We consider nonlinear scalar integral differential equations which generalize many important nonlinear scalar integral differential equations arising from synaptically coupled neuronal networks. The synaptic couplings can be very general, including not only pure excitations (modeled with nonnegative kernel functions), lateral inhibitions (modeled with Mexican hat kernel functions), lateral excitations (modeled with upside down Mexican hat kernel functions), but also synaptic couplings which may change sign for finitely many times or even infinitely many times.Moreover, we consider a Heaviside transfer function and distributed transmission and feedback delays. The work studies the existence and stability of traveling front solutions of such equations.