Some statistical issues in estimating information in neural spike trains
Vincent Q. Vu, Bin Yu, Robert E. Kass · 2009
Information theory provides an attractive framework for attacking the neural coding problem. This entails estimating information theoretic quantities from neural spike train data. This paper highlights two issues that may arise: non-parametric entropy estimation and non-stationarity. It gives an overview of these issues and some of the progress that has been made.