Likelihood Methods for Point Processes with Refractoriness

@article{Citi2014LikelihoodMF,
  title={Likelihood Methods for Point Processes with Refractoriness},
  author={Luca Citi and Demba E. Ba and Emery N. Brown and Riccardo Barbieri},
  journal={Neural Computation},
  year={2014},
  volume={26},
  pages={237-263}
}
Likelihood-based encoding models founded on point processes have received significant attention in the literature because of their ability to reveal the information encoded by spiking neural populations. We propose an approximation to the likelihood of a point-process model of neurons that holds under assumptions about the continuous time process that are physiologically reasonable for neural spike trains: the presence of a refractory period, the predictability of the conditional intensity… 
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