Estimation of Regional Activation Maps and Interdependencies from Minimum Norm Estimates of Magnetoencephalography (MEG) Data

2014 ◽  
pp. 267-289
Author(s):  
Abdou Mousas ◽  
Panagiotis G. Simos ◽  
Roozbeh Rezaie ◽  
Andrew C. Papanicolaou
Keyword(s):  
Minimum Norm ◽  
Norm Estimates

Interpreting magnetic fields of the brain: minimum norm estimates

1994 ◽  
Vol 32 (1) ◽  
pp. 35-42 ◽  
Author(s):  
M. S. Hämäläinen ◽  
R. J. Ilmoniemi
Keyword(s):  
Magnetic Fields ◽  
Minimum Norm ◽  
Norm Estimates ◽  
The Brain

scholarly journals Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics

NeuroImage ◽  
2011 ◽  
Vol 54 (3) ◽  
pp. 1966-1974 ◽  
Author(s):  
Olaf Hauk ◽  
Daniel G. Wakeman ◽  
Richard Henson
Keyword(s):  
Minimum Norm ◽  
Norm Estimates

scholarly journals Minimum norm estimates in MEG can delineate the onset of interictal epileptic discharges: A comparison with ECoG findings

2013 ◽  
Vol 2 ◽  
pp. 663-669 ◽  
Author(s):  
Yuji Kanamori ◽  
Hiroshi Shigeto ◽  
Naruhito Hironaga ◽  
Koichi Hagiwara ◽  
Taira Uehara ◽  
...  
Keyword(s):  
Minimum Norm ◽  
Norm Estimates ◽  
Epileptic Discharges

Assessing and improving the spatial accuracy in MEG source localization by depth-weighted minimum-norm estimates

NeuroImage ◽  
2006 ◽  
Vol 31 (1) ◽  
pp. 160-171 ◽  
Author(s):  
Fa-Hsuan Lin ◽  
Thomas Witzel ◽  
Seppo P. Ahlfors ◽  
Steven M. Stufflebeam ◽  
John W. Belliveau ◽  
...  
Keyword(s):  
Source Localization ◽  
Minimum Norm ◽  
Spatial Accuracy ◽  
Norm Estimates

Anatomically and Functionally Constrained Minimum-Norm Estimates

2010 ◽  
pp. 186-215 ◽  
Author(s):  
Matti S. Hämäläinen ◽  
Fa-Hsuan Lin ◽  
John C. Mosher
Keyword(s):  
Minimum Norm ◽  
Norm Estimates

Magnetic nanoparticle imaging by means of minimum norm estimates from remanence measurements

2008 ◽  
Vol 46 (12) ◽  
pp. 1177-1185 ◽  
Author(s):  
Daniel Baumgarten ◽  
Mario Liehr ◽  
Frank Wiekhorst ◽  
Uwe Steinhoff ◽  
Peter Münster ◽  
...  
Keyword(s):  
Magnetic Nanoparticle ◽  
Minimum Norm ◽  
Norm Estimates ◽  
Nanoparticle Imaging

scholarly journals MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ana-Sofía Hincapié ◽  
Jan Kujala ◽  
Jérémie Mattout ◽  
Sebastien Daligault ◽  
Claude Delpuech ◽  
...  
Keyword(s):  
Tikhonov Regularization ◽  
Spectral Power ◽  
Regularization Parameter ◽  
Signal To Noise Ratio ◽  
Minimum Norm ◽  
Norm Estimates ◽  
Source Data ◽  
Ill Posed ◽  
Source Level ◽  
Oscillatory Coupling

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.

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