Acoustics, Speech, and Signal Processing, IEEE International Conference on (2009)
Apr. 19, 2009 to Apr. 24, 2009
Bin Yu , University of California, Berkeley, Department of Statistics, USA
Robert E. Kass , Carnegie Mellon University, Department of Statistics, Center for the Neural Basis of Cognition, USA
Vincent Q. Vu , University of California, Berkeley, Department of Statistics, USA
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.
Bin Yu, Robert E. Kass, Vincent Q. Vu, "Some statistical issues in estimating information in neural spike trains", Acoustics, Speech, and Signal Processing, IEEE International Conference on, vol. 00, no. , pp. 3509-3512, 2009, doi:10.1109/ICASSP.2009.4960382