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dc.contributor.authorLópez Hincapié, José David-
dc.contributor.authorValencia, Felipe-
dc.contributor.authorFlandin, Guillaume-
dc.contributor.authorPenny, Will D.-
dc.contributor.authorBarnes, Gareth Robert-
dc.date.accessioned2024-08-31T12:28:02Z-
dc.date.available2024-08-31T12:28:02Z-
dc.date.issued2017-
dc.identifier.citationJ.D. López, F. Valencia, G. Flandin, W. Penny, G.R. Barnes, Reconstructing anatomy from electro-physiological data, NeuroImage, Volume 163, 2017, Pages 480-486, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2017.06.049 (https://www.sciencedirect.com/science/article/pii/S1053811917305207)spa
dc.identifier.issn1053-8119-
dc.identifier.urihttps://hdl.handle.net/10495/41654-
dc.description.abstractABSTRACT: Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. We demonstrate that both empirical and simulated MEG data give rise to consistent and plausible anatomical estimates. Importantly, the estimation of structure from MEG data can be quantified in terms of millimetres from the true brain structure. We show, for simulated data, that the functional assumptions which are closer to the functional ground-truth give rise to anatomical estimates that are closer to the true anatomy.spa
dc.format.extent7 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherElsevierspa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa
dc.rightsinfo:eu-repo/semantics/openAccessspa
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/co/*
dc.titleReconstructing anatomy from electro-physiological dataspa
dc.typeinfo:eu-repo/semantics/articlespa
dc.publisher.groupSistemas Embebidos e Inteligencia Computacional (SISTEMIC)spa
dc.identifier.doi10.1016/j.neuroimage.2017.06.049-
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
dc.identifier.eissn1095-9572-
oaire.citationtitleNeuroImagespa
oaire.citationstartpage480spa
oaire.citationendpage486spa
oaire.citationvolume163spa
dc.rights.creativecommonshttps://creativecommons.org/licenses/by/4.0/spa
dc.publisher.placeOrlando, Estados Unidosspa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.redcolhttps://purl.org/redcol/resource_type/ARTspa
dc.type.localArtículo de investigaciónspa
dc.subject.decsEncéfalo - diagnóstico por imagen-
dc.subject.decsBrain - diagnostic imaging-
dc.subject.decsAlgoritmos-
dc.subject.decsAlgorithms-
dc.subject.decsSimulación por Computador-
dc.subject.decsComputer Simulation-
dc.subject.decsInterpretación de Imagen Asistida por Computador-
dc.subject.decsImage Interpretation, Computer-Assisted-
dc.subject.decsMagnetoencefalografía-
dc.subject.decsMagnetoencephalography-
dc.subject.decsModelos Neurológicos-
dc.subject.decsModels, Neurological-
dc.description.researchgroupidCOL0010717spa
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D001921-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D000465-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D003198-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D007090-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D015225-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D008959-
dc.relation.ispartofjournalabbrevNeuroimagespa
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