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Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks

Fig 4

Critical avalanches in networks with different sizes.

We simulate networks subjected to noisy inputs with a constant strength r_in that linearly scales with the network size and exhibits critical dynamics (). We show the distributions of avalanche size S, avalanche duration T, and the average size 〈S〉 under duration T. Horizontal purple lines indicate the ranges of estimated power-law distributions. From left to right, the network sizes are N = 2500, 5000, 10,000, 15,000. The input strengths are r_in = 0.9, 1.8, 3.6, 5.4/ms, to maintain the scale condition r_in~O(N) for E–I balanced networks. Avalanches are measured with adapted time bin Δt = T_m = 0.11, 0.03, 0.02, 0.013 ms respectively.

doi: https://doi.org/10.1371/journal.pcbi.1009848.g004