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A metric space approach to the information channel capacity of spike trains

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Abstract

A novel method is presented for calculating the information channel capacity of spike trains. This method works by fitting a χ-distribution to the distribution of distances between responses to the same stimulus: the χ-distribution is the length distribution for a vector of Gaussian variables. The dimension of this vector defines an effective dimension for the noise and by rephrasing the problem in terms of distance based quantities, this allows the channel capacity to be calculated. As an example, the capacity is calculated for a data set recorded from auditory neurons in zebra finch.

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Acknowledgements

JBG wishes to thanks the Irish Research Council of Science, Engineering and Technology for an Embark Postgraduate Research Scholarship. CJH wishes to thank Science Foundation Ireland for Research Frontiers Programme grant 08/RFP/MTH1280. They are grateful to Garrett Greene, Louis Aslett and Daniel McNamee for useful discussion and to Kamal Sen for the use of the data analysed here.

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Authors and Affiliations

  1. School of Mathematics, Trinity College Dublin, Dublin 2, Ireland

    James B. Gillespie & Conor J. Houghton

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  1. James B. Gillespie
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  2. Conor J. Houghton
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Correspondence to Conor J. Houghton.

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Action Editor: Aurel A. Lazar

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Gillespie, J.B., Houghton, C.J. A metric space approach to the information channel capacity of spike trains. J Comput Neurosci 30, 201–209 (2011). https://doi.org/10.1007/s10827-010-0286-8

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  • DOI: https://doi.org/10.1007/s10827-010-0286-8

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