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, a phenomenological experience frequently elicited by interactive media, 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 brain-wide dynamics, but this approach has rarely been applied to flow or to its natural comparisons: boredom and frustration. Consequently, it remains unclear whether tools drawn from complexity science can objectively discriminate between these phenomenological experiences while also clarifying their neural basis. To address this uncertainty, we induced each phenomenological experience with a difficulty-titrated video game during functional magnetic resonance imaging and collected concurrent behavioral and self-report data. Our complex systems analyses revealed that flow, in this experimental setup, shows an inverse relationship to global entropy with moderate explanatory power, and is not explained by either synchronization or metastability, whereas boredom and frustration exhibit different configurations of brain-dynamics metrics. Notably, these findings integrate previously separate prefrontal and network-synchrony observations within a single dynamical systems framework and identify complexity-based markers with the potential to map the neural underpinnings of media-related benefits.