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Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks
A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and i...
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| Publicado no: | Neuroimage |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Academic Press
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6565932/ https://ncbi.nlm.nih.gov/pubmed/29746906 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2018.04.077 |
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