Expertise-related functional connectivity changes in Chinese calligraphy linked to flow experience.

Abstract

Flow is a deeply immersive state that supports optimal performance, yet its neural basis under conditions of real-world expertise remains poorly understood. Using functional MRI, this study investigated how long-term Chinese calligraphy expertise relates to flow in a culturally meaningful setting. Expert and novice participants performed imagined embodied handwriting of Kai-Shu and Cao-Shu, which differ in motor and cognitive challenges. Expert calligraphers reported significantly higher flow than novices across both scripts, including in the more challenging Cao-Shu style despite having no formal training in it. Functional connectivity analyses were performed on background task-residual BOLD signals to assess intrinsic coupling that persists during performance. In Kai-Shu, experts showed stronger ventral anterior insula (vAI)-superior parietal lobule (SPL) connectivity and weaker vAI-ventral striatum (VS) connectivity, suggesting enhanced perception-action coupling and reduced task-irrelevant processing. In Cao-Shu, experts exhibited reduced anterior medial prefrontal cortex (aMPFC) connectivity with default mode network (DMN) regions, suggesting reduced self-referential processing under higher task challenges. These connectivity patterns were significantly associated with reported flow ratings and together suggest a flexible neural adaptation supporting task-focused engagement in familiar contexts and reduced introspection when demands increase. To further examine whether these effects form an integrated mechanism linking proficiency and flow, Bayesian network (BN) modeling revealed a directional dependency from expertise to functional connectivity to flow, suggesting that long-term practice contributes to a proficient neural mechanism that supports higher flow experiences during task engagement. These findings extend current accounts of flow by delineating how sustained expertise is associated with neural processing patterns that are linked to higher flow across varying task challenges.