Tuned for Creativity? Graph-Theoretical Mapping of Resting-State EEG Reveals Neural Signatures of Creativity

Abstract: Understanding how creativity is represented in the brain's intrinsic functional architecture remains a central challenge in cognitive neuroscience. While resting-state fMRI studies have revealed large-scale network correlates of creative potential, electroencephalography (EEG) offers a temporally precise and scalable approach to capture the fast oscillatory dynamics that underlie spontaneous neural organization. In this study, we used a data-driven network approach to examine whether resting-state EEG connectivity patterns differentiate individuals according to their creative abilities. Creativity was evaluated by: The Inventory of Creative Activities and Achievements (ICAA), The Divergent Association Task (DAT), The Matchstick Arithmetic Puzzles Task (MAPT) and Self-rating (SR) of creative ability in 30 healthy young adults. Graph-theoretical analyses were applied to functional connectivity matrices and clustered based on graph similarity. Two distinct participant clusters emerged, differing systematically across multiple dimensions of creativity. Cluster 1, characterized by consistently higher performance across multiple creativity variables (ICAA, DAT, MAPT and SR), showed broad alpha-band hypoconnectivity, relatively preserved left frontal connectivity and greater network modularity. Cluster 0, associated with lower creativity scores, exhibited stronger overall connectivity strength, reduced modularity and higher local clustering. These findings suggest that resting-state EEG connectivity patterns can index stable cognitive traits such as creativity. More broadly, they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network organization that may support creative and adaptive cognition.