Selection of publications
Spike train statistics
Exact computation of the maximum-entropy potential of spiking neural-network models, R. Cofre and B. Cessac, Phys. Rev. (2014).
Parameters estimation for spatio-temporal maximum entropy distributions: application to neural spike trains, H. Nasser and B. Cessac, Entropy (2014)
Statistics of spike trains in conductance-based neural networks: Rigorous results, B. Cessac, Journal of Mathematical Neuroscience (2011)
A discrete time neural network model with spiking neurons: II: Dynamics with noise , B. Cessac, J Math Biol Published online (2010)
How Gibbs distributions may naturally arise from synaptic adaptation mechanisms, B. Cessac, H. Rostro, J.C. Vasquez, T. Viéville , J. Stat. Phys,136, (3), 565-602 (2009)
On Dynamics of Integrate-and-Fire Neural Networks with Adaptive Conductances, Cessac B., Vieville T., Front. Comput. Neurosci. 2:2 (2008)
