This is the readme for simulation code associated with the paper: Lim S, Goldman MS (2013) Balanced cortical microcircuitry for maintaining information in working memory, Nature Neuroscience 16:1360-1314 Matlab simulation code written by Sukbin Lim and posted to ModelDB on 8/12/2014 Contents: FiringRateModel_PM.m: An m-file simulates firing rate models of parametric working memory circuits based on negative derivative feedback. If flag = 1, the external input is transient, resulting a jump in the network activity and if flag = 0, the external input is like a step, resulting in ramp-like activity. The simulations of the firing rate models were run with a fourth-order explicit Runge-Kutta method using the function ode45. By default the output of FiringRateModel_PM.m should look like: SpikingNetworkModel_PM.m: An m-file simulates spiking network models of parametric working memory circuits based on negative derivative feedback. It reproduces Figure 5 in the paper. The numerical integration of the network simulation was performed using the second-order Runge-Kutta algorithm and spike times were approximated by linear interpolation (Hansel et al. 1998) - Caution: Simulation of spiking network model in Matlab is slow for a large size of network which is required for strong corrective feedback.