Neural dynamics track the approach to physical exhaustion

Abstract

Physical exhaustion has long been described through its cardiorespiratory and metabolic cost, while the neural dynamics of its approach remain largely unexplored. Here we recorded high-density electroencephalography in 28 trained cyclists during a maximal incremental test to characterise how neural dynamics change towards exhaustion. As physiological strain rose, oscillatory power shifted to lower frequencies, neural activity became more regular and predictable, and functional coupling extended to longer timescales. Participant-specific models built on neural dynamics tracked proximity to exhaustion with accuracy comparable to cardiorespiratory measures. Over the final minutes, neural features remained informative while cardiorespiratory measures lost accuracy. Models trained across participants still tracked proximity to exhaustion, but less precisely. The approach to exhaustion thus follows a common neural path, tuned to each individual.