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Journal Abstract Search

599 related items for PubMed ID: 27141854

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  • 3. Markov chain Monte Carlo methods for hierarchical clustering of dynamic causal models.
    Yao Y, Stephan KE.
    Hum Brain Mapp; 2021 Jul; 42(10):2973-2989. PubMed ID: 33826194
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  • 4. Regression DCM for fMRI.
    Frässle S, Lomakina EI, Razi A, Friston KJ, Buhmann JM, Stephan KE.
    Neuroimage; 2017 Jul 15; 155():406-421. PubMed ID: 28259780
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  • 5. A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data.
    Chen S, Bowman FD, Mayberg HS.
    Biometrics; 2016 Jun 15; 72(2):596-605. PubMed ID: 26501687
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  • 7. Inversion of hierarchical Bayesian models using Gaussian processes.
    Lomakina EI, Paliwal S, Diaconescu AO, Brodersen KH, Aponte EA, Buhmann JM, Stephan KE.
    Neuroimage; 2015 Sep 15; 118():133-45. PubMed ID: 26048619
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  • 13. Group-representative functional network estimation from multi-subject fMRI data via MRF-based image segmentation.
    Tang B, Iyer A, Rao V, Kong N.
    Comput Methods Programs Biomed; 2019 Oct 15; 179():104976. PubMed ID: 31443856
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  • 14. Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data.
    Røge RE, Madsen KH, Schmidt MN, Mørup M.
    Neural Comput; 2017 Oct 15; 29(10):2712-2741. PubMed ID: 28777721
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  • 15. Comparing variational Bayes with Markov chain Monte Carlo for Bayesian computation in neuroimaging.
    Nathoo FS, Lesperance ML, Lawson AB, Dean CB.
    Stat Methods Med Res; 2013 Aug 15; 22(4):398-423. PubMed ID: 22642986
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  • 16. Physiologically informed dynamic causal modeling of fMRI data.
    Havlicek M, Roebroeck A, Friston K, Gardumi A, Ivanov D, Uludag K.
    Neuroimage; 2015 Nov 15; 122():355-72. PubMed ID: 26254113
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  • 17. Fast Bayesian whole-brain fMRI analysis with spatial 3D priors.
    Sidén P, Eklund A, Bolin D, Villani M.
    Neuroimage; 2017 Feb 01; 146():211-225. PubMed ID: 27876654
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