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Structure predicts function: Combining non-invasive electrophysiology with in-vivo histology

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.

Publication metadata

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


DOI: 10.1016/j.neuroimage.2014.12.030


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Funder referenceFunder name
G.-A.-Lienert Stiftung
LOEWE Grant "Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF)"
Wellcome Trust
616905European Research Council under the European Union
MO 2397/1-1Deutsche Forschungsgemeinschaft (DFG)
MR/K005464/1MRC UK MEG Partnership Grant