Golenia, L., Schoemaker, M. M., Otten, E., Mouton, L. J., & Bongers, R. M. (2017). What the Dynamic Systems Approach Can Offer for Understanding Development: An Example of Mid-childhood Reaching. Frontiers in psychology, 8, 1774. doi:10.3389/fpsyg.2017.01774

We propose that the DSA (Turvey and Fitzpatrick, 1993; Thelen and Smith, 1994; Lewis, 2011; Spencer et al., 2011; Newell and Liu, 2012; Molenaar et al., 2014; Endedijk et al., 2015) can offer an explanation for the full complexity of the development of reaching during mid-childhood. In contrast with ‘single-cause approaches,’ the DSA takes all components of the system into account. Importantly, the system is not confined to the body, but includes the full action-perception cycle. Automatically, this means that the environment and the task are equally important parts of the system. Thus, the DSA’s starting point is that all components of the person, environment and task are equally important and could potentially contribute to the emerging behavior (cf. Newell, 1986).

According to the DSA, the components of the body-environment-task system are interacting. The result of the interaction at any point in time is the system’s current behavior. Hence, if one or multiple components change, the behavior might change. Thus, developmental trends emerge from changes in interactions that are affected by all components of the system. In contrast with ‘single-cause approaches,’ the DSA does not search for causal factors in development, but aims to reveal processes according to which behavior emerges from various contributing components. It also means that the component(s) involved in the emergence of new behavior may differ at each instant in development.

The concept that DSA uses to explain the emergence of new behavior is that of an attractor. Attractors are preferred, but not fixed, behaviors of the system to which the system returns to when perturbed. Attractors emerge from the interaction of the components at a certain point in time. At a given moment more behavioral attractors are present, hence, the attractor landscape represents the dynamic regime and the stability of the attractors emerging from interactions among task, person and environment components. Changes in the attractor landscape (reflecting disappearing behaviors, appearing behaviors, and qualitatively changing behaviors) are indicated in terms of stability and its counterpart variability. Stability of the attractor specifies resistance to change which is indicated by the effort it takes the system to perform a new or a different behavior. Weak attractor stability can result in an easy transition to a different attractor, which is reflected in increased behavioral variability. For development this means that when components of the system change, the interaction changes, which might influence the stability of the attractors in the attractor landscape. This changed attractor landscape can lead to different behavioral patterns becoming stable resulting in changes at the performance level, affecting development.