Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study-Reference-Cited by-同舟云学术

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

Published:2010-05 Issue:1 Volume:51 Page:145-163
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Güllmar Daniel,Haueisen Jens,Reichenbach Jürgen R.

Funder

German Ministry of Science

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference87 articles.

1. Electrical conductivities of the freshly excised cerebral cortex in epilepsy surgery patients; correlation with pathology, seizure duration, and diffusion tensor imaging;Akhtari;Brain Topogr.,2006

2. Spatial transformations of diffusion tensor magnetic resonance images;Alexander;IEEE Trans Med. Imaging,2001

3. Influence of realistic skull and white matter anisotropy on the inverse problem in eeg/meg-source localization;Anwander,2002

4. Computational aspects of finite element modeling in eeg source localization;Awada;IEEE Trans. Biomed. Eng.,1997

5. Effect of conductivity uncertainties and modeling errors on eeg source localization using a 2-d model;Awada;IEEE Trans Biomed. Eng.,1998

Cited by 167 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Accuracy of dipole source reconstruction in the 3-layer BEM model against the 5-layer BEM-FMM model;2024-05-21

2. A hybrid boundary element-finite element approach for solving the EEG forward problem in brain modeling;Frontiers in Systems Neuroscience;2024-05-03

3. A review of algorithms and software for real-time electric field modeling techniques for transcranial magnetic stimulation;Biomedical Engineering Letters;2024-03-29

4. The effects of peeling on finite element method -based EEG source reconstruction;Biomedical Signal Processing and Control;2024-03

5. Comparing the performance of beamformer algorithms in estimating orientations of neural sources;iScience;2024-03