We compare six numerical integrators' performance when simulating a regular spiking cortical neuron model whose 74-compartments are equipped with eleven membrane ion channels and Calcium dynamics. Four methods are explicit and two are implicit; three are finite difference PDE methods, two are Runge-Kutta methods, and one an exponential time differencing method. Three methods are first-, two commonly considered second-, and one commonly considered fourth-order. Derivations show, and simulation data confirms, that Hodgkin-Huxley type cable equations render multiple order explicit RK methods as first-order methods. Illustrations compare accuracy, stability, variations of action potential phase and waveform statistics. Explicit methods were found unsuited for our model given their inability to control spiking waveform consistency up to 10 microseconds less than the step size for onset of instability. While the backward-time central space method performed satisfactorily as a first order method for step sizes up to 80 microseconds, performance of the Hines-Crank-Nicolson method, our only true second order method, was unmatched for step sizes of 1-100 microseconds.
翻译:我们比较了六种数字融合器的性能,模拟一个常规的螺旋神经模型,其74个部分配有11个膜离子信道和钙动力。四种方法是明确的,两种是隐含的;三种是有限的差异PDE方法;两种是龙格-库塔方法,一种是指数时间差异法。三种方法是第一种,两种是通常考虑的第二种,一种是通常考虑的第四级。衍生显示,模拟数据证实,Hodgkin-Huxley型电缆等式使多顺序清晰的RK方法成为第一级方法。说明比较准确性、稳定性、行动潜在阶段的变化和波形统计。发现一些方法不适合我们的模型,因为它们无法控制波形一致性的升幅高达10微秒,比起不稳定时的步数小。虽然后时中央空间方法作为向80微秒的步数的第一个顺序方法表现得令人满意,但Hine-Clank-Nicolson方法的性能是多重顺序。我们唯一的第二步法是不匹配的。