Synaptic drive of a network of spiking neurons were trained to follow 1000 ms long targets where and were selected uniformly from the interval [500 ms, 1000 ms]. (a) Network consisted of leaky integrate-and-fire neuron models, whose membrane potential obeys with a time constant ms; the neuron spikes when exceeds spike threshold mV then is reset to mV. Red curves show the target pattern and black curves show the voltage trace and synaptic drive of a trained network. (b) Spike rastergram of a trained leaky integrate-and-fire neuron network generating the synaptic drive patterns. (c) Network consisted of Izhikevich neurons, whose dynamics are described by two equations and ; the neuron spikes when exceeds 30 mV, then is reset to and is reset to . Neuron parameters and were selected as in the original study (Izhikevich, 2003) so that there were equal numbers of regular spiking, intrinsic bursting, chattering, fast spiking and low threshold spiking neurons. Synaptic current is modeled as in Equations 6 for all neuron models with synaptic decay time ms. Red curves show the target patterns and black curves show the voltage trace and synaptic drive of a trained network. (d) Spike rastergram of a trained Izhikevich neuron network showing the trained response of different cell types.