Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks
A Bayesian model for sparse, hierarchical inverse 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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal article |
| Published: |
Elsevier
2018
|