Figure 3.
Numerical simulations of a network of 1000 Izhikevich neurons with parameters as in Table 1, except gsyn = 200 and the applied current which is normally distributed with mean and variance as follows. (A) 〈Iapp〉 = 5000 pA, σI = 2000 pA. (B) 〈Iapp〉 = 3000 pA, σI = 200 pA. (C) 〈Iapp〉 = 3000 pA, σI = 500 pA. (D) 〈Iapp〉 = 3000 pA, σI = 2000 pA. Blue is the network average of a given variable, red is MFI, green is MFII and black is MFIII. In this region, the mean-driving current is away from rheobase, 〈Iapp〉 » Irh. All three approximations are quantitatively and qualitatively similar for small to intermediate sized variances in the distribution of currents. For small variances, MFI is the most accurate and for larger variances, MFIII is the most accurate. For large variance, MFII bifurcates back to tonic firing earlier than MFI and MFIII, as seen in (D).