  Precise timing of spikes and temporal locking are key elements of neural
computation. Here we demonstrate how even strongly heterogeneous, deterministic
neural networks with delayed interactions and complex topology can exhibit
periodic patterns of spikes that are precisely timed. We develop an analytical
method to find the set of all networks exhibiting a predefined pattern
dynamics. Such patterns may be arbitrarily long and of complicated temporal
structure. We point out that the same pattern can exist in very different
networks and have different stability properties.
