Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study

Güllmar, Daniel; Haueisen, Jens; Reichenbach, Jürgen R.

doi:10.1016/j.neuroimage.2010.02.014

Cited by 195 publications

(187 citation statements)

References 79 publications

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“…Our results show strong errors in the leadfield nearby large white matter tracts. Deviation between leadfields in all directions were more pronounced in sulci than gyri, reaffirming previously reported results [6]. Anisotropic conductivity information should not be ignored in neural source imaging studies.…”

Section: Discussionsupporting

confidence: 91%

“…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]. The dipole shift for these sources tended to be parallel to the principal direction of the nearby white matter.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, our FE mesh is of higher quality than many previous studies, as we use an unstructured tetrahedral mesh, rather than structured hexahedral grids (used in e.g. [27,6]). This allows us to refine the mesh for more realistic calculations within highly curved regions of the brain.…”

Section: Discussionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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We present a finite element modeling (FEM) implementation for solving the forward problem in electroencephalography (EEG). The solution is based on Helmholtz's principle of reciprocity which allows for dramatically reduced computational time when constructing the leadfield matrix. The approach was validated using a 4-shell spherical model and shown to perform comparably with two current state-of-the-art alternatives (OpenMEEG for boundary element modeling and SimBio for finite element modeling).We applied the method to real human brain MRI data and created a model with five tissue types: white matter, grey matter, cerebrospinal fluid, skull, and scalp. By calculating conductivity tensors from diffusion-weighted MR images, we also demonstrate one of the main benefits of FEM: the ability to include anisotropic conductivities within the head model. Root-mean square deviation between the standard leadfield and the leadfield including white-matter anisotropy showed that ignoring the directional conductivity of white matter fiber tracts leads to orientation-specific errors in the forward model. Realistic head models are necessary for precise source localization in individuals. Our approach is fast, accurate, open-source and freely available online.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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“…For example, for fMRI it is still not clear if the signal reflects pre-or postsynaptic activity (Logothetis, 2008), or excitatory or inhibitory synaptic activity (Lauritzen and Gold, 2003). For EEG forward models, the anisotropy of the conductivities may matter (Güllmar et al, 2010), and linking local field potentials to the spiking/synaptic activity is also a current research topic (Rasch et al, 2009). For example, we have recently combined NMMs and anisotropic head-models in order to simulate EEG activity (Zimmermann et al, 2011) as an attempt for a multi-scale forward model.…”

mentioning

confidence: 99%

Towards Model-Based Brain Imaging with Multi-Scale Modeling

Schwabe¹,

Zheng²

2012

Neuroimaging - Methods

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Electric field calculations in brain stimulation based on finite elements: An optimized processing pipeline for the generation and usage of accurate individual head models

Windhoff¹,

Opitz²,

Thielscher³

2011

Human Brain Mapping

400

371

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The need for realistic electric field calculations in human noninvasive brain stimulation is undisputed to more accurately determine the affected brain areas. However, using numerical techniques such as the finite element method (FEM) is methodologically complex, starting with the creation of accurate head models to the integration of the models in the numerical calculations. These problems substantially limit a more widespread application of numerical methods in brain stimulation up to now. We introduce an optimized processing pipeline allowing for the automatic generation of individualized high-quality head models from magnetic resonance images and their usage in subsequent field calculations based on the FEM. The pipeline starts by extracting the borders between skin, skull, cerebrospinal fluid, gray and white matter. The quality of the resulting surfaces is subsequently improved, allowing for the creation of tetrahedral volume head meshes that can finally be used in the numerical calculations. The pipeline integrates and extends established (and mainly free) software for neuroimaging, computer graphics, and FEM calculations into one easy-to-use solution. We demonstrate the successful usage of the pipeline in six subjects, including field calculations for transcranial magnetic stimulation and transcranial direct current stimulation. The quality of the head volume meshes is validated both in terms of capturing the underlying anatomy and of the well-shapedness of the mesh elements. The latter is crucial to guarantee the numerical robustness of the FEM calculations. The pipeline will be released as open-source, allowing for the first time to perform realistic field calculations at an acceptable methodological complexity and moderate costs.

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Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study

Cited by 195 publications

References 79 publications

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

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

Towards Model-Based Brain Imaging with Multi-Scale Modeling

Electric field calculations in brain stimulation based on finite elements: An optimized processing pipeline for the generation and usage of accurate individual head models

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