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...

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Detalles Bibliográficos
Autores principales: Gerwinn, Sebastian, Macke, Jakob H., Bethge, Matthias
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2010
Materias:
Neuroscience
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

Internet

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

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