For fixed feedback gain $K=1.5$, Fig. \[fig:isi\_tau\] depicts the average interspike intervals of the subsystems, shown as solid (black) and dashed (red) curves for $\langle T_1\rangle$ and $\langle T_2\rangle $, and their ratio (green dots) for the case of (a) moderately, (b) weakly, and (c) strongly synchronized systems, respectively, in dependence on the time delay $\tau_K$. In all three cases, the stochastic synchronization can be strongly modulated by changing the delay time, i.e., one can either enhance and suppress synchronization by appropriate choice of the local feedback delay.

The overall dependence of the frequency synchronization, measured by the ratio of $\langle T_1\rangle/\langle T_2\rangle$, is displayed in dependence on the control parameters $K$ and $\tau_K$ in Fig. \[fig:isi\_control\] for moderate, weak, strong synchronization in panels (a), (b), and (c), respectively. Thus, Fig. \[fig:isi\_tau\] can be understood as a horizontal cut for $K=1.5$ through Fig. \[fig:isi\_control\]. One can see a modulation of the ratio of average interspike interval by $\tau_K$ for a large range of feedback gain. In view of applications, where neural synchronization is often pathological, e.g. in Parkinson’s disease or epilepsy, it is interesting to note that there are cases where a proper choice of the local feedback control parameters 