Phantasy therapy in psychiatry: rediscovering reality in phantasy. A special treatment for in- and outpatients in general psychiatry.

Phantasy Therapy is an interdisciplinary depth-psychologically oriented group therapy form with focus on the treatment of psychoses in acute and remission phases. A different theme is presented to the patients every week on two consecutive days (90 min per session), coherently, via various sensory channels. On the first day, the theme is concretely and operationally introduced by means of an object, transformed into movement in the broadest sense of the word, and experienced directly with the body. The first session ends with a story, usually a fairy tale or parable, so that the body experiences can be further realized symbolically at the cognitive-emotional level. The second session treats the same theme via repetition of the chosen story with the deeper transformation of symbols into color and form. The first day is jointly led by a psychotherapist and a movement/ dance therapist, the second day by a psychotherapist and an art therapist. Our approach understands therapy as a somatesthetic experience- and synthetic expression-oriented encounter with the patient via the therapist's empathic imaginative identification with the patient by means of a progressively orchestrated, positivizing, cognitive-emotional, theme-centered rapport. In this connection six therapeutic elements are of importance: theme, object, movement, fairy tale, artwork, symbol. Phantasy Therapy offers the patient creative freedom in a humorous and playful way within a certain therapeutic security (Amae principle) and contradicts several classical prejudices concerning the treatment of psychotic patients.

Intraindividual specificity and stability of human EEG: comparing a linear vs a nonlinear approach.

We have applied the so-called "unfolding dimension approach" to reanalyze an earlier longitudinal EEG study. Both linear and nonlinear approaches show that the EEG comprises a static, person-specific part upon which nonstatic and state-specific parts are superimposed. The intraindividual specificity and stability of the genetic part are similar between methods. This is assessed by comparing the outcome of a person to his own outcomes at later times (14 days and 5 years later). The nonlinear method revealed a median correlation coefficient rho = 0.55, whereas advanced linear methods showed a median rho = 0.84. An apparent effect for the 5-year interval was detected with the nonlinear method and is discussed in terms of the different assumptions of the two approaches concerning EEG signal generation.

Reliable computer-assisted classification of the EEG: EEG variants in index cases and their first degree relatives.

A method which optimizes on global properties of sample recordings is proposed for the definition of and the discrimination between electroencephalogram (EEG) classes. The sample was drawn from students at the University of Heidelberg from 1974 to 1978 and consists of 15 healthy index cases clinically ascertained as belonging to the low voltage EEG group. In addition, the three clinically defined groups: diffuse beta (18 index cases), borderline alpha (12 index cases) and monomorphous alpha (18 index cases) have been included in the study, as well as the first degree relatives of the index cases, thus providing a clinical classification into four groups. The proposed method provides an automatic and reliable classification algorithm using discriminant and cluster analysis. The relation between such an automatized classification and clinical classification schemes is investigated. In particular, the inheritance of the low voltage EEG, the question on sex differences and the question of a simple Mendelian mechanism had been examined. The method of random splittings had been applied for discriminant and cluster analysis. Our findings can be summarized as follows: (1) except for the monomorphous alpha EEG group, the clinical classification shows rather marginal separation (discriminating performance 60% to 75%), while a new and more reliable grouping scheme improves the discriminating performance up to 87% to 91%. The latter scheme leads to the concept of personal channel pattern (PCP) and was compared to the clinical classification scheme by means of contingency tables; (2) only a weak correlation between the clinically and PCP-based groups could be found (Cramér Index: 0.27). Accordingly, we continued to investigate the extent to which the proposed EEG classification scheme can nevertheless explain the genetic mechanisms apparently involved in the low voltage EEG. We thus considered the role of sex differences manifest in our proposed new grouping scheme; (3) males occurred more frequently in the new group 3 and females more frequently in the new group 1. In this regard, a much better correlation of the new groups between mothers and children than between fathers and children was observed; and (4) with help of our new PCP scheme, we have been able to reproduce a simple two gene Mendelian scheme to explain inheritance of the clinical low voltage EEG group. In this PCP-based scheme, the low voltage property does not occur when dominance of a certain gene (called gene A) is absent.

Towards an understanding of sensory soft signs of schizophrenia.

Neurological soft signs are considered to be non-localizing findings and clinical neurodysfunctional correlates of schizophrenia. Sensory signs in 21 chronic schizophrenic patients were compared with those of healthy subjects. The schizophrenic patients differed significantly from the controls in graphesthesia testing; there was no clear-cut impairment of other somatic sensory modalities. The graphesthesia learning effect was weaker in the patient group. No unequivocal correlation could be found between psychopathology or course variables and dysgraphesthesia. The authors hypothesize that an impairment in graphesthesia testing may reflect a working memory deficit in schizophrenics.

Chaos theory and schizophrenia: elementary aspects.

Elementary aspects of the usefulness and impact of chaos theory to an understanding of schizophrenia are discussed. In addressing the question 'Is there chaos in schizophrenia?', attention is limited to schizophrenic psychosis. A differentiated view of chaos as metaphor, analogy and mathematical/physical concept is presented with emphasis upon how the latter may apply to empirical knowledge of schizophrenic psychosis. The typical behavior of both psychotic schizophrenic patients and general chaotic systems, and the dynamical analysis of time-series data extracted from such systems, are reviewed. A general hypothesis connecting chaos and schizophrenia is introduced and analyzed. Arguments are provided in favor of the hypothesis at sociological, psychological, and biological scales of manifestation. This makes possible a model-independent 'chaos theory approach' to schizophrenia and the criteria necessary to test it. Some consequences of this approach are briefly considered. The original question is rephrased with the technical language of chaos theory: 'Are chaotic attractors diagnostic markers for schizophrenia?' or 'Is schizophrenia a dynamical disease?'. A few implications of viewing schizophrenia as a dynamical disease are discussed.

Long-term prognosis of schizophrenia.

The question of determining prognostically relevant features for schizophrenia was approached with multivariate statistical methods applied to the data from the Bonn longitudinal study of 502 schizophrenic patients. In this study, personal interviews according to a clinical classification scheme allowed every patient to be ranked within each of three different outcome classes: psychopathological remission, occupational remission, and course type. Our multivariate analysis encompassed a total of 50 items pertinent to the time up to and including the first 6 months after the first psychotic manifestation. Despite the introduction of mathematical methods considerably more sophisticated than those employed in earlier studies, no satisfactory solution could be found to the problem of predicting end states of schizophrenia. Reliable predictions could be made only for 'extreme' end states (i.e. full remission versus (1) characteristic residues in the narrower sense; (2) total unemployment, or (3) surging or simple courses to mixed residues or to typical schizophrenic defect psychoses). Accordingly, sufficiently reliable assertions applied only to a minority of about 1/3 of patients, whereas for the majority of 2/3, no generalizable prognostication was possible (67-71% true-positive predictions on 36-63% of total population in extreme states). By contrast, our analyses have clearly uncovered a fundamental problem of investigations into the long-term prognosis of schizophrenia: the extreme dependence of results on the clinical definition of end states. The further the phenomenon 'end state' is qualitatively subdivided, the poorer and less reproducible is the mutual discrimination between intermediate states and the less reliable are allocations of patients to these intermediate states by means of multivariate classifiers. Furthermore, our analyses have also demonstrated the usefulness of multivariate, adaptive procedures for investigations into the structural properties of long-term courses, so that predictions might be considerably improved if more reliable definitions of schizophrenic end states are available.