Described is a system, method, and computer program product for feature detection with spiking dynamics. The system is configured to perform operations of first receiving an input pattern comprising a plurality of features. The input pattern is then translated into a spike-coded representation of the input pattern. The spike-coded representation of the input pattern is transferred to a feature detector layer of a feature detector network comprising a set of feature detector neurons having input weights. Each feature detector neuron in the set of feature detector neurons then competes for the feature detector neuron whose input weights best represent the input pattern. Finally, the input weights which compressively code frequently seen input patterns are updated according to a set of learning rules. Also presented is a novel set of rules that transform the functional properties of rate-coded models into the spiking domain.