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Complex Systems Group

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Complexity research transcends the boundaries between the classical scientific disciplines and is a hot topic in physics, mathematics, biology, economy as well as psychology and the life sciences and is collectively referred to as the Complexity Sciences. Contrary to what the term “complex” might suggest, complexity research is often about finding simple models / explanations that are able to simulate a wide range of qualitatively different behavioural phenomena. “Complex” generally refers to the object of study: Complex systems are composed of many constituent parts that interact with one another across many different temporal and spatial scales to generate behaviour at the level of the system as a whole that can appear to be periodic, nonlinear, unstable or extremely persistent. The focus of many research designs and analyses is to quantify the degree of periodicity, nonlinearity, context sensitivity or resistance to perturbation by exploiting the fact that “everything is interacting” in complex systems.

This requires a mathematical formalism and rules of scientific inference that are very different from the mathematics underlying traditional statistical analyses that assume “everything is NOT interacting” in order to be able to validly infer statistical regularities in a dataset and generalise them to a population. The complex systems approach to behavioural science often overlaps with the idiographical approach of the science of the individual, that is, the goal is not to generalise properties or regularities to universal or statistical laws that hold at the level of infinitely large populations, but to apply general principles and universal laws that govern the adaptive behaviour of all complex systems to study specific facts, about specific systems observed in specific contexts at a specific instant.

Our research concerns:

  1. Perception, action & cognition with a focus on reading (Learning & Plasticity group).
  2. Change processes in psychopathology and intervention (Developmental Psychopathology group).
  3. The development of research methods and data-analysis techniques, e.g. the R-package ‘casnet’

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Selected publications

  • Bosman, A.M.T. (2017). Disorders are reduced normativity emerging from the relationship between organisms and their environment. In K. Hens, D. Cutas, & D. Horstkötter (Eds.), Parental responsibility in the context of neuroscience and genetics (pp. 35–54). Springer International Publishing. https://doi.org/10.1007/978-3-319-42834-5_3
  • Cui, J., Olthof, M., Lichtwarck-Aschoff, A., Li, T., & Hasselman, F. (2021). simlandr: Simulation-Based Landscape Construction for Dynamical Systems. https://doi.org/10.31234/osf.io/pzva3
  • de Boer, N. S., de Bruin, L. C., Geurts, J. J., & Glas, G. (2021). The network theory of psychiatric disorders: a critical assessment of the inclusion of environmental factors. Frontiers in Psychology, 221.
  • Heino, M. T., Knittle, K., Noone, C., Hasselman, F., & Hankonen, N. (2021). Studying behaviour change mechanisms under complexity. Behavioral Sciences, 11(5), 77.
  • Olthof, M., Hasselman, F., Oude Maatman, F., Bosman, A.M.T., & Lichtwarck-Aschoff, A.(in press) Complexity theory of psychopathology, Journal of Psychopathology and Clinical Science. https://doi.org/10.31234/osf.io/f68ej
  • Oude Maatman, F. (2021, July 12). Psychology's Theory Crisis, and Why Formal Modelling Cannot Solve It. https://doi.org/10.31234/osf.io/puqvs
  • Hasselman, F. (2018). casnet: An R toolbox for studying Complex Adaptive Systems and  NETworks. Retrieved from: https://github.com/FredHasselman/casnet
  • Hasselman, F., & Bosman, A. M. (2020). Studying Complex Adaptive Systems with Internal  States: A Recurrence Network Approach to the Analysis of Multivariate Time Series  Data Representing Self-Reports of Human Experience. Frontiers in Applied  Mathematics and Statistics, 6, 9.
  • Lichtwarck-Aschoff, A., Hasselman, F., Cox, R., Pepler, D., & Granic, I. (2012). A characteristic  destabilization profile in parent-child interactions associated with treatment efficacy  for aggressive children. Nonlinear Dynamics-Psychology and Life Sciences, 16, 353.
  • Loretan, N., Radstaak, R. J., & Bosman, A. M. T. (2019). De test getest: Over de  onbruikbaarheid van psychologische testen voor uitspraken over het individu.  Orthopedagogiek: Onderzoek en Praktijk, 58, 115-136.
  • Olthof, M., Hasselman, F., Strunk, G., van Rooij, M., Aas, B., Helmich, M. A., … Lichtwarck- Aschoff, A. (2020). Critical Fluctuations as an Early-Warning Signal for Sudden Gains  and Losses in Patients Receiving Psychotherapy for Mood Disorders. Clinical  Psychological Science, 8, 25–35.
  • Wijnants, M. L. (2014). A review of theoretical perspectives in cognitive science on the  presence of scaling in coordinated physiological and cognitive processes. Journal of  Nonlinear Dynamics.
  • Wijnants, M., Cox, R., Hasselman, F., Bosman, A., & Van Orden, G. (2012). A trade-off study  revealing nested timescales of constraint. Frontiers in physiology, 3, 116.