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Autumn School 2008 - Magnetoencephalography
Haueisen, Jens (2008)
clipboard
mla
clipboard		 Haueisen J. "Autumn School 2008 - Magnetoencephalography.", timms video, Universität Tübingen (2008): https://timms.uni-tuebingen.de:443/tp/UT_20081015_003_autumnschool_0001. Accessed 14 Jan 2026.
apa
clipboard		 Haueisen, J. (2008). Autumn School 2008 - Magnetoencephalography. timms video: Universität Tübingen. Retrieved January 14, 2026 from the World Wide Web https://timms.uni-tuebingen.de:443/tp/UT_20081015_003_autumnschool_0001
harvard
clipboard		 Haueisen, J. (2008). Autumn School 2008 - Magnetoencephalography [Online video]. 15 October. Available at: https://timms.uni-tuebingen.de:443/tp/UT_20081015_003_autumnschool_0001 (Accessed: 14 January 2026).
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title: Autumn School 2008 - Magnetoencephalography
alt. title: Forward modeling in MEG data analysis
creator: Haueisen, Jens (author)
subjects: Autumn School 2008, Magnetoencephalography, Neurosciences, MEG data analysis, Forward modeling, Source models, Volume conductor modeling, Boundary Element Method (BEM) models, BEM model discretization, Finite Element Method (FEM) models, Anisotropy, Haueisen, Jens, Universität Tübingen
description: Lecture of Prof. Dr.-Ing. habil. Jens Haueisen
abstract: In order to reconstruct the neuronal activity underlying measured EEG and MEG data both the forward problem (computing the electromagnetic field due to given sources) and the inverse problem (finding the best fitting sources to explain given data) have to be solved. The forward problem involves a source model and a model with the conductivities of the head. Based on the physiological background of the generation of EEG and MEG signals, basic source modeling approaches are introduced. The equivalent electric current dipole model is considered, since this model is the most basic one and widely used in source reconstruction procedures. The conductivity model can be as simple as a homogenously conducting sphere or as a complex as a finite element model consisting of millions of elements, each with a different anisotropic conductivity tensor. The question is addressed how complex the employed forward model should be, and, more specifically, the influence of anisotropic volume conduction is evaluated. For this purpose high resolution finite element models of the rabbit and the human head are employed in combination with individual conductivity tensors to quantify the influence of white matter anisotropy and the solution of the forward and inverse problem in EEG and MEG. Although the current state of the art in the analysis of this influence of brain tissue anisotropy on source reconstruction does not yet allow a final conclusion, the results available indicate that the expected average source localization error due to anisotropic white matter conductivity might be within the principal accuracy limits of current inverse procedures. However, in some percent of the cases a considerably larger localization error might occur. In contrast, dipole orientation and dipole strength estimation are influenced significantly by anisotropy. In conclusion, models taking into account tissue anisotropy information are expected to improve source estimation procedures.
publisher: ZDV Universität Tübingen
contributors: ZDV Universität Tübingen (producer), Research Training Group - SFB 550, University of Tübingen (organizer)
creation date: 2008-10-15
dc type: image
localtype: video
identifier: UT_20081015_003_autumnschool_0001
language: eng
rights: Url: https://timmsstatic.uni-tuebingen.de/jtimms/TimmsDisclaimer.html?639039724195634845