A novel spike distance

Neural Comput. 2001 Apr;13(4):751-63. doi: 10.1162/089976601300014321.

Abstract

The discrimination between two spike trains is a fundamental problem for both experimentalists and the nervous system itself. We introduce a measure for the distance between two spike trains. The distance has a time constant as a parameter. Depending on this parameter, the distance interpolates between a coincidence detector and a rate difference counter. The dependence of the distance on noise is studied with an integrate-and-fire model. For an intermediate range of the time constants, the distance depends linearly on the noise. This property can be used to determine the intrinsic noise of a neuron.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Evoked Potentials / physiology
  • Models, Neurological
  • Neurons / physiology*
  • Poisson Distribution