title: Calculating mutual information for spike trains and other data with distances but no coordinates.
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.
authors.affiliation: Department of Computer Science , University of Bristol, Merchant Venturers Building, Woodland Road , Bristol BS8 1UB, UK.
authors.forename: Conor
authors.identifier: 0000-0001-5017-9473
authors.initials: C
authors.lastname: Houghton
keywords: information theory; mutual information; spike trains