Gibbs distribution analysis of temporal correlation structure on multicell spike trains from retina ganglion cells

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