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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Academic Press
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6565932/ https://www.ncbi.nlm.nih.gov/pubmed/29746906 http://dx.doi.org/10.1016/j.neuroimage.2018.04.077 |