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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MIT Press
2019
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| Materias: | |
| 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 |