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Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification
Generalized linear models (GLMs) represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2013
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3836720/ https://www.ncbi.nlm.nih.gov/pubmed/24278006 http://dx.doi.org/10.1371/journal.pcbi.1003356 |