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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...
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| Foilsithe in: | Netw Neurosci |
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| Main Authors: | , , , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
MIT Press
2019
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| Ábhair: | |
| Rochtain Ar Líne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6663300/ https://ncbi.nlm.nih.gov/pubmed/31410382 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1162/netn_a_00092 |
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