scholarly journals Where Bayes tweaks Gauss: Conditionally Gaussian priors for stable multi-dipole estimation

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Alessandro Viani ◽  
Gianvittorio Luria ◽  
Alberto Sorrentino ◽  
Harald Bornfleth
Keyword(s):  
Dipole Estimation

Dipole estimation errors due to differences in modeling anisotropic conductivities in realistic head models for EEG source analysis

2008 ◽  
Vol 53 (7) ◽  
pp. 1877-1894 ◽  
Author(s):  
Hans Hallez ◽  
Bart Vanrumste ◽  
Peter Van Hese ◽  
Steven Delputte ◽  
Ignace Lemahieu
Keyword(s):  
Source Analysis ◽  
Estimation Errors ◽  
Eeg Source Analysis ◽  
Dipole Estimation

sLORETA-qm for interictal MEG epileptic spike analysis: Comparison of location and quantity with equivalent dipole estimation

2012 ◽  
Vol 123 (8) ◽  
pp. 1496-1501 ◽  
Author(s):  
T. Uda ◽  
N. Tsuyuguchi ◽  
E. Okumura ◽  
S. Sakamoto ◽  
M. Morino ◽  
...  
Keyword(s):  
Equivalent Dipole ◽  
Dipole Estimation ◽  
Spike Analysis ◽  
Epileptic Spike

Dipole estimation of alpha EEG during alcohol ingestion in males genotypes for ALDH2

Life Sciences ◽  
2000 ◽  
Vol 67 (10) ◽  
pp. 1163-1173 ◽  
Author(s):  
Koichiro Hara ◽  
Omi Terasaki ◽  
Yoshiro Okubo
Keyword(s):  
Alcohol Ingestion ◽  
Dipole Estimation

scholarly journals Highly Automated Dipole EStimation (HADES)

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
C. Campi ◽  
A. Pascarella ◽  
A. Sorrentino ◽  
M. Piana
Keyword(s):  
Inverse Problem ◽  
User Interface ◽  
Graphical User Interface ◽  
Particle Filtering ◽  
Synthetic Data ◽  
Nonlinear Relationship ◽  
Data Set ◽  
Automatic Estimation ◽  
Dipole Estimation ◽  
Dipolar Model

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed a new Bayesian approach, particle filtering, based on dynamical tracking of the dipole constellation. Contrary to many dipole-based methods, particle filtering does not assume stationarity of the source configuration: the number of dipoles and their positions are estimated and updated dynamically during the course of the MEG sequence. We have now developed a Matlab-based graphical user interface, which allows nonexpert users to do automatic dipole estimation from MEG data with particle filtering. In the present paper, we describe the main features of the software and show the analysis of both a synthetic data set and an experimental dataset.

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