Dynamical analysis of schizophrenia courses

n Iorder to assess the working hypothesis that schizophrenia may be viewed as a nonlinear dynamical disease, we examined the long-term psychoticity clynamics of 14 patients. The data consist of daily ratings of psychopathology observed for 200 or more consecutive days in each patient. We implemented nonlinear dynamical analysis methods with a potential of being applicable even to relatively short and noisy time series: two different forecasting approaches combined with surrogate methods that allow statistical testing in each single case. The resulting classification of dynamics gives evidence that eight patients show nonlinear evolutions of symptom courses. Four cases can be modeled linearly, two as random processes. Thus, a larger proportion of the schizophrenic psychoses we studied shows nonlinear time courses. In this way the validity of the concept of dynamical diseases could be supported on statistical grounds in this important area of psychopathology. The nonlinear view—a low-dimensional nonlinear system generating psychotic symptoms—may provide the foundation for a more parsimonious theory of schizophrenia compared to traditional multicausal models. In several of the nonlinear cases we also observed the qualitative “fingerprint” of deterministic chaos: a decay of deterministic features of the course of disorder with time.