Journal of Computational Neuroscience

, Volume 22, Issue 1, pp 5–19 | Cite as

Non-parametric detection of temporal order across pairwise measurements of time delays

Article

Abstract

Neuronal synchronization is often associated with small time delays, and these delays can change as a function of stimulus properties. Investigation of time delays can be cumbersome if the activity of a large number of neurons is recorded simultaneously and neuronal synchronization is measured in a pairwise manner (such as the cross-correlation histograms) because the number of pairwise measurements increases quadratically. Here, a non-parametric statistical test is proposed with which one can investigate (i) the consistency of the delays across a large number of pairwise measurements and (ii) the consistency of the changes in the time delays as a function of experimental conditions. The test can be classified as non-parametric because it takes into account only the directions of the delays and thus, does not make assumptions about the distributions and the variances of the measurement errors.

Keywords

Cross correlation Phase offset Temporal-order code Transitivity Additivity 

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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  1. 1.Max-Planck-Institute for Brain ResearchFrankfurt am MainGermany
  2. 2.Frankfurt Institute for Advanced StudiesJohann Wolfgang Goethe-UniversityFrankfurtGermany

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