Figure 1. Schematics of the balanced E/I-model and identification of suprathreshold sequences in population spiking activity with respect to minimal coincident spiking threshold and temporal coarse graining.

(A) Schematic of the neuronal network consisting of N = 10⁶ neurons (80% excitatory and 20% inhibitory) with a low external Poisson drive of rate λ = 2*10⁻⁵ per time step per neuron. The E/I balance is controlled by $g$, which scales the inhibitory weight matrices (W_II, W_EI) as a function of the excitatory weight matrices (W_EE, W_IE). If not otherwise stated, we set $\mathrm{g}=3.5$ to obtain critical dynamics (see Methods). (B) High variability in intermittent population activity characterizes critical dynamics. Snapshot of the summed neuronal spiking activity as a function of time. (C) Duration, size and scaling of avalanches in the critical model follow power-laws with corresponding exponent estimates $\mathrm{\alpha },\mathrm{\beta }$ and $\mathrm{\chi }$. Note that the external Poisson drive and the finite size of the network introduce lower and higher cut-offs, respectively (beige areas). (D) Zoomed population activity from B. At the original temporal resolution $\Delta t$ and given the coincident spiking threshold, θ (left), we can identify two sequences of suprathreshold activity, $S_1$ and $S_2$ with durations $T_1$ and $T_2$, respectively. Temporally coarse-graining the population activity (right; $k=5$, binning the data into new bins of 5 time points) and increasing the threshold to $\theta \prime >\theta$, absorbs $S_1$ and $S_2$ into a new suprathreshold activity period $S^{\prime }$ with duration $T\prime$.