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Publications about 'EM'
Articles in journal or book chapters
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K.H Brodersen,
T.M. Schofield,
A.P. Leff,
C.S. Ong,
E.I. Lomakina,
J.M. Buhmann,
and K.E. Stephan.
Generative Embedding for Model-Based Classification of fMRI Data.
PLOS Computational Biology,
7(6):e1002079,
2011.
Keyword(s): DCM.
[bibtex-entry]
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R.N.A. Henson,
D.G. Wakeman,
V. Litvak,
and K.J. Friston.
A parametric empirical Bayesian framework for the EEG/MEG inverse problem: generative models for multi-subject and multi-modal integration.
Frontiers in Human Neuroscience,
5(76),
2011.
Keyword(s): EEG,
MEG,
Bayesian.
[bibtex-entry]
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R.N.A. Henson,
G. Flandin,
K.J. Friston,
and J. Mattout.
A Parametric Empirical Bayesian framework for fMRI-constrained MEG/EEG source reconstruction.
Human Brain Mapping,
31(10):1512-1531,
2010.
[bibtex-entry]
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C. Phillips,
J. Mattout,
M.D. Rugg,
P. Maquet,
and K.J. Friston.
An empirical Bayesian solution to the source reconstruction problem in EEG.
NeuroImage,
24:997-1011,
2005.
Keyword(s): EEG,
bayesian.
[bibtex-entry]
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K.J. Friston and J. Ashburner.
Generative and recognition models for neuroanatomy.
NeuroImage,
23(1):21-24,
2004.
Keyword(s): spatial,
Bayesian,
EM.
[bibtex-entry]
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K.J. Friston and W.D. Penny.
Posterior probability maps and SPMs.
NeuroImage,
19(3):1240-1249,
2003.
Keyword(s): Bayesian,
hierarchical,
PPM,
EM.
[bibtex-entry]
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W.D. Penny and K.J. Friston.
Mixtures of General Linear Models for Functional Neuroimaging.
IEEE Transactions on Medical Imaging,
22(4):504-514,
2003.
Keyword(s): Mixture,
GLM,
Bayesian,
fMRI,
spatial,
EM.
[bibtex-entry]
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K.J. Friston,
W.D. Penny,
C. Phillips,
S.J. Kiebel,
G. Hinton,
and J. Ashburner.
Classical and Bayesian Inference in Neuroimaging: Theory.
NeuroImage,
16:465-483,
2002.
Keyword(s): Bayesian,
PPM,
EM,
REML.
[bibtex-entry]
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Last modified: Mon Feb 4 11:41:48 2013
Author: spm.
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Introduction