Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling

Abstract

To achieve a deeper understanding of the brain, scientists, and clinicians use electroencephalography (EEG) and magnetoencephalography (MEG) inverse methods to reconstruct sources in the cortical sheet of the human brain. The influence of structural and electrical anisotropy in both the skull and the white matter on the EEG and MEG source reconstruction is not well understood.In this paper, we report on a study of the sensitivity to tissue anisotropy of the EEG/MEG forward problem for deep and superficial neocortical sources with differing orientation components in an anatomically accurate model of the human head.The goal of the study was to gain insight into the effect of anisotropy of skull and white matter conductivity through the visualization of field distributions, isopotential surfaces, and return current flow and through statistical error measures. One implicit premise of the study is that factors that affect the accuracy of the forward solution will have at least as strong an influence over solutions to the associated inverse problem.Major findings of the study include (1) anisotropic white matter conductivity causes return currents to flow in directions parallel to the white matter fiber tracts; (2) skull anisotropy has a smearing effect on the forward potential computation; and (3) the deeper a source lies and the more it is surrounded by anisotropic tissue, the larger the influence of this anisotropy on the resulting electric and magnetic fields. Therefore, for the EEG, the presence of tissue anisotropy both for the skull and white matter compartment substantially compromises the forward potential computation and as a consequence, the inverse source reconstruction. In contrast, for the MEG, only the anisotropy of the white matter compartment has a significant effect. Finally, return currents with high amplitudes were found in the highly conducting cerebrospinal fluid compartment, underscoring the need for accurate modeling of this space. D

A finite-element reciprocity solution for EEG forward modeling with realistic individual head models

“…following transcranial direct current stimulation) along trajectories parallel to the primary direction of the fiber tracts [4,27]. Sources located deep in the brain, as well as those bordering strongly anisotropic tissue, are misrepresented in EEG localization when neglecting the effects of white matter anisotropy [4].…”

“…following transcranial direct current stimulation) along trajectories parallel to the primary direction of the fiber tracts [4,27]. Sources located deep in the brain, as well as those bordering strongly anisotropic tissue, are misrepresented in EEG localization when neglecting the effects of white matter anisotropy [4]. One recent study that included an inverse analysis found that sulcal sources localized in EEG studies may be mislocalized outside of the sulci if white matter anisotropy is neglected [6].…”

“…In this paper we focus on the forward problem, which has not been given a great deal of attention in neuroimaging. Despite many published studies demonstrating high-quality head models and forward modeling approaches [2,3,4,5,6,7,8], most functional neuroimaging studies still rely on relatively poor quality electromagnetic head models when performing source localization.…”

The surface Laplacian technique in EEG: Theory and methods

“…Furthermore, when the media is anisotropic, E (r) is not necessarily in the same direction as j (r), and ρ needs to be a rank-two tensor. However, at the scalp, equation (8) is an excellent approximation to EEG, as the ρ is approximately isotropic in the tangential direction (Rush and Driscoll, 1968;Wolters et al, 2006;Petrov, 2012). meaning comes from Gauss's Law, which in its differential form given by Maxwell is written as…”

Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization

“…The construction of a realistic head conductivity model requires accurate segmentation of magnetic resonance (MR) images of the head into tissue classes corresponding to different conductivity values. It is common practice to use five tissue classes-white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), skull, and skin [4,5] followed by manual correction for source localization, although improvements in localization accuracy can be achieved with more classes [6]. Completely manual segmentation [7], typically performed by a clinical expert, is the gold standard.…”