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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Tetzlaff, T., Diesmann, M. (2010). Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale. In: Grün, S., Rotter, S. (eds) Analysis of Parallel Spike Trains. Springer Series in Computational Neuroscience, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5675-0_6
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DOI: https://doi.org/10.1007/978-1-4419-5675-0_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5674-3
Online ISBN: 978-1-4419-5675-0
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