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Optimal estimation of the parameters affecting the Parkinson's disease state of thalamic cell model

机译:影响帕金森氏细胞模型毒素疾病状态的参数的最佳估计

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The Parkinson's disease (PD) state can be distinguished by relay reliability of thalamic cell (TC). Among numerous parameters of single-compartment conductance-based TC model, only two of them mainly modulate the relay reliability of TC. In order to explore the relationship between the two parameters and the firing relay, a parameter estimation method based on particle swarm optimization (PSO) algorithm is proposed and conducted on the TC model with two adjustable parameters. The simulation results estimated respectively from spiking features of PD state and normal state both achieve good performance.
机译:通过丘脑(TC)的继电器可靠性,可以区分帕金森病(PD)状态。在基于单室电导的TC模型的许多参数中,其中两个主要是调制TC的继电器可靠性。为了探索两个参数和射击继电器之间的关系,提出了一种基于粒子群优化(PSO)算法的参数估计方法,并在具有两个可调参数的TC模型上进行。仿真结果分别估计PD状态和正常状态的尖峰特征均达到良好的性能。

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