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This study examined the relationship between speech characteristics and psychopathology throughout the course of affective disturbances. Our sample comprised 20 depressive, hospitalized patients who had been selected according to the following criteria: (1) first admission; (2) long-term patient; (3) early entry into study; (4) late entry into study; (5) low scorer; (6) high scorer, and (7) distinct retarded-depressive symptomatology. Since our principal goal was to model the course of affective disturbances in terms of speech parameters, a total of 6 repeated measurements had been carried out over a 2-week period, including 3 different psychopathological instruments and speech recordings from automatic speech as well as from reading out loud. It turned out that neither applicability nor efficiency of single-parameter models depend in any way on the given, clinically defined subgroups. On the other hand, however, no significant differences between the clinically defined subgroups showed up with regard to basic speech parameters, except for the fact that low scorers seemed to take their time when producing utterances (this in contrast to all other patients who, on the average, had a considerably shorter recording time). As to the relationship between psychopathology and speech parameters over time, we found significant correlations: (1) in 60% of cases between the apathic syndrome and energy/dynamics; (2) in 50% of cases between the retarded-depressive syndrome and energy/dynamics; (3) in 45% of cases between the apathic syndrome and mean vocal pitch, and (4) in 71 % of low scores between the somatic-depressive syndrome and time duration of pauses. All in all, single parameter models turned out to cover only specific aspects of the individual courses of affective disturbances, thus speaking against a simple approach which applies in general.

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 reproducibility of greater than 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.(ABSTRACT TRUNCATED AT 400 WORDS)

Within the broader context of our investigations into the heredity of the human EEG, we analysed the EEGs of 28 pairs of monozygotic and 21 pairs of dizygotic twins who were separated as infants and reared apart. The principal goal of this study was to determine the degree to which environmental factors possibly influence the development of a person's EEG. Monozygotic twins reared apart were, with respect to their EEGs, only slightly less similar to each other (if there is any difference at all) than the same person is to himself over time. For dizygotic twins reared apart, we verified the findings of our previous study, namely, that the average within-pair similarity of EEGs estimated from a sufficiently representative sample of fraternal twins was significantly higher than the average inter-individual similarity of EEGs obtained from unrelated persons. The results on both monozygotic and dizygotic twins, yielded conclusive proof that the individual EEG pattern is predominantly determined by hereditary factors.