元水平群体模型中纳入了耦合和内部反馈结构。我们研究了两种形式的内部反馈——兴奋调节和用抑制来补偿过度兴奋。我们表明,正常的反馈作用能迅速调节/补偿神经群体之间异常高的耦合,而这些反馈作用中的病理状态会导致异常同步和类似“癫痫发作”的高振幅振荡。然后,我们开发了一种外部控制范式,称为反馈解耦,作为一种强大的同步控制策略。外部反馈解耦控制器的作用是实现维持正常水平同步行为的操作目标,而不管内部反馈机制中的病理状态如何。这种分析结果具有有趣的物理解释,并对癫痫等疾病的治疗具有特定意义。所提出的治疗方法与近期在人类和动物癫痫大脑中的各种观察结果一致,也与非线性系统、自适应系统、优化和神经生理学的理论一致。

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