Calculating the Mutual Information Between Two Spike Trains
Abstract
It is difficulty to estimate the mutual information between spike trains because established methods require more data than is usually available. Kozachenko-Leonenko estimators promise to solve this problem, but include a smoothing parameter which must be set. It is proposed 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.
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