@Article{	  cessac:11b,
  author		      = {Bruno Cessac},
  title			      = {Statistics of spike trains in conductance-based neural networks: Rigorous results},
  journal		      = {The Journal of Mathematical Neuroscience},
  year			      = {2011},
  volume		      = {1},
  number		      = {8},
  pages			      = {1-42},
  url			      = {http://www.mathematical-neuroscience.com/content/1/1/8},
  keywords		      = {Neural Networks, Spike statistics, Gibbs distributions},
  topic			      = {Modeling of spiking neurons},
  owner			      = {bcessac},
  group			      = {Neuromathcomp},
  annote		      = {We consider a conductance-based neural network inspired by the generalized Integrate and Fire
				model introduced by Rudolph and Destexhe in 1996. 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 the presence of a time-dependent
				stimulus and apply therefore to non-stationary dynamics.},
  x-editorial-board	      = {yes},
  x-international-audience    = {yes},
  doi			      = {10.1186/2190-8567-1-8},
  x-pays		      = {}
}