Fig. 1
Rapid divergence of spontaneous activity. a Morphologically detailed model of a neocortical microcircuit (NMC); depicted are 100 randomly selected neurons, out of 31,346 in total (~0.3%). Neurons are colored according to their layer. b Examples of simulated noise sources in the NMC-model: stochastic synaptic transmission, including (a) vesicle release failure and (b) spontaneous vesicle release (“miniature PSPs”) at all 36 million synapses; (c) probabilistic opening and closing of voltage-gated potassium channels in irregularly spiking inhibitory neurons (1137 out of 31,346 neurons); (d) a constant depolarizing current with a weak white noise component (\(\sigma _{\mathrm{s}}^2 \ll \mu _{\mathrm{s}}\)) injected into the somata of all neurons. c The membrane potential of four sample neurons (and population mean of all 31,346 neurons) during a network simulation of spontaneous activity. At t0, the state of the microcircuit is saved, and then resumed twice with identical initial conditions, but with different random seeds for all noise sources. d Root-mean square deviation (RMSDV(t)) and correlation (rV(t)) of the somatic membrane potentials between pairs of resumed simulations diverging from identical initial conditions (mean of all neurons and 40 saved base states ± 95% confidence interval). The dashed lines depict the steady-state RMSDV and rV between independent simulations (i.e., resumed from different base states). e The similarity of the system (sRMSD and sr) defined as the difference between the diverging and steady-state RMSDV and rV, normalized to lie between 1 (identical) and 0 (fully diverged) (mean ± 95% confidence interval). Exponential fit of sRMSD and sr for t − t0 < 40 ms (estimated time constant ± 68% confidence interval of fit). f1 Mean spike count and variance of spike count of 40 independent trials of 1000 ms duration for all neurons in the microcircuit, plotted separately for excitatory neurons (red) and inhibitory neurons (blue). The dashed lines indicate the expected values for a Poisson process. Black lines indicate minimum variance due to the fact that the spike count has to be an integer. f2 Distribution of Fano factors (variance divided by mean spike count) corresponding to f1
