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A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons
We propose a scalable semiparametric Bayesian model to capture dependencies among multiple neurons by detecting their co-firing (possibly with some lag time) patterns over time. After discretizing time so there is at most one spike at each interval, the resulting sequence of 1’s (spike) and 0’s (sil...
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| Publicado no: | Neural Comput |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4377280/ https://ncbi.nlm.nih.gov/pubmed/24922500 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1162/NECO_a_00631 |
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