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A Rate and History-Preserving Resampling Algorithm for Neural Spike Trains
Resampling methods are popular tools for exploring the statistical structure of neural spike trains. In many applications, it is desirable to have resamples that preserve certain non-Poisson properties, like refractory periods and bursting, and that are also robust to trial-to-trial variability. Pat...
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| Main Authors: | , |
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| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
2009
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| Ábhair: | |
| Rochtain Ar Líne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3065177/ https://ncbi.nlm.nih.gov/pubmed/19018703 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1162/neco.2008.03-08-730 |
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