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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...
| Autores principales: | , , , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Academic Press
2010
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| Materias: | |
| 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 |