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Bayesian Inference for Generalized Linear Models for Spiking Neurons
Generalized Linear Models (GLMs) are commonly used statistical methods for modelling the relationship between neural population activity and presented stimuli. When the dimension of the parameter space is large, strong regularization has to be used in order to fit GLMs to datasets of realistic size...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Research Foundation
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2889714/ https://www.ncbi.nlm.nih.gov/pubmed/20577627 http://dx.doi.org/10.3389/fncom.2010.00012 |