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Unsupervised Learning of Functional Network Dynamics in Resting State fMRI
Research in recent years has provided some evidence of temporal non-stationarity of functional connectivity in resting state fMRI. In this paper, we present a novel methodology that can decode connectivity dynamics into a temporal sequence of hidden network “states” for each subject, using a Hidden...
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| Autors principals: | , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2013
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3974209/ https://ncbi.nlm.nih.gov/pubmed/24683988 |
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