Analysis of Parallel Spike Trains pp 103-127

Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 7)

Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale

Abstract

Spiking activity is typically measured by counting the number of spikes in a certain time interval. The length of this interval, the “bin size”, varies considerably across studies. In this chapter, we provide a mathematical framework to relate the spike-count statistics to the statistics of the underlying point processes. We show that spike-count variances, covariances, and correlation coefficients generally depend in a nontrivial way on the bin size and on the spike-train auto- and cross-correlation structure. The spike-count coherence, in contrast, constitutes a correlation measure independent of bin size.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Mathematical Sciences and TechnologyNorwegian University of Life SciencesÅsNorway
  2. 2.Laboratory for Computational NeurophysicsRIKEN Brain Science InstituteWakoshiJapan
  3. 3.Bernstein Center for Computational NeuroscienceAlbert-Ludwig UniversityFreiburgGermany

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