Literature DB >> 24434678

Comparison of three-shell and simplified volume conductor models in magnetoencephalography.

Matti Stenroos1, Alexander Hunold2, Jens Haueisen2.   

Abstract

Experimental MEG source imaging studies have typically been carried out with either a spherically symmetric head model or a single-shell boundary-element (BEM) model that is shaped according to the inner skull surface. The concepts and comparisons behind these simplified models have led to misunderstandings regarding the role of skull and scalp in MEG. In this work, we assess the forward-model errors due to different skull/scalp approximations and due to differences and errors in model geometries. We built five anatomical models of a volunteer using a set of T1-weighted MR scans and three common toolboxes. Three of the models represented typical models in experimental MEG, one was manually constructed, and one contained a major segmentation error at the skull base. For these anatomical models, we built forward models using four simplified approaches and a three-shell BEM approach that has been used as reference in previous studies. Our reference model contained in addition the skull fine-structure (spongy bone). We computed signal topographies for cortically constrained sources in the left hemisphere and compared the topographies using relative error and correlation metrics. The results show that the spongy bone has a minimal effect on MEG topographies, and thus the skull approximation of the three-shell model is justified. The three-shell model performed best, followed by the corrected-sphere and single-shell models, whereas the local-spheres and single-sphere models were clearly worse. The three-shell model was the most robust against the introduced segmentation error. In contrast to earlier claims, there was no noteworthy difference in the computation times between the realistically-shaped and sphere-based models, and the manual effort of building a three-shell model and a simplified model is comparable. We thus recommend the realistically-shaped three-shell model for experimental MEG work. In cases where this is not possible, we recommend a realistically-shaped corrected-sphere or single-shell model.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Boundary element method; Forward model; Magnetoencephalography; Source imaging; Spherical model

Mesh:

Year:  2014        PMID: 24434678     DOI: 10.1016/j.neuroimage.2014.01.006

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  26 in total

Review 1.  Magnetoencephalography in the study of brain dynamics.

Authors:  Vittorio Pizzella; Laura Marzetti; Stefania Della Penna; Francesco de Pasquale; Filippo Zappasodi; Gian Luca Romani
Journal:  Funct Neurol       Date:  2014 Oct-Dec

2.  Attention modulates topology and dynamics of auditory sensory gating.

Authors:  Sanja Josef Golubic; Miljenka Jelena Jurasic; Ana Susac; Ralph Huonker; Theresa Gotz; Jens Haueisen
Journal:  Hum Brain Mapp       Date:  2019-03-18       Impact factor: 5.038

3.  Measuring MEG closer to the brain: Performance of on-scalp sensor arrays.

Authors:  Joonas Iivanainen; Matti Stenroos; Lauri Parkkonen
Journal:  Neuroimage       Date:  2016-12-19       Impact factor: 6.556

4.  Magnetoencephalography and the infant brain.

Authors:  Yu-Han Chen; Joni Saby; Emily Kuschner; William Gaetz; J Christopher Edgar; Timothy P L Roberts
Journal:  Neuroimage       Date:  2019-01-24       Impact factor: 6.556

5.  Increased Low- and High-Frequency Oscillatory Activity in the Prefrontal Cortex of Fibromyalgia Patients.

Authors:  Manyoel Lim; June Sic Kim; Dajung J Kim; Chun Kee Chung
Journal:  Front Hum Neurosci       Date:  2016-03-14       Impact factor: 3.169

6.  Incorporating and Compensating Cerebrospinal Fluid in Surface-Based Forward Models of Magneto- and Electroencephalography.

Authors:  Matti Stenroos; Aapo Nummenmaa
Journal:  PLoS One       Date:  2016-07-29       Impact factor: 3.240

7.  Similarities and differences between on-scalp and conventional in-helmet magnetoencephalography recordings.

Authors:  Lau M Andersen; Robert Oostenveld; Christoph Pfeiffer; Silvia Ruffieux; Veikko Jousmäki; Matti Hämäläinen; Justin F Schneiderman; Daniel Lundqvist
Journal:  PLoS One       Date:  2017-07-24       Impact factor: 3.240

8.  Discrimination of cortical laminae using MEG.

Authors:  Luzia Troebinger; José David López; Antoine Lutti; Sven Bestmann; Gareth Barnes
Journal:  Neuroimage       Date:  2014-07-17       Impact factor: 6.556

9.  Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals.

Authors:  Stephan Lau; Daniel Güllmar; Lars Flemming; David B Grayden; Mark J Cook; Carsten H Wolters; Jens Haueisen
Journal:  Front Neurosci       Date:  2016-04-07       Impact factor: 4.677

10.  Consistency of magnetoencephalographic functional connectivity and network reconstruction using a template versus native MRI for co-registration.

Authors:  Linda Douw; Dagmar Nieboer; Cornelis J Stam; Prejaas Tewarie; Arjan Hillebrand
Journal:  Hum Brain Mapp       Date:  2017-10-08       Impact factor: 5.038

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