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This paper reviews the class of instantaneous, 3D, discrete, linear solutions for the EEG inverse problem. Five different inverse methods are analyzed and compared: minimum norm, weighted minimum norm, Backus and Gilbert, weighted resolution optimization (WROP), and low resolution brain electromagnetic tomography (LORETA). The inverse methods are compared by testing localization errors in the estimation of single and multiple sources. These tests constitute the minimum necessary condition to be satisfied by any tomography. Of the five inverse solutions tested, only LORETA demonstrates the ability of correct localization in 3D space. The other four inverse solutions should not be used if the research aim is to localize the neuronal generators of EEG in a 3D brain. In this sense, minimum norm, weighted minimum norm, Backus and Gilbert, and WROP can be likened to x-rays, where depth information is totally lacking. For the sake of reproducible research, all the material and methods used in this part of the study, consisting of computer programs (source code and executables) and data, are available upon request to the author. In this way, all the results and conclusions can be checked, reproduced, and validated by the interested reader.