In this article, we have discussed recent progress in quantifying the genetically determined component of the resting EEG. This progress has been made possible in particular by the application of advanced information processing techniques such as “supervised learning,” and the development of a problem-oriented “similarity” concept. Our work aimed at modeling previous findings regarding the distinct individuality of human brain-wave patterns, the high similarity between the EEGs of monozygotic twins, and the average within-pair similarity of dizygotic twins. Thus, we had three objectives: First, we wanted to improve the quantification of EEG characteristics with respect to reproducibility and specificity by means of adaptive procedures and repeated measurements. Second, we wanted to compare the “typical” within-subject EEG similarity with the “typical” within-pair EEG similarity of monozygotic and dizygotic twins brought up together. Finally, we were interested in the degree to which environmental factors affect the characteristics of human brain-wave patterns. Our investigations were based on the empirical data derived from five different populations: (1) 81 healthy subjects, (2) 24 pairs of monozygotic twins brought up together, (3) 25 pairs of dizygotic twins brought up together, (4) 28 pairs of monozygotic twins reared apart, and (5) 21 pairs of dizygotic twins reared apart. Following our similarity conception, repeated measurements on the set of 81 individuals were used as design samples, and new registrations from the same individuals taken 14 days later were referred to as test samples in order to develop the appropriate method and to determine all required calibration parameters. This specific approach allowed us to construct EEG spectral patterns which, with a specificity and reproductibility of>90% each, largely met the requirements of genetic EEG studies. Hence, we were able systematically to investigate the within-pair EEG similarity of our twin samples. Our results provided ample evidence that the individual characteristics of the resting EEG are primarily determined by genetic factors: (1) There exists an almost perfect one-to-one mapping between each individual and his EEG; (2) monozygotic twins proved, with respect to their resting EEGs, to be only slightly less like one another (if there is any difference at all) than each person is to himself over time; (3) the average within-pair EEG similarity estimated from a sufficiently representative sample of dizygotic twins is significantly above the inter-individual EEG similarity between unrelated persons (this finding holds true for both samples of dizygotic twins brought up together and reared apart, and there is also no statistically significant difference in the resting EEG between these two samples) and, (4) the EEGs of monozygotic twins reared apart are obviously as similar to each other as are the EEGs of the same person over time, and there is no statistically significant difference in the resting EEG between the two populations of monozygotic twins brought up together and monozygotic zygotic twins reared apart.