@Article{	  vasquez-palacios-etal:12,
author = {Juan-Carlos Vasquez and Adrian Palacios and Olivier Marre and Michael J. Berry II and Bruno
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}


26 August 2016