Solution of the EEG inverse problem by random dipole sampling
Created March 19, 2026
Updated on March 25, 2026
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MainTitle
Solution of the EEG inverse problem by random dipole sampling
Original ids
10.1088/1361-6420/ad14a1; 20.500.14243/452173; 20.500.14243/562916; 11573/1696446
Type
publication
bestAccessRight
OPEN
countries
Italy
Creator/Author
Full name
Della Cioppa, Lorenzo, orcid: 0000-0001-8222-112x ; Tartaglione, Michela, orcid: 0000-0003-0249-6962 ; Pascarella, Annalisa, orcid: 0000-0001-8795-0815 ; Pitolli, Francesca, orcid: 0000-0002-7159-0533
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Description
<jats:title>Abstract</jats:title> <jats:p>Electroencephalography (EEG) source imaging aims to reconstruct brain activity maps from the neuroelectric potential difference measured on the skull. To obtain the brain activity map, we need to solve an ill-posed and ill-conditioned inverse problem that requires regularization techniques to make the solution viable. When dealing with real-time applications, dimensionality reduction techniques can be used to reduce the computational load required to evaluate the numerical solution of the EEG inverse problem. To this end, in this paper we use the random dipole sampling method, in which a Monte Carlo technique is used to reduce the number of neural sources. This is equivalent to reducing the number of the unknowns in the inverse problem and can be seen as a first regularization step. Then, we solve the reduced EEG inverse problem with two popular inversion methods, the weighted Minimum Norm Estimate (wMNE) and the standardized LOw Resolution brain Electromagnetic TomogrAphy (sLORETA). The main result of this paper is the error estimates of the reconstructed activity map obtained with the randomized version of wMNE and sLORETA. Numerical experiments on synthetic EEG data demonstrate the effectiveness of the random dipole sampling method.</jats:p>
Publication Date
2023-12-27
Publisher
IOP Publishing
Subjects
EEG imaging, underdetermined inverse problem, random sampling, inversion method, wMNE, sLORETA; Biomedical imaging and signal processing; sLORETA; Randomized algorithms; random sampling; inversion method; Monte Carlo methods; EEG imaging; 01 natural sciences; 03 medical and health sciences; underdetermined inverse problem; 0302 clinical medicine; Ill-posedness and regularization problems in numerical linear algebra; 0101 mathematics; EEG imagingunderdetermined inverse problem; wMNE
isGreen
true
isInDiamondJournal
false
Publication
Name
Inverse Problems
Publication
Article
Starting page
025006
issnOnline
1361-6420
issnPrinted
0266-5611
vol
40
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Last Updated
March 25, 2026, 10:48 (UTC)
Created
March 19, 2026, 00:29 (UTC)
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