Effective neuronal refractoriness dominates the statistics of superimposed spike trains
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1471-2202
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Effective neuronal refractoriness dominates the statistics of superimposed spike trains ; volume:12 ; number:1 ; day:18 ; month:7 ; year:2011 ; pages:1-2 ; date:12.2011
BMC neuroscience ; 12, Heft 1 (18.7.2011), 1-2, 12.2011
- Creator
- Contributor
- DOI
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10.1186/1471-2202-12-S1-P273
- URN
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urn:nbn:de:1111-201603218401
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:51 AM CEST
Data provider
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Deger, Moritz
- Helias, Moritz
- Boucsein, Clemens
- Rotter, Stefan
- SpringerLink (Online service)
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Statistical properties of superimposed stationary spike trains
Higher-order correlations in non-stationary parallel spike trains: statistical modeling and inference
Testing for higher-order correlations in massively parallel spike trains
CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains
Wechselwirkende stochastische Punktprozesse als Modell für neuronale Aktivität im Neocortex der Säugetiere
Linking neural mass signals and spike train statistics through point process and linear systems theory
Effect of network structure on spike train correlations in networks of integrate-and-fire neurons
Basal ganglia and cortical control of thalamic rebound spikes
Sensory processing in neocortical networks: randomness, specificity and learning
Dynamics of competition between coupled spiking networks in the balanced state
Going beyond Poisson processes: a new statistical framework in neuronal modeling and data analysis
Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks
Statistical properties of superimposed stationary spike trains
Higher-order correlations in non-stationary parallel spike trains: statistical modeling and inference
Testing for higher-order correlations in massively parallel spike trains
CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains
Wechselwirkende stochastische Punktprozesse als Modell für neuronale Aktivität im Neocortex der Säugetiere
Linking neural mass signals and spike train statistics through point process and linear systems theory
Effect of network structure on spike train correlations in networks of integrate-and-fire neurons
Basal ganglia and cortical control of thalamic rebound spikes
Sensory processing in neocortical networks: randomness, specificity and learning
Dynamics of competition between coupled spiking networks in the balanced state
Going beyond Poisson processes: a new statistical framework in neuronal modeling and data analysis