Statistics of spike trains in conductance-based neural networks:   Rigorous results
  We consider a conductance based neural network inspired by the generalized Integrate and Fire model introduced by Rudolph and Destexhe. We show the existence and uniqueness of a unique Gibbs distribution characterizing spike train statistics. The corresponding Gibbs potential is explicitly computed. These results hold in presence of a time-dependent stimulus and apply therefore to non-stationary dynamics. 
B. Cessac
math-ph math.DS math.MP physics.bio-ph q-bio.NC