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Sparse balance: Excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights

Fig 2

Sparse balance yields non-Gaussian dynamics and a subthreshold mean.

Distribution of currents x (over time and units) for gamma-distributed synapses. Dashed lines denote the mean of each distribution, i.e., . Area above threshold (set to zero; solid line) corresponds to the fraction of active units f. A) With low synaptic variance (ν = 1), the distribution of x is a Gaussian centered around a mean that tends to zero for larger K. B) Same as in A except for high synaptic variance (ν = 1/2). Note the larger range of the horizontal axis compared to B. The distribution is no longer Gaussian. is relatively insensitive to K and lies below threshold. (Model parameters are g = J₀ = 2, I₀ = 1, J_ij ∼ gamma, N = K, ϕ = [tanh]₊).

doi: https://doi.org/10.1371/journal.pcbi.1008836.g002