Calculating mutual information for spike trains and other data with distances but no coordinates

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Abstract

Many important data types, such as the spike trains recorded from neurons in typical electrophysiological experiments, have a natural notion of distance or similarity between data points, even though there is no obvious coordinate system. Here, a simple Kozachenko–Leonenko estimator is derived for calculating the mutual information between datasets of this type.
Original languageEnglish
Article number140391
Number of pages6
JournalRoyal Society Open Science
Volume2
Early online date13 May 2015
DOIs
Publication statusPublished - May 2015

Keywords

  • spike trains
  • information theory
  • mutual information

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