cluster synchronization or chaotic solutions can be excluded. But adding delayed feedback of the mean-field, mixtures of excitatory and inhibitory acting units of the network or systematic shifts in the signal function might be a source for more complex situations.

Special initial conditions (for example all units in the excited state) cause damped oscillations of the mean-field. Even in the case of a $\delta$-function as waiting time density, the assumed exponentially distributed activation times scatter the individual spins with large dispersion. Hence the coherence of special initial conditions is destroyed after a few excitations yielding a stationary mean-field.

Nevertheless, as will be seen in the next section, the individual spins can fire with a small CV[^2] resembling oscillatory behavior. In the states with high mean-field values the activation time becomes negligible small. In these situations the spiking is dominated by the recovery time from the excited to the rest state. If this time does not possess remarkable dispersion the CV become vanishingly smalls.

In the next Section \[sec:RBN\] further insight into the consequences of several degrees will be given by dealing with the simplest case of network with two populations with different degrees $k_1, k_2$, only.

Random binary networks {#sec:RBN}
