@Article{	  vasquez-palacios-etal:12,
  author		      = {Juan-Carlos Vasquez and Adrian Palacios and Olivier Marre and Michael J. Berry II and Bruno
				Cessac},
  title			      = {Gibbs distribution analysis of temporal correlation structure on multicell spike trains from
				retina ganglion cells},
  journal		      = {J. Physiol. Paris},
  year			      = {2012},
  volume		      = {106},
  number		      = {3-4},
  pages			      = {120-127},
  month			      = may,
  url			      = {http://arxiv.org/abs/1112.2464},
  keywords		      = {Spike-train analysis, Higher-order correlation, Statistical Physics, Gibbs Distributions,
				Maximum Entropy},
  topic			      = {Modeling of spiking neurons},
  owner			      = {pkornp},
  group			      = {Neuromathcomp},
  annote		      = {We present a method to estimate Gibbs distributions with spatio-temporal con- straints on spike
				trains statistics. We apply this method to spike trains recorded from ganglion cells of the
				salamander retina, in response to natural movies. Our analysis, restricted to a few neurons,
				performs more accurately than pairwise syn- chronization models (Ising) or the 1-time step
				Markov models (Marre et al. (2009)) to describe the statistics of spatio-temporal spike patterns
				and emphasizes the role of higher order spatio-temporal interactions.},
  x-editorial-board	      = {yes},
  x-international-audience    = {yes},
  x-pays		      = {US,CL}
}