A Complexity-Science Framework for Studying Flow: Using Media to Probe Brain– Phenomenology Dynamics

Consciousness spans a range of phenomenological experiences, from effortless immersion to disengaged monotony, yet how such phenomenology emerges from brain activity is not well understood. Flow, in particular, has drawn attention for its links to performance and wellbeing, but existing neural accounts rely on single-region or small-network analyses that overlook the brain’s distributed and dynamic nature. Complexity science offers tools that capture whole-brain dynamics, but this approach has rarely been applied to flow or to its natural comparison states of boredom and frustration. Consequently, it remains unclear whether tools drawn from complexity science can objectively separate phenomenological experiences while also clarifying their neural basis. Here we show that a complexity science approach distinguishes flow from boredom and frustration. We induced each phenomenological experience with a difficulty-titrated video game during functional magnetic resonance imaging and collected concurrent behavioral and self-report data. Whole-brain analyses revealed that flow is marked by lower global entropy, higher dynamical agility, and decreased dynamical complexity, whereas boredom and frustration exhibit different configurations of brain-dynamics metrics. Notably, these findings integrate previously separate prefrontal, network-synchrony, and cerebellar observations within a single dynamical systems framework and identify complexity-based markers that map the neural correlates of media-related benefits.