Such neural populations are usually localized spatially and contain both excitatory and inhibitory neurons [@WIL72]. In this sense, the model of two mutually coupled neurons may also serve as a paradigm of two coupled neural sub-ensembles.

Starting from such simplest network motifs, larger networks can be built, and their effects may be studied. For example, starting from two interconnected reticular thalamic neurons with oscillatory behavior, it was shown in [@DES94] how more complex dynamics emerges in ring networks with nearest neighbors and fully reciprocal connectivity, or in networks organized in a two-dimensional array with proximal connectivity and “dense proximal” coupling in which every neuron connects to all other neurons within some radius. In another example [@ZHO06c], a neural population was itself modeled as a small sub-network of excitable elements, to study hierarchically clustered organization of excitable elements in a [*network of networks*]{}.

In the following, we consider two mutually coupled neurons modelled by the paradigmatic FitzHugh-Nagumo system [@FIT61; @NAG62; @LIN04] in the excitable regime: $$\begin{aligned}
\label{eq:system}
    \epsilon_1 \dot{x}_1 &=& x_1 - \frac{x_1^3}{3} - y_1+ C[x_2(t-\tau)-x_1(t)]\nonumber\\
        \dot{y}_1 &=& x_1 + a + D_1 \xi_1(t) \nonumber\\
        \epsilon_2 \dot{x}_2 &=& x_2 - \frac{x_2^3}{3} - y_2 + C[x_1(t-\tau)-x_2(t)]\nonumber\\
        \dot{y}_2 &=& x_2 + a + 