Ten simple rules for dynamic causal modeling

Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and...

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Detalles Bibliográficos
Autores principales: Stephan, K.E., Penny, W.D., Moran, R.J., den Ouden, H.E.M., Daunizeau, J., Friston, K.J.
Formato: Texto
Lenguaje:English
Publicado: Academic Press 2010
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825373/
https://www.ncbi.nlm.nih.gov/pubmed/19914382
http://dx.doi.org/10.1016/j.neuroimage.2009.11.015

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825373/
https://www.ncbi.nlm.nih.gov/pubmed/19914382
http://dx.doi.org/10.1016/j.neuroimage.2009.11.015

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