A functional network estimation method of resting-state fMRI using a hierarchical Markov random field

@article{Liu2014AFN,
  title={A functional network estimation method of resting-state fMRI using a hierarchical Markov random field},
  author={Wei Liu and Suyash P. Awate and Jeffrey S. Anderson and P. Thomas Fletcher},
  journal={NeuroImage},
  year={2014},
  volume={100},
  pages={520-34}
}
We propose a hierarchical Markov random field model for estimating both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo… CONTINUE READING
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