1. A method for improving neural dynamics of an artificial neural network stored in a device, comprising: obtaining prototypical neuron dynamics from a prototypical neuron, the neuron dynamics comprising at least spike timing; and modifying parameters of a piecewise linear neuron model, of the artificial neural network, so that at least a spike timing of the piecewise linear neuron model matches at least a spike timing of the prototypical neuron, the parameters being modified based on an objective function that determines a metric that quantizes a difference between a first function of spike times of the piecewise linear neuron model and a time constant and a second function of spike times of the prototypical neuron and the time constant.