Registration ends 07.4.2026 at 23:59 h

Experimental psychology tends to approach mind and behavior from a rather static perspective: We ask participants to fill out a questionnaire once and correlate the resulting score to another variable. Similarly, the biological basis of human behavior and psychological experience are often explained by reference to static assignments of specific functional profiles to circumscribed brain areas. In this course, however, we will explore how insights from dynamical systems theory can inform both theorizing and experimental research in psychology. The guiding idea is to use appropriate metaphors and data analysis tools to study how mind and behavior dynamically unfold over time, enabled by flexibly forming and dissolving assemblies of neural, bodily, and environmental structures that change over time and depending on context.

In the first part of the course, we will read and critically discuss theoretical papers that introduce us to dynamical systems theory and how this approach challenges common assumptions in psychology and cognitive neuroscience. The aim of the first part of the course is to reflect on the controversies that motivate a dynamical systems approach to psychology.

In the second part of the course, we will adopt the perspective of an experimental psychologist who has developed some sympathy for dynamical systems thinking and who would like to align her research with this paradigm. One of the key implications is that dynamically inclined experimental psychologists like to use time series analysis methods that can handle data originating from an interdependent dynamical system. Students will form working groups, and each group will be tasked to work through materials covering one data analysis technique (e.g. recurrence or fractal analysis) and to perform a small sample analysis in R. At the end of the term, each group will present their results in class.

This course is targeted at students who are interested in conceptual debates in psychology and their practical implications for empirical research. From a methodological perspective, the course will combine close readings and conceptual discussions with the acquisition of new data analysis skills.

- Students acquire a basic understanding of the conceptual toolkit of dynamical systems theory.
- Students become aware of how abstract theoretical debates are deeply intertwined with choosing a particular data analysis method in experimental psychology.
- Students gain first experiences in using nonlinear data analysis methods.

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