Host Institution: Ruhr-University Bochum
Department that hosts the PhD: Institute for Neural Computation
Contact: Prof. dr. Schöner (use this email contact only to request additional information, do NOT use this email for applications)
The goal of this theoretical project is to provide a conceptual framework, supported and made concrete by a mathematical model, to interpret findings on the development of selection decisions in action directed at objects in young children. In past work that was based on close theory-experiment interaction, we have shown that motor decisions in infancy and early childhood are influenced in a graded way by a variety of factors that include the perceptual structure of the environment, the recent history of action decisions, and perceived outcomes of a motor action. In particular, we found that the metrics of the movement choices matters (rather than merely the number or probability of choices). The spatial precision hypothesis accounts for a link between such metric effects and the variance across trials of performance. Over development, the neural representations on which movements are based are postulated to become more stable, less variable, more resistant to distractors, and thus showing a narrower range of non-unique selection decisions. The theoretical challenge this project will address is how the postulated developmental trajectory may be driven by learning processes. Such an account must, importantly, explain why the early stage of the developmental system, is broadly tuned to response metrics and has limited stability. Such an explanation must provide arguments for the functional advantage of that early developmental stage. Our hypothesis is, that the lack of precise motor control, observed through variance in motor performance, consistent with the early form of selection decision making that integrates and averages broadly. Using the concepts of the theoretical work, we will help design, analyze, and interpret experiments on the development of action decision making in collaboration with PhD project 10.
Dineva, E., & Schöner, G. (2018). How infants’ reaches reveal principles of sensorimotor decision making. Connection Science, 30(1), 53–80. https://doi.org/10.1080/09540091.2017.1405382
Schöner, G., & Dineva, E. (2007). Dynamic instabilities as mechanisms for emergence. Developmental Science, 10(1), 69–74.
Schöner, G. (2014). Dynamical Systems Thinking: From Metaphor to Neural Theory. In P. C. M. Molenaar, R. M. Lerner, & K. M. Newell (Eds.), Handbook of Developmental Systems Theory and Methodology (pp. 188–219). New York, New York, USA: Guilford Publications.
Specific required skills of PhD student
|Programming||Basic skills, capacity to learn Matlab or Python|
|Background||Training in mathematics, physics, engineering, or computer science would be helpful.|
|Project specific knowledge||Differential equations, numerics|
|Primary focus project||Mathematical modeling in close alignment with experimental data and based on good conceptual understanding|
|Methods||Dynamical systems, neural networks, neural dynamics, numerical simulation|