Nonlinear Dynamics, Psychology, and Life Sciences, Vol. 21, Iss. 1, January, 2017, pp. 19-34
@2017 Society for Chaos Theory in Psychology & Life Sciences

 
 
 

How to Modify Psychopathological States? Hypotheses Based on Complex Systems Theory

Hermann Haken, University of Stuttgart, Germany
Wolfgang Tschacher, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland

Abstract: In mathematical analysis based on the assumptions of complexity science, the emergence of a pattern is the result of a competition of modes, which each have a parameter value attached. In the context of visual pattern recognition, a specific connectionist system (the synergetic computer SC) was developed, which was derived from the assumptions of synergetics, a theory of complex systems. We adapted the processes of visual pattern recognition performed by the SC to a different context, psychopathology and therapeutic interventions, assuming these scenarios are analogous. The problem then becomes, under which conditions will a previously established psychopathological pattern not be restituted? We discuss several cases by using the equations of the SC. Translated to the psychopathological context, we interpret the mathematical findings and proofs in such a way that successful corrective interventions, e.g. by psychotherapy, should focus on one alternative pattern only. This alternative cognition-behavior-experience pattern is to be constructed individually by a therapist and a patient in the therapeutic alliance. The alternative pattern must be provided with higher valence (i.e. affective and motivational intensity) than possessed by the psychopathological pattern. Our findings do not support a linear symptom-oriented therapy approach based on specific intervention techniques, but rather a holistic approach. This is consistent with empirical results of psychotherapy research, especially the theory of common factors.

Keywords: psychotherapy, psychopathological disorder, synergetics, self-organization, affordance, common factors