  We analyse the storage and retrieval capacity in a recurrent neural network
of spiking integrate and fire neurons. In the model we distinguish between a
learning mode, during which the synaptic connections change according to a
Spike-Timing Dependent Plasticity (STDP) rule, and a recall mode, in which
connections strengths are no more plastic. Our findings show the ability of the
network to store and recall periodic phase coded patterns a small number of
neurons has been stimulated. The self sustained dynamics selectively gives an
oscillating spiking activity that matches one of the stored patterns, depending
on the initialization of the network.
