- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2202
- Extent
-
Online-Ressource
- Language
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Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Multi-scale detection of rate and variance changes in neuronal spike trains ; volume:16 ; number:1 ; day:18 ; month:12 ; year:2015 ; pages:1 ; date:12.2015
BMC neuroscience ; 16, Heft 1 (18.12.2015), 1, 12.2015
- Creator
-
Albert, Stefan
Messer, Michael
Rummell, Brian
Sigurdsson, Torfi
Schneider, Gaby
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/1471-2202-16-S1-P217
- URN
-
urn:nbn:de:101:1-2020100415421913336174
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:48 AM CEST
Data provider
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Associated
- Albert, Stefan
- Messer, Michael
- Rummell, Brian
- Sigurdsson, Torfi
- Schneider, Gaby
- SpringerLink (Online service)
Other Objects (12)
Multiscale relevance and informative encoding in neuronal spike trains
Measuring spike train synchrony between neuronal populations
Finding the event structure of neuronal spike trains
Identifying spike-timing dependent plasticity in spike train models of synaptically-coupled neuronal ensembles
Effective neuronal refractoriness dominates the statistics of superimposed spike trains
Using spike train distances to identify the most discriminative neuronal subpopulation
Measuring spike train reliability
Neuronal connectivity inference from spike trains using an empirical probabilistic causality measure
A new spike train metric
A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains
Parametric estimation of spike train statistics
Detecting rate changes in spike trains
Multiscale relevance and informative encoding in neuronal spike trains
Measuring spike train synchrony between neuronal populations
Finding the event structure of neuronal spike trains
Identifying spike-timing dependent plasticity in spike train models of synaptically-coupled neuronal ensembles
Effective neuronal refractoriness dominates the statistics of superimposed spike trains
Using spike train distances to identify the most discriminative neuronal subpopulation
Measuring spike train reliability
Neuronal connectivity inference from spike trains using an empirical probabilistic causality measure
A new spike train metric
A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains
Parametric estimation of spike train statistics
Detecting rate changes in spike trains
Multiscale relevance and informative encoding in neuronal spike trains
Measuring spike train synchrony between neuronal populations
Finding the event structure of neuronal spike trains
Identifying spike-timing dependent plasticity in spike train models of synaptically-coupled neuronal ensembles
Effective neuronal refractoriness dominates the statistics of superimposed spike trains
Using spike train distances to identify the most discriminative neuronal subpopulation
Measuring spike train reliability
Neuronal connectivity inference from spike trains using an empirical probabilistic causality measure
A new spike train metric
A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains
Parametric estimation of spike train statistics