Y. Ahmadian, J. Pillow, and L. , Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains, Neural Computation, vol.79, issue.1, pp.46-96, 2011.
DOI : 10.1152/jn.90941.2008
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740351

V. I. Arnold, Geometrical Methods in the Theory of Ordinary Differential Equations, 1983.

R. Bowen, Equilibrium States and the Ergodic Theory of Anosov Diffeomorphisms, 2008.
DOI : 10.1007/BFb0081279

D. R. Brillinger, Maximum likelihood analysis of spike trains of interacting nerve cells, Biological Cybernetics, vol.56, issue.3, pp.189-200, 1988.
DOI : 10.1007/BF00318010

B. Cessac and R. Cofré, Spike train statistics and Gibbs distributions, Journal of Physiology-Paris, vol.107, issue.5, pp.360-368, 2013.
DOI : 10.1016/j.jphysparis.2013.03.001
URL : https://hal.archives-ouvertes.fr/hal-00850155

R. Cofré and B. , Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses, Chaos, Solitons & Fractals, vol.50, pp.13-31, 2013.
DOI : 10.1016/j.chaos.2012.12.006

E. J. Chichilnisky, A simple white noise analysis of neuronal light responses, Network: Computation in Neural Systems, vol.12, issue.2, pp.199-213, 2001.
DOI : 10.1080/713663221

S. Cocco, S. Leibler, and R. Monasson, Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods, Proceedings of the National Academy of Sciences, vol.106, issue.33, pp.14058-14062, 2009.
DOI : 10.1073/pnas.0906705106
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2729019

R. Fernandez and G. Maillard, Chains with Complete Connections: General Theory, Uniqueness, Loss of Memory and Mixing Properties, Journal of Statistical Physics, vol.214, issue.1, pp.555-588, 2005.
DOI : 10.1007/s10955-004-8821-5
URL : https://hal.archives-ouvertes.fr/hal-01296844

H. Georgii, Gibbs measures and phase transitions, De Gruyter Studies in Mathematics, issue.9, 1988.
DOI : 10.1515/9783110850147

W. Gerstner and W. Kistler, Spiking Neuron Models, 2002.
DOI : 10.1017/cbo9780511815706

E. T. Jaynes, Information Theory and Statistical Mechanics, Physical Review, vol.106, issue.4, p.620, 1957.
DOI : 10.1103/PhysRev.106.620

O. Marre, S. Boustani, Y. Frégnac, and A. Destexhe, Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations, Physical Review Letters, vol.102, issue.13, p.138101, 2009.
DOI : 10.1103/PhysRevLett.102.138101
URL : https://hal.archives-ouvertes.fr/hal-00444939

M. Pollicott and H. Weiss, Free Energy as a Dynamical Invariant (or Can You Hear the Shape of a Potential?), Communications in Mathematical Physics, vol.109, issue.3, pp.457-482, 2003.
DOI : 10.1007/s00220-003-0905-6

M. Shadlen and W. Newsome, Noise, neural codes and cortical organization, Current Opinion in Neurobiology, vol.4, issue.4, pp.569-579, 1994.
DOI : 10.1016/0959-4388(94)90059-0