Beyond The Limit: Characterizing The Neural Dynamics Of Physical Exhaustion

Reaching maximal physical exhaustion is a complex transition involving metabolic, cardiorespiratory, and neural adaptations. As exercise intensity rises, a transition to anaerobic metabolism occurs, reaching the anaerobic threshold, where anaerobic mechanisms supplement aerobic energy production. Eventually, individuals reach the volitional exhaustion threshold, becoming unable to sustain the required power output. Traditional paradigms focus on metabolic and cardiorespiratory indices but fail to accurately identify individual exhaustion points. PURPOSE: The present study aimed to characterize the neural dynamics during physical exhaustion, identifying markers of voluntary exercise cessation. METHODS: Thirty participants completed a maximal incremental cycling test to exhaustion on a stationary bike. Every 5 minutes, the resistance increased by 30 watts until participants reached volitional exhaustion. Electroencephalography (EEG) and cardiorespiratory monitoring were recorded throughout the protocol. EEG complexity was quantified using entropy-based measures (Kolmogorov-Sinai entropy) to capture nonlinear neural changes. A cluster-based non-parametric permutation test was conducted with time as the main effect and entropy as dependent variable. RESULTS: In the early stages of exercise, a significant increase (p ≤ 0.001) in entropy was observed within a cluster comprising 56 electrodes across the whole scalp, peaking at warm-up. This was followed by a significant decrease in entropy near exhaustion, with a second cluster of 55 electrodes showing reduced entropy (p ≤ 0.05) over the whole scalp in the final phase of exercise. Additionally, a comparison between initial baseline and post-exercise baseline revealed a significant reduction in entropy (p ≤ 0.05) within a cluster of 47 electrodes over central and fronto-temporal areas, suggesting a prolonged neural adaptation beyond the exercise period. CONCLUSION: Our findings suggest that brain entropy undergoes distinct adaptations throughout progressive physical exertion, potentially serving as a novel biomarker for effort regulation and voluntary exercise cessation. FUNDING: This work was funded by UK Research and Innovation under the UK government’s Horizon Europe funding guarantee (EP/Y029100/1)