(A) Contour plot of slopes of response curves in numerical experiments using rate model neurons.

<p>We plot the derivative of change in the PN activity with respect to the external stimulus as a function of , which is the fraction of neurons that receive input, and , which is the probability of having a connection from an inhibitory neuron to an excitatory one. The parameter values used in this simulation of the rate model neurons were , , , while the probability of connections are , and . The gain constants are set to 1 with thresholds . Strict gain control corresponds to slope and is represented by the thick black solid line. The line is not complete because we do not have enough resolution to reliably track the gain control boundary. (B) Exploration of the dependence of the gain control boundaries as a function of the strength of the coupling from the excitatory to the inhibitory population. The parameters were the same as for the simulations shown in A except . (C) Examples of the mean activity of the excitatory population for different realizations (rows) of the network using the same parameter values as (A) near the gain control conditions. Despite the restraining gain control conditions the dynamics of the rate models are capable of displaying a rich variety of dynamical behaviors. Each column represents different levels of recruitment () by the input.