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Forward tools to enhance creative performance based on neurobiological foundations and implications: bridging divergent and convergent thinking

Published online by Cambridge University Press:  27 August 2025

Björn R. Kokoschko*
Affiliation:
Otto-von-Guericke-Universität Magdeburg, Germany Hochschule Anhalt, Germany
Michael K. Schabacker
Affiliation:
Otto-von-Guericke-Universität Magdeburg, Germany
Martin T. Wiesner
Affiliation:
Hochschule Anhalt, Germany

Abstract:

One focus of creativity research is the question of how creative potential can be effectively unleashed in relation to certain cognitive styles such as convergent and divergent thinking. Neurobiological findings show that different brain structures need to be activated in order to specifically stimulate these cognitive styles. By integrating tools that help understand and optimize the neurochemistry of creativity into the design process, we enable a comprehensive application of creativity and improve the ability to develop innovative solutions. In this contribution, we therefore examine which neurobiological structures undaerlay creativity and how they can be activated in a natural way. We present practical tools for fostering creativity from litertaur, make the scientific mechanisms underlying creativity accessible to designers and propose an approach for implementing the tools.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2025
Figure 0

Table 1. Overview of the neural networks involved

Figure 1

Table 2. Overview of the tools