Simoni Mario F, DeWeerth Stephen P
Rose-Hulman Institute of Technology, Terre Haute, IN 47803, USA.
IEEE Trans Neural Syst Rehabil Eng. 2006 Sep;14(3):281-9. doi: 10.1109/TNSRE.2006.881537.
We are developing hardware models of central pattern generators (CPGs) to enhance neural prostheses, create biologically based controllers for autonomous machines, and to better understand how biology creates stable and robust movements. Previously, we designed and implemented an analog integrated circuit model of a neuron with Hodgkin-Huxley like dynamics, the silicon neuron. In this work, we use silicon neurons to implement a half-center oscillator and show that the underlying dynamics of this CPG produce bursting behaviors that are well matched to the biological counterpart on which our model is based. In addition, we demonstrate the robustness of the bursting behavior by systematically varying two parameters in each silicon neuron and mapping the corresponding effects on the bursting.
我们正在开发中枢模式发生器（CPG）的硬件模型，以增强神经假体，为自主机器创建基于生物学的控制器，并更好地理解生物学如何产生稳定且强健的运动。此前，我们设计并实现了一个具有霍奇金-赫胥黎式动力学的神经元模拟集成电路模型——硅神经元。在这项工作中，我们使用硅神经元来实现一个半中心振荡器，并表明该CPG的基础动力学产生的爆发行为与我们模型所基于的生物对应物非常匹配。此外，我们通过系统地改变每个硅神经元中的两个参数并绘制对爆发的相应影响，来证明爆发行为的稳健性。
