Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testing

Network inference algorithms are valuable tools for the study of large-scale neuroimaging datasets. Multivariate transfer entropy is well suited for this task, being a model-free measure that captures nonlinear and lagged dependencies between time series to infer a minimal directed network model. Gr...

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Detalles Bibliográficos
Autores principales: Novelli, Leonardo, Wollstadt, Patricia, Mediano, Pedro, Wibral, Michael, Lizier, Joseph T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2019
Materias:
Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6663300/
https://www.ncbi.nlm.nih.gov/pubmed/31410382
http://dx.doi.org/10.1162/netn_a_00092

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6663300/
https://www.ncbi.nlm.nih.gov/pubmed/31410382
http://dx.doi.org/10.1162/netn_a_00092

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