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dc.contributor.authorLópez Hincapié, José David-
dc.contributor.authorStevenson, Claire M.-
dc.contributor.authorBrookes, Matthew J.-
dc.contributor.authorTroebinger, Luzia-
dc.contributor.authorMattout, Jérémie-
dc.contributor.authorPenny, Will D.-
dc.contributor.authorMorris, Peter Gordon-
dc.contributor.authorHillebrand, Arjan-
dc.contributor.authorHenson, Richard N.-
dc.contributor.authorBarnes, Gareth Robert-
dc.date.accessioned2024-08-31T13:01:30Z-
dc.date.available2024-08-31T13:01:30Z-
dc.date.issued2014-
dc.identifier.citation"Claire Stevenson, Matthew Brookes, José David López, Luzia Troebinger, Jeremie Mattout, William Penny, Peter Morris, Arjan Hillebrand, Richard Henson, Gareth Barnes, Does function fit structure? A ground truth for non-invasive neuroimaging, NeuroImage, Volume 94, 2014, Pages 89-95, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2014.02.033. (https://www.sciencedirect.com/science/article/pii/S1053811914001487) "spa
dc.identifier.issn1053-8119-
dc.identifier.urihttps://hdl.handle.net/10495/41655-
dc.description.abstractABSTRACT: There are now a number of non-invasive methods to image human brain function in-vivo. However, the accuracy of these images remains unknown and can currently only be estimated through the use of invasive recordings to generate a functional ground truth. Neuronal activity follows grey matter structure and accurate estimates of neuronal activity will have stronger support from accurate generative models of anatomy. Here we introduce a general framework that, for the first time, enables the spatial distortion of a functional brain image to be estimated empirically. We use a spherical harmonic decomposition to modulate each cortical hemisphere from its original form towards progressively simpler structures, ending in an ellipsoid. Functional estimates that are not supported by the simpler cortical structures have less inherent spatial distortion. This method allows us to compare directly between magnetoencephalography (MEG) source reconstructions based upon different assumption sets without recourse to functional ground truth.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.titleDoes function fit structure? A ground truth for non-invasive neuroimagingspa
dc.typeinfo:eu-repo/semantics/articlespa
dc.publisher.groupSistemas Embebidos e Inteligencia Computacional (SISTEMIC)spa
dc.identifier.doi10.1016/j.neuroimage.2014.02.033-
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.citationstartpage89spa
oaire.citationendpage95spa
oaire.citationvolume94spa
dc.rights.creativecommonshttps://creativecommons.org/licenses/by/4.0/spa
oaire.fundernameMedical Research Councilspa
oaire.fundernameWellcome Trustspa
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.decsAlgoritmos-
dc.subject.decsAlgorithms-
dc.subject.decsModelos Neurológicos-
dc.subject.decsModels, Neurological-
dc.subject.decsMapeo Encefálico-
dc.subject.decsBrain Mapping-
dc.subject.decsSimulación por Computador-
dc.subject.decsComputer Simulation-
dc.subject.decsMagnetoencefalografía-
dc.subject.decsMagnetoencephalography-
dc.subject.decsModelos Neurológicos-
dc.subject.decsModels, Neurological-
dc.subject.decsModelos Anatómicos-
dc.subject.decsModels, Anatomic-
dc.subject.decsSustancia Gris-
dc.subject.decsGray Matter-
dc.subject.decsReproducibilidad de los Resultados-
dc.subject.decsReproducibility of Results-
dc.subject.decsSensibilidad y Especificidad-
dc.subject.decsSensitivity and Specificity-
dc.description.researchgroupidCOL0010717spa
oaire.awardnumberMR/K005464/1spa
oaire.awardnumber091593spa
oaire.awardnumberMC_US_A060_0046spa
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D000465-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D008959-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D001931-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D003198-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D015225-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D008959-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D008953-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D066128-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D015203-
dc.subject.meshurihttps://id.nlm.nih.gov/mesh/D012680-
dc.relation.ispartofjournalabbrevNeuroimagespa
oaire.funderidentifier.rorRoR:03x94j517-
oaire.funderidentifier.rorRoR:029chgv08-
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