  Latency reduction of postsynaptic spikes is a well-known effect of Synaptic
Time-Dependent Plasticity. We expand this notion for long postsynaptic spike
trains, showing that, for a fixed input spike train, STDP reduces the number of
postsynaptic spikes and concentrates the remaining ones. Then we study the
consequences of this phenomena in terms of coding, finding that this mechanism
improves the neural code by increasing the signal-to-noise ratio and lowering
the metabolic costs of frequent stimuli. Finally, we illustrate that the
reduction of postsynaptic latencies can lead to the emergence of predictions.
