A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem

S. Baillet; L. Garnero

doi:10.1109/10.568913

A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem

IEEE Transactions on Biomedical Engineering ◽

10.1109/10.568913 ◽

1997 ◽

Vol 44 (5) ◽

pp. 374-385 ◽

Cited By ~ 211

Author(s):

S. Baillet ◽

L. Garnero

Keyword(s):

Inverse Problem ◽

Bayesian Approach ◽

Meg Inverse Problem

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BAYESIAN APPROACH TO THE STATISTICAL INVERSE PROBLEM OF SCATTEROMETRY: COMPARISON OF THREE SURROGATE MODELS

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2015013050 ◽

2015 ◽

Vol 5 (6) ◽

pp. 511-526 ◽

Cited By ~ 4

Author(s):

Sebastian Heidenreich ◽

Hermann Gross ◽

Markus Bar

Keyword(s):

Inverse Problem ◽

Bayesian Approach ◽

Surrogate Models ◽

Statistical Inverse Problem

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A probabilistic solution to the MEG inverse problem via MCMC methods: the reversible jump and parallel tempering algorithms

IEEE Transactions on Biomedical Engineering ◽

10.1109/10.918592 ◽

2001 ◽

Vol 48 (5) ◽

pp. 533-542 ◽

Cited By ~ 24

Author(s):

C. Bertrand ◽

M. Ohmi ◽

R. Suzuki ◽

H. Kado

Keyword(s):

Inverse Problem ◽

Parallel Tempering ◽

Mcmc Methods ◽

Reversible Jump ◽

Meg Inverse Problem ◽

Probabilistic Solution

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Bayesian theory and artificial neural network approach in MEG inverse problem

Proceedings. International Conference on Machine Learning and Cybernetics ◽

10.1109/icmlc.2002.1167458 ◽

2003 ◽

Author(s):

Sheng Ye ◽

Jie Hu

Keyword(s):

Neural Network ◽

Inverse Problem ◽

Artificial Neural Network ◽

Bayesian Theory ◽

Network Approach ◽

Neural Network Approach ◽

Meg Inverse Problem ◽

Artificial Neural ◽

Artificial Neural Network Approach

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Neuromagnetic source parameter estimation of MEG inverse problem by a synthetic nonlinear optimization method

IEEE 2002 International Conference on Communications, Circuits and Systems and West Sino Expositions ◽

10.1109/icccas.2002.1179006 ◽

2003 ◽

Author(s):

Jing Hu ◽

Jie Hu

Keyword(s):

Inverse Problem ◽

Parameter Estimation ◽

Nonlinear Optimization ◽

Optimization Method ◽

Source Parameter ◽

Meg Inverse Problem ◽

Nonlinear Optimization Method

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Gaussian mixture prior distribution on artifactual current for MEG inverse problem

Neuroscience Research ◽

10.1016/j.neures.2010.07.1472 ◽

2010 ◽

Vol 68 ◽

pp. e332

Author(s):

Taku Yoshioka ◽

Ken-ichi Morishige ◽

Mitsuo Kawato ◽

Masa-aki Sato

Keyword(s):

Inverse Problem ◽

Prior Distribution ◽

Gaussian Mixture ◽

Meg Inverse Problem ◽

Mixture Prior

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Multivariate source prelocalization (MSP): Use of functionally informed basis functions for better conditioning the MEG inverse problem

NeuroImage ◽

10.1016/j.neuroimage.2005.01.026 ◽

2005 ◽

Vol 26 (2) ◽

pp. 356-373 ◽

Cited By ~ 33

Author(s):

J MATTOUT ◽

M PELEGRINIISSAC ◽

L GARNERO ◽

H BENALI

Keyword(s):

Inverse Problem ◽

Basis Functions ◽

Meg Inverse Problem

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Solving the MEG Inverse Problem: A Robust Two-Way Regularization Method

Technometrics ◽

10.1080/00401706.2014.887594 ◽

2015 ◽

Vol 57 (1) ◽

pp. 123-137

Author(s):

Siva Tian ◽

Jianhua Z. Huang ◽

Haipeng Shen

Keyword(s):

Inverse Problem ◽

Regularization Method ◽

Meg Inverse Problem

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A Bayesian approach to the ecosystem inverse problem

Ecological Modelling ◽

10.1016/s0304-3800(03)00186-8 ◽

2003 ◽

Vol 168 (1-2) ◽

pp. 39-55 ◽

Cited By ~ 37

Author(s):

Michael Dowd ◽

Renate Meyer

Keyword(s):

Inverse Problem ◽

Bayesian Approach

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Introducing PET priors in the EEG/MEG inverse problem

Electroencephalography and Clinical Neurophysiology ◽

10.1016/s0013-4694(97)87982-9 ◽

1997 ◽

Vol 103 (1) ◽

pp. 18

Author(s):

J Lachaux

Keyword(s):

Inverse Problem ◽

Meg Inverse Problem

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Regularization of EEG/MEG Inverse Problem with a Local Cortical Wave Pattern

Information and Control Systems ◽

10.15217/issn1684-8853.2017.5.12 ◽

2017 ◽

Vol 5 (90) ◽

pp. 12-20 ◽

Cited By ~ 1

Author(s):

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...

Keyword(s):

Inverse Problem ◽

Wave Pattern ◽

Meg Inverse Problem

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