Visual Analysis of Cognitive Structure based on the Human-Machine Interaction

ABSTRACT

Learning is a process that changes the cognitive structure, which is the important representation of advanced cognition. Due to the difficulties in observing cognition, the empirical and visual researches of cognitive structure are significant. To realize the empirical research, the first issue is how to observe the cognitive structures. Based on the humanmachine interaction, we have established a new "Brain cognitive body - cognitive coupling Situations - information Manifolds" (BSM) cognition observation platform. This platform allows the users to observe the cognitive processes and structures, collect and re-structure the cognitive activity information. Additionally, the cognitive structure imaging, the empirical and visual analysis and the dimension reduction for high-dimensional cognitive manifolds can be realized on this BSM platform. Here, we have selected the tree-based network to represent the low-dimensional cognitive manifolds to develop a visual and vectorial model of layered cognitive structure. The digital model of cognitive structure is able to provide the basis for studying the empirical research, mathematics and dynamics of the cognitive structure, and the new ways for the advanced cognitive research.

Keywords:

Cognitive structure, complete network, human-machine interaction, topological manifold, visual analysis.