dc.contributor.author | Lucena Gómez, Gustavo | |
dc.contributor.author | Peigneux, Philippe | |
dc.contributor.author | Wens, Vincent | |
dc.contributor.author | Bourguignon, Mathieu | |
dc.date.accessioned | 2021-02-10T09:00:44Z | |
dc.date.available | 2021-02-10T09:00:44Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Gustavo Lucena Gómez, Philippe Peigneux, Vincent Wens, Mathieu Bourguignon, Localization accuracy of a common beamformer for the comparison of two conditions, NeuroImage, Volume 230, 2021, 117793, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2021.117793. | es_ES |
dc.identifier.issn | 1053-8119 | |
dc.identifier.uri | http://hdl.handle.net/10810/50129 | |
dc.description | Available online 23 January 2021. | es_ES |
dc.description.abstract | The linearly constrained minimum variance beamformer is frequently used to reconstruct sources underpinning neuromagnetic recordings. When reconstructions must be compared across conditions, it is considered good prac- tice to use a single, “common ”beamformer estimated from all the data at once. This is to ensure that differences between conditions are not ascribable to differences in beamformer weights. Here, we investigate the localiza- tion accuracy of such a common beamformer. Based on theoretical derivations, we first show that the common beamformer leads to localization errors in source reconstruction. We then turn to simulations in which we at- tempt to reconstruct a (genuine) source in a first condition, while considering a second condition in which there is an (interfering) source elsewhere in the brain. We estimate maps of mislocalization and assess statistically the difference between “standard ”and “common ”beamformers. We complement our findings with an application to experimental MEG data. The results show that the common beamformer may yield significant mislocalization. Specifically, the common beamformer may force the genuine source to be reconstructed closer to the interfering source than it really is. As the same applies to the reconstruction of the interfering source, both sources are pulled closer together than they are. This observation was further illustrated in experimental data. Thus, although the common beamformer allows for the comparison of conditions, in some circumstances it introduces localization inaccuracies. We recommend alternative approaches to the general problem of comparing conditions. | es_ES |
dc.description.sponsorship | G.L.G. was supported by postdoctoral grant from FNRS-FWO Excel- lence Of Science project Memodyn (ID EOS 30446199). M.B. has been supported by the program Attract of Innoviris (grant 2015-BB2B-10), by the Spanish Ministry of Economy and Competitiveness (grant PSI2016- 77175-P), and by the Marie Sklodowska-Curie Action of the European Commission (grant 743562). This study and the MEG project at CUB Hôpital Erasme were financially supported by the Fonds Erasme (Re- search Convention: “Les Voies du Savoir ”, Fonds Erasme, Brussels, Bel- gium). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | NeuroImage | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/PSI2016-77175-P | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/MSC/IF/ 743562 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | Beamformer | es_ES |
dc.subject | Functional mapping | es_ES |
dc.subject | Magnetoencephalography | es_ES |
dc.subject | Linearly constrained minimum variance | es_ES |
dc.subject | Source estimation | es_ES |
dc.title | Localization accuracy of a common beamformer for the comparison of two conditions | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license | es_ES |
dc.relation.publisherversion | https://www.sciencedirect.com/journal/neuroimage | es_ES |
dc.identifier.doi | 10.1016/j.neuroimage.2021.117793 | |