Figure 1.

Structure of grown networks. (A) The network is composed of 80% excitatory and 20% inhibitory LIF neurons. EE connections are plastic and follow the SP rule. All other connections are static and randomly created at the beginning of the simulation, such that all neurons have a fixed indegree corresponding to 10% of the presynaptic population size. (B) Time evolution of average EE connectivity. Dots and bars indicate mean ± standard deviation across 10 independent simulation runs. Highest standard deviation in the time series is 2.8 × 10⁻⁵. (C) Indegree and outdegree distributions for EE connections after 750 s simulation time. μ_in, ${\sigma }_{\mathrm{in}}^2$, μ_out and ${\sigma }_{\mathrm{out}}^2$ are the mean and the variance of the shown indegree and outdegree distributions, respectively. (D) Normalized histogram of the number of synapses per contact between pairs of neurons after 750 s of simulation. Black dots refer to a Poisson distribution with rate parameter matching the average connectivity of the simulated network. (E) Raster plot showing 1 s activity of 100 excitatory and 25 inhibitory neurons (randomly chosen) after 750 s of simulation. (F) Histograms of firing rate, irregularity and pairwise correlation for all (pairs of) excitatory neurons after the network has reached a statistical equilibrium state (judged “by eye”). The neurons fire in an asynchronous-irregular (AI) regime. Data were extracted from 20 s of activity, the bin size used for calculating CC was 10 ms. (B–F) Target rate ρ = 8 Hz and β = 2 for all subplots.