{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Oliveira R"],"funding":["Swiss National Science Foundation","Fondation Roger de Spoelberch"],"pagination":["874023"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9070985"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16"],"pubmed_abstract":["<h4>Purpose</h4>We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired <i>in vivo</i> in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.<h4>Theory</h4>The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [<i>P</i>(<i>r</i>)] and (2) the g-ratio of the individual axons that compose this tract [<i>g</i>(<i>r</i>)]. <i>P</i>(<i>r</i>) is assumed to follow a Gamma distribution with mode and scale parameters, <i>M</i> and θ, and <i>g</i"],"journal":["Frontiers in neuroscience"],"pubmed_title":["<i>In vivo</i> Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data."],"pmcid":["PMC9070985"],"funding_grant_id":["320030_184784","320030","196194","CRSK-3_196194","184784"],"pubmed_authors":["Di Domenicantonio G","Oliveira R","Pelentritou A","Lutti A","De Lucia M"],"additional_accession":[]},"is_claimable":false,"name":"<i>In vivo</i> Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data.","description":"<h4>Purpose</h4>We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired <i>in vivo</i> in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.<h4>Theory</h4>The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [<i>P</i>(<i>r</i>)] and (2) the g-ratio of the individual axons that compose this tract [<i>g</i>(<i>r</i>)]. <i>P</i>(<i>r</i>) is assumed to follow a Gamma distribution with mode and scale parameters, <i>M</i> and θ, and <i>g</i","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-04-08T09:52:02.06Z","creation":"2025-04-04T10:02:01.417Z"},"accession":"S-EPMC9070985","cross_references":{"pubmed":["35527816"],"doi":["10.3389/fnins.2022.874023"]}}