The EEG and MEG, Using a Model of Eccentric Spheres to Describe the Head

Meijs, J. W. H.; Peters, M.J.

doi:10.1109/tbme.1987.325929

Cited by 55 publications

(15 citation statements)

References 11 publications

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“…For these applications, simplified spherical shell (Brazier, 1949; Geisler and Gerstein, 1961; Frank, 1952; Wilson and Bayley, 1950; Hosek et al, 1978; Meijs and Peters, 1987) models can be used and solved with analytical methods, but they neglect the complex anatomy of the head and the brain. Numerous studies have demonstrated that realistic modeling of anatomical structures such as the skull (Dannhauer et al, 2011; Ramon et al, 2004; Chauveau et al, 2004; Lanfer et al, 2012a; Anwander et al, 2002; Ary et al, 1981; Cuffin, 1993; van den Broek et al, 1998; Vorwerk et al, 2014), the dura (Slutzky et al, 2010; Ramon et al, 2014; Ramon, 2012), the cerebrospinal fluid (CSF) (Ramon et al, 2006; Haueisen et al, 1997; Slutzky et al, 2010; Ramon et al, 2004; van den Broek et al, 1998; Vorwerk et al, 2014; Bangera et al, 2010; Bénar and Gotman, 2002; Lanfer et al, 2012b; Rice et al, 2013; Vanrumste et al, 2000; Wendel et al, 2008) and head extent (Lanfer et al, 2012a; Bruno et al, 2003; Vatta et al, 2005) as well as realistic modeling of anisotropy (Chauveau et al, 2004; Anwander et al, 2002; Vorwerk et al, 2014; Bangera et al, 2010; Haueisen et al, 2002; Güllmar et al, 2010; Wolters et al, 2006; Hallez et al, 2005, 2008, 2009; Rullmann et al, 2009; Wolters, 2003), particularly of the white matter, can substantially improve the accuracy of forward and inverse modeling of EEG signals.…”

Section: Introductionmentioning

confidence: 99%

The role of blood vessels in high-resolution volume conductor head modeling of EEG

et al. 2016

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Reconstruction of the electrical sources of human EEG activity at high spatiotemporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebrospinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7 T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17 × 106 nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15 mm. Large errors (>2 cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura — structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

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Section: Introductionmentioning

confidence: 99%

The role of blood vessels in high-resolution volume conductor head modeling of EEG

et al. 2016

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“…The computation of the flux through the coil is carried out numerically by approximating the surface integral over each coil by a seven-point Gaussian integration formula (ABRAMOWn'Z and S~GUN, 1972 et al, 1985). The radii and centres of the eccentric spheres are deduced from the realistically shaped head model by optimally fitting a sphere to each compartment boundary in terms of a leastsquares fitting procedure (MEIJS and PETERS, 1987).…”

Section: Methodsmentioning

confidence: 99%

Relative influence of model assumptions and measurement procedures in the analysis of the MEG

Meijs

Peters

Boom

et al. 1988

Med. Biol. Eng. Comput.

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“…This locally optimal dipole moment d is given by: Inserting [4] into [3] makes the cost function K independent of the dipole moment parameters d: [5] Here I m is the m × m identity matrix. The solution of the inverse problem is taken to be the location ŕ, where K has its minimum, together with the locally optimal dipole at r '.…”

Section: Source Localization Algorithmsmentioning

confidence: 99%

Accuracy of Two Dipolar Inverse Algorithms Applying Reciprocity for Forward Calculation

Laarne

Hyttinen

Dodel

et al. 2000

Computers and Biomedical Research

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The EEG and MEG, Using a Model of Eccentric Spheres to Describe the Head

Cited by 55 publications

References 11 publications

The role of blood vessels in high-resolution volume conductor head modeling of EEG

The role of blood vessels in high-resolution volume conductor head modeling of EEG

Relative influence of model assumptions and measurement procedures in the analysis of the MEG

Accuracy of Two Dipolar Inverse Algorithms Applying Reciprocity for Forward Calculation

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