  We review two examples where the linear response of a neuronal network
submitted to an external stimulus can be derived explicitely, including network
parameters dependence. This is done in a statistical physics-like approach
where one associates to the spontaneous dynamics of the model a natural notion
of Gibbs distribution inherited from ergodic theory or stochastic processes.
These two examples are the Amari-Wilson-Cowan model and a conductance based
Integrate and Fire model.
