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1530-888X
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Neural Computation

February 2019, Vol. 31, No. 2, Pages 330-343
(doi: 10.1162/neco_a_01155)
© 2018 Massachusetts Institute of Technology
Calculating the Mutual Information between Two Spike Trains
Article PDF (361.74 KB)
Abstract
It is difficult to estimate the mutual information between spike trains because established methods require more data than are usually available. Kozachenko-Leonenko estimators promise to solve this problem but include a smoothing parameter that must be set. We propose here that the smoothing parameter can be selected by maximizing the estimated unbiased mutual information. This is tested on fictive data and shown to work very well.