Systems-level modeling of neuronal circuits for leech swimming
Systems-level modeling of neuronal circuits for leech swimming
复制标题
水蛭游泳神经元回路的系统级建模
DOI：
10.1007/s10827-006-9648-7
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发表时间：
2007-02-01
影响因子：
1.2
通讯作者：
Iwasaki, T.
中科院分区：
文献类型：
--
作者：
Zheng, M.;Friesen, W. O.;Iwasaki, T.
本文描述了控制游泳水蛭有节奏的身体运动的神经中枢模式发生器（CPG）的数学模型。该系统方法用于通过具有最少参数的简单 CPG 架构来捕获生成细胞膜电位协调振荡所必需的神经元动力学。基于生理实验的输入/输出数据，首先对动态组件（神经元和突触相互作用）进行单独建模，然后集成到非线性振荡器链中以形成 CPG。我们通过数值模拟表明，可以在生理上合理的范围内估计一些参数的值，以实现数据在相位、幅度和周期方面的良好拟合。该参数估计导致了关于沿神经索的突触耦合强度和固有周期梯度的预测，后者在质量上与实验观察一致。
This paper describes a mathematical model of the neuronal central pattern generator (CPG) that controls the rhythmic body motion of the swimming leech. The systems approach is employed to capture the neuronal dynamics essential for generating coordinated oscillations of cell membrane potentials by a simple CPG architecture with a minimal number of parameters. Based on input/output data from physiological experiments, dynamical components (neurons and synaptic interactions) are first modeled individually and then integrated into a chain of nonlinear oscillators to form a CPG. We show through numerical simulations that the values of a few parameters can be estimated within physiologically reasonable ranges to achieve good fit of the data with respect to the phase, amplitude, and period. This parameter estimation leads to predictions regarding the synaptic coupling strength and intrinsic period gradient along the nerve cord, the latter of which agrees qualitatively with experimental observations.