Gradient Algorithm

In finding an optimal stimulus waveform for inducing switches in neuronal states, analytical techniques from optimal control theory are often found to be difficult to use or extremely time intensive. Here, we present the code for a gradient-based algorithm approach that has been used to find energetically optimal stimulus waveforms to trigger an action potential in the Hodgkin-Huxley model as well as initiating and repressing repetitive firing in the FitzHugh-Nagumo models. These two models serve just as examples and the code can be easily adapted to any other system.

在寻求引发神经元状态切换的最佳刺激波形的过程中，常常发现最优控制理论的分析技术难以应用或耗时极为漫长。在此，我们提供了基于梯度算法的代码，该算法已被应用于寻找能够触发 Hodgkin-Huxley 模型中动作电位产生的能量最优刺激波形，以及启动和抑制 FitzHugh-Nagumo 模型中重复放电的代码。这两个模型仅作为示例，代码可以轻松地适应任何其他系统。