Abstract：
: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 fluctuations 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.
journal_name
J Neurosci Methodsjournal_title
Journal of neuroscience methodsauthors
Robin K,Maurice N,Degos B,Deniau JM,Martinerie J,Pezard Ldoi
10.1016/j.jneumeth.2009.01.020subject
Has Abstractpub_date
2009-04-30 00:00:00pages
142-9issue
1eissn
0165-0270issn
1872-678Xpii
S0165-0270(09)00044-2journal_volume
179pub_type
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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journal_title：Journal of neuroscience methods
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