<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Stevenson C</submitter><funding>MRC UK MEG Partnership Grant</funding><funding>Leverhulme Trust Early Career Fellowship</funding><funding>J Jacob Astor Charitable Trust</funding><funding>Medical Research Council</funding><funding>Wellcome Trust</funding><funding>MRC</funding><pagination>89-95</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC4073649</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>94</volume><pubmed_abstract>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 cort</pubmed_abstract><journal>NeuroImage</journal><pubmed_title>Does function fit structure? A ground truth for non-invasive neuroimaging.</pubmed_title><pmcid>PMC4073649</pmcid><funding_grant_id>MR/K005464/1</funding_grant_id><funding_grant_id>091593</funding_grant_id><funding_grant_id>MC_US_A060_0046</funding_grant_id><funding_grant_id>MC_U105579226</funding_grant_id><pubmed_authors>Stevenson C</pubmed_authors><pubmed_authors>Barnes G</pubmed_authors><pubmed_authors>Morris P</pubmed_authors><pubmed_authors>Henson R</pubmed_authors><pubmed_authors>Troebinger L</pubmed_authors><pubmed_authors>Penny W</pubmed_authors><pubmed_authors>Lopez JD</pubmed_authors><pubmed_authors>Mattout J</pubmed_authors><pubmed_authors>Brookes M</pubmed_authors><pubmed_authors>Hillebrand A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Does function fit structure? A ground truth for non-invasive neuroimaging.</name><description>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 cort</description><dates><release>2014-01-01T00:00:00Z</release><publication>2014 Jul</publication><modification>2025-06-01T00:33:01.083Z</modification><creation>2025-06-01T00:33:01.083Z</creation></dates><accession>S-EPMC4073649</accession><cross_references><pubmed>24636880</pubmed><doi>10.1016/j.neuroimage.2014.02.033</doi></cross_references></HashMap>