For the paper:

Diesmann M, Gewaltig MO, Aertsen A (1999) Conditions for stable
propagation of synchronous spiking in cortical neural networks.
Nature 402:529-533

Abstract:

The classical view of neural coding has emphasized the importance of
information carried by the rate at which neurons discharge action
potentials. More recent proposals that information may be carried by
precise spike timing have been challenged by the assumption that these
neurons operate in a noisy fashion--presumably reflecting fluctuations
in synaptic input and, thus, incapable of transmitting signals with
millisecond fidelity. Here we show that precisely synchronized action
potentials can propagate within a model of cortical network activity
that recapitulates many of the features of biological systems. An
attractor, yielding a stable spiking precision in the (sub)millisecond
range, governs the dynamics of synchronization. Our results indicate
that a combinatorial neural code, based on rapid associations of
groups of neurons co-ordinating their activity at the single spike
level, is possible within a cortical-like network.

Brian simulator models are available at this web page:

http://briansimulator.org/docs/examples-frompapers_Diesmann_et_al_1999.html

and here is a similar but longer one with functions and a class
definition:

http://briansimulator.org/docs/examples-frompapers_Diesmann_et_al_1999_longer.html

The simulation generates an image similar to Fig. 1d in the paper,
albeit at a faster synaptic delay than the papers 5ms one:

screenshot

If n is reduced to 48 on line 18 (the PulsePacket line) a figure
similar to 1e is produced:

screenshot2

This simulation requires Brian which can be downloaded and installed
from the instructions available at http://www.briansimulator.org/

For support on installing and using Brian simulations there is a
support group at https://groups.google.com/group/briansupport.