A Novel Spike Distance

M. C. W. Van Rossum

doi:10.1162/089976601300014321

A Novel Spike Distance

M. C. W. Van Rossum

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	751-763
Number of pages	13
Journal	Neural Computation
Volume	13
Issue number	4
DOIs	https://doi.org/10.1162/089976601300014321
Publication status	Published - 1 Apr 2001

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title = "A Novel Spike Distance",

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.",

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AB - 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.

U2 - 10.1162/089976601300014321

DO - 10.1162/089976601300014321

M3 - Article

SN - 0899-7667

VL - 13

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JO - Neural Computation

JF - Neural Computation

IS - 4

ER -

A Novel Spike Distance

Abstract

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