Effects of local variations in skull and scalp thickness on EEG's and MEG's

Abstract

Many studies have been performed on the effects of various features of head geometry on electroencephalograms (EEG's) and magnetoencephalograms (MEG's) and on the accuracy with which electrical sources in the brain can be localized using these measurements. However, to date no studies have been performed of the effects of local variations in skull and scalp thickness. This paper presents a computer modeling study of the effects of such local variations. The results obtained in this study indicate that local variations in skull and scalp thickness have effects on EEG's and MEG's which range from a simple intuitive effect to complex effects which depend on such factors as source depth and orientation, the geometry of the variation in skull and scalp thickness, etc. These results also indicate that local variations in skull and scalp thickness cause EEG localization errors which are generally much less than 1 cm and MEG localization errors which are even smaller. These results also indicate that multichannel and single-channel MEG measurements will produce localization errors of approximately the same amplitude when there is a bump on the external surface of the head but that multichannel measurements will produce significantly smaller localization errors than single-channel measurements when a depression is present in that surface.

Modeling Skull Electrical Properties

“…Total errors in conductivities measured relative to a standard shape or solution (orthogonal measurements) were calculated using the formula (6) where K is the cell constant, δσ std is related to errors in conductivity standard value, δσ sig represents uncertainty in measured impedances and δσ model represents errors between the sample geometry and that assumed by a model. In the case of radial measurements the cell constant was the result of two different measurements (for cell area A and sample thickness t), rather than from a measurement referred to a conductivity standard or model, in which case the error was estimated as (7) 3.…”

Applying Craniofacial Metrics to Adapt 3D Generic Head Models

“…Although the resolution of the spherical and elliptical models is of a few centimeters (Crouzeix et al, 1999;Roth et al, 1993), they explain the general theory. Investigations that continued this pursuit of a general understanding of the neuroelectric phenomena involved often tailor spherical models to address specific issues such as local variations (Cuffin, 1993), noise (Ryynänen et al, 2006), conductivity values (Ryynänen et al, 2006), electrode properties in 2-D and 3-D (Ollikainen et al, 2000;Suesserman et al, 1991), source localization (Vanrumste et al, 2001), and spatial resolution (Malmivuo & Suihko, 2004;Malmivuo et al, 1997).…”

Compensation of domain modelling errors in the inverse source problem of the Poisson equation: Application in electroencephalographic imaging

“…In EEG source problem, neural sources are reconstructed inside the brain based on electric potential measurements around the scalp, and it is well known that the inverse solution depends strongly on the accuracy of discretized head geometry [2,4,7,8,16,39,49,54] and the accuracy of electric conductivity modelling of different tissues [3,47,25,48,34,50,51]. The head features can be extracted, to some extent, by using multi-modal imaging (computed tomography / diffusion magnetic resonance imaging), for example.…”