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Lookup NU author(s): Sundeep Teki, Dr Will Sedley, Professor Tim GriffithsORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
We present an approach for combining high resolution MRI-based myelin mapping with functional information from electroencephalography (EEG) or magnetoencephalography (MEG). The main contribution to the primary currents detectable with EEG and MEG comes from ionic currents in the apical dendrites of cortical pyramidal cells, aligned perpendicularly to the local cortical surface. We provide evidence from an in-vivo experiment that the variation in MRI-based myeloarchitecture measures across the cortex predicts the variation of the current density over individuals and thus is of functional relevance. Equivalent current dipole locations and moments due to pitch onset evoked response fields (ERFs) were estimated by means of a variational Bayesian algorithm. The myeloarchitecture was estimated indirectly from individual high resolution quantitative multiparameter maps (MPMs) acquired at 800 mu m isotropic resolution. Myelin estimates across cortical areas correlated positively with dipole magnitude. This correlation was spatially specific: regions of interest in the auditory cortex provided significantly better models than those covering whole hemispheres. Based on the MPM data we identified the auditory cortical area TE1.2 as the most likely origin of the pitch ERFs measured by MEG. We can now proceed to exploit the higher spatial resolution of quantitative MPMs to identify the cortical origin of M/EEG signals, inform M/EEG source reconstruction and explore structure-function relationships at a fine structural level in the living human brain. (C) 2014 The Authors. Published by Elsevier Inc.
Author(s): Helbling S, Teki S, Callaghan MF, Sedley W, Mohammadi S, Griffiths TD, Weiskopf N, Barnes GR
Publication type: Article
Publication status: Published
Journal: NeuroImage
Year: 2015
Volume: 108
Pages: 377-385
Print publication date: 01/03/2015
Online publication date: 18/12/2014
Acceptance date: 10/12/2014
Date deposited: 09/06/2015
ISSN (print): 1053-8119
ISSN (electronic): 1095-9572
Publisher: Elsevier
URL: http://dx.doi.org/10.1016/j.neuroimage.2014.12.030
DOI: 10.1016/j.neuroimage.2014.12.030
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