Effect of model resolution and tissue surfaces on forward EEG and MEG simulations

Abstract

Event Abstract Back to Event Effect of model resolution and tissue surfaces on forward EEG and MEG simulations Ceon Ramon1*, Elham Rejvanian2, Mark Holmes2, Paul Schimpf3, Walter J. Freeman4 and Jens Haueisen5 1 University of Washington and Reykjavik University, United States 2 University of Washington, United States 3 Eastern Washington University, United States 4 University of California, United States 5 Technical University Ilmenau, Germany Finite element method (FEM) models of human heads are routinely being used in forward and inverse modeling of the EEG and MEG data. The models are developed from the segmented MR images with a resolution of 1-3 mm. This pixel resolution and the slice thickness influences the forward EEG and MEG computations. Similarly, FEM models of the head could have 5 to 19 different tissue-types identified in them. How the complexity of the model and different tissues influence the forward and inverse EEG and MEG computations? These topics we examined with different FEM head models varying in model resolutions (1-3 mm) and the tissue-types. All major tissue-types were identified, such as, scalp, hard and soft skull bone, gray and white matter, CSF, cerebellum, corpus callosum, dura etc. Models also included anisotropic conductivities of gray and white matter and detailed structures of the eyes, nose and occipital holes. We used single and distributed dipolar sources to simulate forward EEG and MEG patterns. The dipoles were oriented normal to the local cortical surface. The dipole moments were random with a uniform distribution in the range of 0.0 to 0.1 mA-meter. All computations were performed with a uniform-mesh FE solver with the mesh density identical to the MR image resolution. We found that skull bone, CSF and gray and white matter tissue boundaries and also their anisotropies severely influence the forward EEG and MEG modeling. A more complex model with 1.0 mm resolution performed better than the coarser (2-3 mm) model with fewer tissue-types. This was particularly true for modeling the sulcal and gyral structures in the brain which severely influenced the scalp EEGs and MEGs. The average source localization errors were 2-3 mm for complex models as compared to 5-10 mm for coarser models. We also found that an electrode spacing of about 3 mm is needed for extraction of cortical patterns from scalp EEGs in humans. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Oral Presentation Topic: MEG Modeling Citation: Ramon C, Rejvanian E, Holmes M, Schimpf P, Freeman WJ and Haueisen J (2010). Effect of model resolution and tissue surfaces on forward EEG and MEG simulations. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00035 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Mar 2010; Published Online: 19 Mar 2010. * Correspondence: Ceon Ramon, University of Washington and Reykjavik University, Seattle, United States, ceon@uw.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ceon Ramon Elham Rejvanian Mark Holmes Paul Schimpf Walter J Freeman Jens Haueisen Google Ceon Ramon Elham Rejvanian Mark Holmes Paul Schimpf Walter J Freeman Jens Haueisen Google Scholar Ceon Ramon Elham Rejvanian Mark Holmes Paul Schimpf Walter J Freeman Jens Haueisen PubMed Ceon Ramon Elham Rejvanian Mark Holmes Paul Schimpf Walter J Freeman Jens Haueisen Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.