DCN椎体神经元的Hopf分岔控制

Hopf Bifurcation Control of DCN Pyramidal Neurons

摘要: 耳蜗背侧核(DCN)椎体神经元是听觉中枢系统中首先对声波电信号进行处理的神经元之一，其对声波信息的处理、整合起了非常重要的作用。通过DCN椎体神经元的离体实验数据可以建立基于电压依赖型离子通道变量的数学模型KM模型。我们将hf作为分岔参数对DCN椎体神经元模型进行快慢动力学分析。然后使用冲洗滤波器辅助动态反馈控制器的方法来控制KM模型的Hopf分岔位置，实现我们的控制任务。

Abstract: Pyramidal cell in the dorsal cochlear nucleus (DCN) is one of the first neurons in the central au-ditory system to process acoustic signals, which plays an important role in the processing and integration of acoustic information. The KM model based on voltage dependent ion channel var-iables can be established by the in vitro experimental data of DCN pyramidal neurons. We use hf as a bifurcation parameter to analyze the fast and slow dynamics of DCN pyramidal neurons. Then, a dynamic state-feedback control law incorporating a washout filter is used to control the Hopf bifurcation position of KM model, and our control task is realized.