期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 179, 期 1, 页码 142-149出版社
ELSEVIER
DOI: 10.1016/j.jneumeth.2009.01.020
关键词
Spike trains variability; Bursting; Long-range correlations; Detrended fluctuation analysis; Poisson surprise method; Rank surprise method
The detection and characterization of bursting activity remains a topic where no consensual definition has been reached so far. We compare here three different approaches of spike trains variability: statistical characterization (average frequency, coefficient of variation) burst detection (Poisson and rank surprise) and multi-scale analysis (detrended fluctuation analysis). Using both real and simulated data, we show that Poisson surprise provides information closely related to the coefficient of variation and that rank surprise detects significant bursts which are associated with long-range correlations. Since these long-range correlations are only adequately characterized with multi-scale analysis, this study emphasizes the complementarity of these approaches for the complete characterization of spike trains. (C) 2008 Elsevier B.V. All rights reserved.
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