The aim of this paper is to understand the functional role of mental representations and intentionality in skilled actions from a systems related perspective. Therefore, we will evaluate the function of representation and then discuss the cognitive architecture of skilled actions in more depth. We are going to describe the building blocks and levels of the action system that enable us to control movements such as striking the tennis ball at the right time, or grasping tools in manual action. Based (...) on this theoretical understanding the measurement of mental representations and related research results concerning mental representation in skilled action are presented in an overview. This leads to the question how mental representations develop and change during learning. Finally, to consolidate the functional understanding of mental representation in skilled action and interaction, we provide examples how to use the measurement of mental representation in humans to inform technical systems. (shrink)

The meshed control theory assumes that cognitive control and automatic processes work together in the natural attention of experts for superior performance. However, the methods adopted by previous studies limit their capacity to provide in-depth information on the neuromotor processes. This experiment tested the theory with an alternative approach. Twelve skilled golfers were recruited to perform a putting task under three conditions: (1) normal condition, with no focus instruction (NC), (2) external focus of attention condition (EC), and (3) internal focus (...) of attention condition (IC). Four blocks of 10 putts each were performed under each condition. The putting success rate and accuracy were measured and electroencephalographies (EEGs) were recorded. The behavioral results showed that the NC produced a higher putting success rate and accuracy than the EC and IC. The EEG data showed that the skilled golfers’ attentional processes in the NC initially resembled those in the EC and then moved toward those in the IC just before putting. This indicates a switch from more automatic processes to cognitive control processes while preparing to putt. The findings offer support for the meshed control theory and indicate the dynamic nature of neuromotor processes for the superior performance of athletes in challenging situations. (shrink)

Learning in intelligent systems is a result of direct or indirect interaction with the environment. Humans can learn by way of different states of (inter-)action such as the execution or the imagery of an action, but their unique potential to induce brain-related as well as mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., execution and imagery in terms of physical and mental practice) and their contribution to the learning (...) of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to the motor action system. These findings provide valuable insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process, and to jointly contribute to developing intelligent cognitive systems and their application in robotics, rehabilitation, or sports. (shrink)