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Input correlations impede suppression of chaos and learning in balanced firing-rate networks
Fig 5
Dynamic mean-field theory captures frequency-dependent effects on the suppression of chaos.
A) 
as a function of input frequency f (g = 1.6 light color, g = 2 dark color). 
has a minimum that is captured by the non-stationary DMFT (dashed green line) but not by the quasi-static approximation (dotted green line), which does not depend on frequency f. At high f, the low-pass filter effect of the leak term attenuates the external input modulation for both cases, thus resulting in a linearly increasing 
. B) Dependence of 
on the gain parameter g for high input frequency (f = 0.2/τ), showing a monotonic increase. The non-stationary DMFT results are in good agreement with numerical simulations. For comparison, we include the result of the quasi-static approximation (dotted green line), which shows a more gradual dependence on g and applies only at low frequencies (see Fig 3). Error bars indicate ±2 std. Model parameters: N = 5000, g = 2, f = 0.2/τ, I0 = J0 = 1.
doi: https://doi.org/10.1371/journal.pcbi.1010590.g005