Network oscillations imply the highest cognitive workload and lowest cognitive control during idea generation in open-ended creation tasks

Jia, Wenjun; von Wegner, Frederic; Zhao, Mengting; Zeng, Yong · 2021 · Crossref

DOI: 10.1038/s41598-021-03577-1

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Summary

This study investigates the neural dynamics underlying open-ended design creation, specifically aiming to quantify cognitive workload and control during distinct phases of the design process. Design is a complex, recursive behavior involving problem understanding, idea generation, evaluation, and evolution. While previous neuroimaging studies have linked specific cognitive functions to isolated brain regions, the temporal interaction of large-scale brain networks during the continuous flow of design thinking remains poorly understood. Strictly controlled experiments often fail to capture the non-repetitive, free-flowing nature of creativity. To address this, the authors simulated design creation in a loosely controlled setting, allowing participants self-paced freedom to explore solutions, thereby better modeling real-world design recursivity. The experiment involved 27 graduate engineering students who completed six design tasks (e.g., designing a birthday cake, recycle bin, or wheelchair). Each task consisted of five self-paced activities: problem understanding, idea generation, rating idea generation, idea evaluation, and rating idea evaluation. Electroencephalography (EEG) data were recorded at 500 Hz and pre-processed to remove artifacts. The researchers employed two primary analytical methods: Task-Related Power (TRP) analysis to assess oscillatory power changes in delta, theta, alpha, and beta frequency bands relative to a resting baseline; and EEG microstate analysis to segment unstructured signals into quasi-stable topographic maps representing large-scale network activity. Additionally, they analyzed the temporal dynamics of microstate sequences using entropy rate, autoinformation function, and Hurst exponent to measure short- and long-range correlations. The results indicated that idea generation was associated with the highest cognitive workload and the lowest cognitive control compared to other design activities. TRP analysis revealed significant decreases in delta, theta, alpha, and beta power during idea generation, consistent with increased mental effort. EEG microstate analysis supported this finding, showing that microstate class C, which is negatively associated with the cognitive control network and linked to the default-mode network, was most prevalent during idea generation. Furthermore, microstate sequence analysis demonstrated that idea generation had the shortest temporal correlation times across all metrics (entropy rate, autoinformation, and Hurst exponent). This suggests that during idea generation, the interplay of functional brain networks is less restricted, granting the brain more degrees of freedom in transitioning between network configurations. These findings conclude that idea generation in open-ended tasks is characterized by high cognitive workload and reduced cognitive control, reflected in specific EEG oscillatory patterns and dynamic network behaviors. The study validates the use of loosely controlled experimental settings and EEG microstate analysis for studying complex, non-stationary cognitive processes. By demonstrating that idea generation involves a more flexible and less constrained neural state, the research provides a quantitative framework for understanding the neural basis of creativity and design thinking, distinguishing it from more controlled cognitive activities like evaluation.

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• neuro workload indices