Fig. 1.

(a) A population of $N=3$ EIF neurons receiving common ${\xi }_c$ and independent inputs ${\xi }_i$. The voltages of the neurons evolve according to Eq. (1). Parameters: ${\tau }_m=5\text{ ms}$, ${\Delta }_T=3\text{ mV}$, $V_T=20\text{ mV}$, $V_S=-53\text{ mV}$, $V_R=-60\text{ mV}$, ${\tau }_{\mathrm{ref}}=3\text{ ms}$. We tune the noise amplitude so that when the DC component of the input is $\gamma =-60\text{ mV}$, the neurons fire at 10 Hz; this yields $\sigma =6.23\text{ mV}$. The resulting firing is strongly irregular, with the coefficient of variation of the ISI distribution being 0.91. (b) Cartoon of the binning process: spikes recorded from each of the EIF neurons in a bin contribute towards the population spike count. More than one spike occurring from the same neuron within a single bin is treated as a single event. This happens less than 0.4 % of the time in our numerical simulations with $\mu =0.1$ and $\rho =0.1$ (input parameters $\gamma =-60\text{ mV}$, $\sigma =6.23\text{ mV}$, $\lambda =0.30$)