Replica Mean Field limits for neural networks with excitatory and inhibitory activity

We study Replica Mean Field limits for a neural system of infinitely many neurons with both inhibitory and excitatory interactions. As a result we obtain an analytical characterisation of the invariant state. In particular we focus on the Galves-Löcherbach model with interactions beyond the Uniform Summability Principle.