MAR 14, 2019 10:00 AM PDT

Identifying Pattern Transitions of Mind and Brain in Psychotherapy: The Nonlinear Dynamics of Human Change Processes

Presented At Neuroscience 2019
Speakers
  • Paracelsus Medical University: Institute of Synergetics and Psychotherapy Research, Salzburg, Austria
    Biography
      Since 2008, Dr. Schiepek has been a Professor at the Ludwig-Maximilians-University Munich and at the Paracelsus Medical University Salzburg. He serves as the Director of the Institute Synergetics and Psychotherapy Research at the Paracelsus Medical University Salzburg (Austria) and of the Center for Complex Systems (Stuttgart/Germany). He is a visiting Professor at the Donau-University Krems and at the Alpen-Adria University Klagenfurt (Austria), as well as a member of the European Academy of Sciences and Arts (Academia Scientiarium et Artium Europaea), and vice dean of the medical class. Honorary fellow of the German Society of Systemic Therapy and Systemic Research. Fellow of the Mind Force Institute, Sapienza University, Rome. Member of the scientific directory of the German-Japanese Society for Integrative Science. Member of the German Society of Psychology. Professional Highlights: Synergetics and dynamics of nonlinear systems in psychology, management, and the neurosciences. Process-outcome-research in psychotherapy. Neuroscience of psychotherapy. Internet-based Real-Time Monitoring of change processes in different fields. Social psychology. Management. Research in the measurement and development of human competencies. Member of the scientific board of different institutions, communities, and journals. Published 24 books and about 250 papers in international and German scientific journals and readers.

    Abstract:

    An actual way of understanding complex systems in psychology and psychiatry is by building mathematical models on the functioning of mental, behavioral, or neural systems (computational systems psychology). Applied to the field of psychotherapy, a newly developed model integrates available knowledge and empirical findings on the mechanisms of change. It formalizes circular causalities between order and control parameters into a set of nonlinear difference equations and shows how self-organized thresholds create critical instabilities and order-to-order transitions of dynamic patterns. The model explains many features of change dynamics which are known from psychotherapy research, e.g., sudden gains or losses. It can be validated by empirical time series data and allows for short term predictions of critical instabilities and perhaps also of the effects of interventions before these are applied in reality. Here we are at the crossroad of digitalization, personalization and complexity science on the way to intelligent systems in psychological medicine.

    Internet- and app-based methods can be used for a continuous real-time monitoring of human change processes. One of these methods is the Synergetic Navigation System (SNS) which allows for the analysis and visualization of the assessed time series in real-time and by this provides substantial information on the dynamic features of human change processes, like dynamic complexity and critical instability, dynamic synchronization of treatment-related cognitions and emotions, phase-transitions between dynamic patterns and its precursors, and others. Therapists make use of these markers and features for continuous shared decision making together with their patients

    The complex systems approach in psychiatry and psychology tries to integrate different levels of human functioning: the physiological level (e.g., brain dynamics), the mind (cognitions and emotions), behavior, and social interaction. An example will be provided how these levels can be investigated in a multi-level multi-methods project on psychotherapeutic change dynamics. The challenge is to integrate the different time scales of mind-brain dynamics (fMRI scans, immunological end endocrine parameters) and of the personal development during the whole period of psychotherapeutic treatment. The aim is to identify synchronized phase transitions in bio-psycho-social systems.


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