Size and location of activated cortical areas are often identified in relation to their surrounding macro-anatomical landmarks such as gyri and sulci. The sulcal pattern, however, is highly variable. In addition, many cortical areas are not linked to well defined landmarks, which in turn do not have a fixed relationship to functional and cytoarchitectonic boundaries. Therefore, it is difficult to unambiguously attribute localized neuronal activity to the corresponding cortical areas in the living human brain. Here we present new methods that are implemented in a toolbox for the objective anatomical identification of neuromagnetic activity with respect to cortical areas. The toolbox enables the platform independent integration of many types of source analysis obtained from magnetoencephalography (MEG) together with probabilistic cytoarchitectonic maps obtained in postmortem brains. The probability maps provide information about the relative frequency of a given cortical area being located at a given position in the brain. In the new software, the neuromagnetic data are analyzed with respect to cytoarchitectonic maps that have been transformed to the individual subject brain space. A number of measures define the degree of overlap between and distance from the activated areas and the corresponding cytoarchitectonic maps. The implemented algorithms enable the investigator to quantify how much of the reconstructed current density can be attributed to distinct cortical areas. Dynamic correspondence patterns between the millisecond-resolved MEG data and the static cytoarchitectonic maps are obtained. We show examples for auditory and visual activation patterns. However, size and location of the postmortem brain areas as well as the inverse method applied to the neuromagnetic data bias the anatomical classification. Therefore, the adaptation to the respective application and a combination of the objective quantities are discussed.