  We study the influence of correlations among discrete stochastic excitatory
or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For
any level of correlation the emitted signal exhibits at some finite noise
intensity a maximal degree of regularity, i.e., a coherence resonance.
Furthermore, for either inhibitory or excitatory correlated stimuli a {\it
Double Coherence Resonance} (DCR) is observable. DCR refers to a (absolute)
maximum coherence in the output occurring for an optimal combination of noise
variance and correlation. All these effects can be explained by taking
advantage of the discrete nature of the correlated inputs.
