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Article: A two-way regularization method for MEG source reconstruction

TitleA two-way regularization method for MEG source reconstruction
Authors
KeywordsMeg
Inverse problem
Two-way regularization
Spatio-temporal
Issue Date2012
Citation
Annals of Applied Statistics, 2012, v. 6, n. 3, p. 1021-1046 How to Cite?
AbstractThe MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.
Persistent Identifierhttp://hdl.handle.net/10722/219678
ISSN
2015 Impact Factor: 1.432
2015 SCImago Journal Rankings: 1.533

 

DC FieldValueLanguage
dc.contributor.authorTian, Tian Siva-
dc.contributor.authorHuang, Jianhua Z.-
dc.contributor.authorShen, Haipeng-
dc.contributor.authorLi, Zhimin-
dc.date.accessioned2015-09-23T02:57:42Z-
dc.date.available2015-09-23T02:57:42Z-
dc.date.issued2012-
dc.identifier.citationAnnals of Applied Statistics, 2012, v. 6, n. 3, p. 1021-1046-
dc.identifier.issn1932-6157-
dc.identifier.urihttp://hdl.handle.net/10722/219678-
dc.description.abstractThe MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.-
dc.languageeng-
dc.relation.ispartofAnnals of Applied Statistics-
dc.subjectMeg-
dc.subjectInverse problem-
dc.subjectTwo-way regularization-
dc.subjectSpatio-temporal-
dc.titleA two-way regularization method for MEG source reconstruction-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1214/11-AOAS531-
dc.identifier.scopuseid_2-s2.0-84870021233-
dc.identifier.volume6-
dc.identifier.issue3-
dc.identifier.spage1021-
dc.identifier.epage1046-
dc.identifier.eissn1941-7330-

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