Motor decision making



When we perform goal-directed movements, we have to plan and perform these movements in the presence of uncertain and dynamic environmental conditions. To account for that, movements seem to be coordinated to allow flexibility in movement execution by simultaneously granting stability in the movement outcome. This is acheived by a continuous specification of selected as well potential movements during movement planning and execution, influenced by changes in the immediate environment – a process referred to as "embodied decision making".   

In this line of research, we are investigating how age-related changes in cognitive and motor functioning affect the above mentioned "flexibility-stability trade-off"  in movement coordination. 


Motion tracking systems (e.g. Qualisys, Optotrak, Zebris) to record the execution of goal-directed pointing and reaching movements. 

 □ Analysis of the amount and structure of movement variability (e.g. PCA, canonical correlation, uncontrolled manifold) to gain insight into underlying movement coordination patterns
 □ To elucidate neurophyisiological correlates of the motor behaviour non-invasive methods (e.g. EEG, TMS) are applied in cooperation with other project partners

 □ Tests of basic and higher cognitive functions to identify the relation of cognitive functioning to performance in simple and complex motor decision tasks


“Trust your training: Improving movement stability in older people by manipulating cognitive uncertainty (during motor decision making) through cortical stimulation, cognitive or motor learning”
2015 – 2017

Technical University of Munich:
 “The influence of movement planning on movement variability in reaching movements: a TMS study”
 2014 – 2015


Krüger, M., & Hermsdörfer, J. (2019). Target uncertainty during motor decision-making: The time course of movement variability reveals the effect of different sources of uncertainty on the control of reaching movements. Frontiers in Psychology, 10:41. 

Krüger, M., Straube, A., & Eggert, T. (2017). The Propagation Of Movement Variability In Time: A Methodological Approach For Discrete Movements With Multiple Degrees Of Freedom. Frontiers in Computational Neuroscience, 11:39.