Many complex systems are composed of a large number of similar
units that are connected in a complicated manner. An important
example is provided by neural networks where nerve cells in the
brain communicate by exchanging pulses via synaptic connections.
Unlike atoms in a crystal which are arranged on a regular, e.g
cubic lattice, nerve cells in the brain grow synaptic
connections in a highly specific but irregular fashion. In such
systems, a particular question is how rapid coordination, e.g.
synchronization, between units of a complex network can be
achieved. Three theoretical neuro-physicists from the Max Planck
Institut for Flow Research in Goettingen have now shed new light
on this question for networks of pulse-coupled oscillators,
simple models of neural networks in the brain (Physical Review
Letters 92: 074101, 2004). To analyze the impact of network
structure on its function the scientists use the theory of
random matrices. Initiated by the work of Wigner on correlations
of energy levels in atomic nu