To investigate the influence of anisotropic electrical conductivity in white matter on the forward and inverse solution in electroencephalography (EEG) and magnetoencephalography (MEG) numerical simulation studies were performed. A high-resolution (1 mm3 isotropic) finite element model of a human head was implemented to study the sensitivity of EEG and MEG source localization. In vivo information on the anisotropy was obtained from magnetic resonance diffusion tensor imaging and included into the model, whereas both a direct transformation and a direct transformation with volume normalization were used to obtain conductivity tensors. Additionally, fixed artificial anisotropy ratios were also used, while considering only the orientation information from DTI, to generate conductivity tensors. Analysis was performed using over 25,000 single dipolar sources covering the full neocortex. Major findings of the study include that EEG is more sensitive to anisotropic conductivities in white matter compared to MEG. Especially with the inverse analysis, we found that sources placed deep in sulci are located more laterally if anisotropic conductivity of white matter tissue is neglected. Overall, the single-source localization errors resulting from a neglect of anisotropy were found to be smaller compared to errors associated with other modeling errors, like misclassified tissue or the use of nonrealistic head models. In contrast to the small localization error we observed significant changes in magnitude and orientation. The latter is important since dipole orientation might be more important than absolute dipole localization in assigning, e.g., epileptic activity to the wall of the affected brain sulcal area. If high-resolution finite element models are used to perform source localization in EEG and MEG experiments and the quality of the measured data permits localization accuracy of 1 mm and below, the influence of anisotropic compartments has to be taken into account.