Predictive control for spike pattern modulation of a two-compartment neuron model

被引:2
|
作者
Su, Fei [1 ]
Wang, Jiang [1 ]
Li, Huiyan [2 ]
Deng, Bin [1 ]
Wei, Xile [1 ]
Yu, Haitao [1 ]
Liu, Chen [1 ]
机构
[1] Tianjin Univ, Sch Elect Engn & Automat, Tianjin 300072, Peoples R China
[2] Tianjin Univ Technol & Educ, Sch Automat & Elect Engn, Tianjin 300222, Peoples R China
基金
中国国家自然科学基金;
关键词
Spike pattern; Cellular electrophysiology; Pinsky-Rinzel model; Predictive control; Uncertainty; Geometric parameter; DEEP BRAIN-STIMULATION; CLOSED-LOOP CONTROL; SUBTHALAMIC NUCLEUS; PARKINSONIAN STATE; PHASE MODELS; ELECTROPHYSIOLOGY; EPILEPSY; CHANNEL;
D O I
10.1016/j.neucom.2016.06.062
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Modulating the spike patterns of single neuron is an important content of closed-loop cellular electrophysiology. This paper investigates the spike pattern control of a physiologically accurate two-compartment Pinsky-Rinzel model with a fast and local optimized generalized predictive control algorithm. In order to simulate the electrophysiological experiments more realistically, uncertainties including model parameter variations, noises with arbitrary intensities and changes of inner states are introduced in the model. Simulation results demonstrate the robustness of the proposed algorithm on different uncertainties. What is more, the control performances rely on the value of the geometric parameter that characterizes the ratio between the soma area and the dendrite area while has little to do with the internal coupling conductance. The derived theoretical simulations represent a new direction towards the design of online optimal stimulus waveforms in real cellular electrophysiological experiments, which can effectively cope with the physiological uncertainties. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:89 / 101
页数:13
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