Fig 4. Performance for variations of the input variance.

Time series of population spike rate and mean adaptation current from the different models in response to varying ${\sigma }_{\text{ext}}^2$ for large mean input and rapid variations, μ_ext = 4 mV/ms, ${\tau }_{\text{ou}}^{{\sigma }^2}=5\text{ms}$ (A) and for small mean input and moderately fast variations, μ_ext = 1.5 mV/ms, ${\tau }_{\text{ou}}^{{\sigma }^2}=50\text{ms}$ (B). The values for the remaining input parameters were ${\overline{\sigma }}_{\text{ext}}^2=9{\text{mV}}^2/\text{ms}$, ϑ_σ² = 2 mV²/ms. For the aEIF population 〈w〉± standard deviation are visualized (red shaded areas). Note that the mean adaptation time series of all models as well as the spike rates of the cascade based models are on top of each other. The indicated Pearson correlation coefficients (with dashed input-output correlation) and root mean square distances were calculated from simulated spike rate time series of 60 s duration from which the first second was excluded, as the initial conditions of the models were not matched. In A the correlation ρ (but not the distance d_RMS) between the spike rates of the model spec₁ and the aEIF population) is strongly decreased due to a small time lag between the two time series which is difficult to see in the figure.