Flow, an optimal experience characterized by deep immersion and engagement in an activity, has been extensively studied in behavioral research. However, its neural dynamic mechanism remains poorly understood. In a within-subject video gaming experiment, we captured neural activity underlying flow, boredom, and anxiety using a 64-channel electroencephalogram (EEG) system. Compared to boredom and anxiety, flow exhibits the highest global functional connectivity, metastability, and dimensionality of dynamic functional connectivity patterns, suggesting that flow is a highly adaptable process that is supported by high-dimensional neural dynamics. Unlike previous studies that focused on identifying static or localized brain activity, we examine the neural dynamic patterns of flow and propose the Global Dynamic Flow Model that characterizes flow as a high-dimensional, global metastable neural activity. Our study offers novel insights into the role of high-dimensionality and global metastability in brain activity associated with the flow experience.
Eldaly et al. (Mon,) studied this question.