The Readiness-Efficiency Coupling

Motor sequence learning (MSL) involves transitioning from reactive, stimulus-led control to predictive, automated execution. While expertise is traditionally quantified by speed and accuracy, the underlying organizational shifts in fractal movement variability remain poorly understood. We propose the Readiness-Efficiency hypothesis: expertise emerges through a functional coupling of high preparatory complexity and reduced execution complexity. Participants (n = 22) performed a whole-body Dance Discrete Sequence Production task while Center of Mass (CoM) kinematics were recorded. Hurst exponents (H) quantified fractal complexity across ten blocks of practice and transfer. As learning progressed, preparatory dynamics shifted toward higher complexity (H<inf>prep</inf>↑), reflecting structured readiness, while execution dynamics shifted toward reduced complexity (H<inf>exec</inf>↓), reflecting automated efficiency. Crucially, a three-way interaction revealed that the fastest response times were achieved specifically when high preparatory readiness was coupled with reduced execution complexity. This coupling collapsed upon transfer to novel sequences, indicating task-specificity. State-space analysis confirmed the Readiness-Efficiency configuration acts as a functional attractor, with the probability of occupying this state increasing five-fold through practice. These findings demonstrate that expertise is characterized by dynamic flexibility–the capacity to dissociate and pair control regimes to meet phase-specific demands–providing a mechanistic framework for profiling skill acquisition.