ORIGINAL RESEARCH article
Front. Physiol.
Sec. Exercise Physiology
Volume 16 - 2025 | doi: 10.3389/fphys.2025.1672704
Neural and behavioral correlates of rhythmic action anticipation and error monitoring in swimming: Evidence from EEG and behavioral assessments
Provisionally accepted
- 1北京师范大学体育与运动学院, 北京市, China
- 2济南市中医医院, 济南市, China
- 3清华大学, 北京市, China
- 4济南市群众体育事业发展中心, 济南市, China
- 5北京体育大学, 北京市, China
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Objective: This study, conducted between August 2022 and August 2023, aimed to investigate the behavioral and neural mechanisms underlying rhythmic action anticipation in swimming and compare these mechanisms between competitive and recreational athletes.Method:A total of 63 participants were enrolled: 28 competitive swimmers (CG, 8+ years of competitive experience) and 35 recreational swimmers (RG, 2 – 3 years of recreational training). All completed a video-based action judgment task (identifying valid/invalid swimming movements across 4 phases: start, stroke, turn, wall-touch), with EEG recorded to analyze ERP components (P300, N400, ERN, Pe) linked to anticipation and error monitoring.Results: Behaviorally: CG had higher valid-action judgment accuracy (76 ± 13% vs. RG 55 ± 17%, p<0.01), notably in the start (77±12% vs. 58±16%, p<0.01) and stroke phases (75±14% vs. 53 ±19%, p<0.05); RG performed better in invalid-action identification (39.5±10% vs. CG 25.5± 8.5%, p<0.05) in these two phases. No group differences were found in the turn or wall-touch phases (p>0.05). For ERP characteristics: CG exhibited larger P300 (valid: 2.39±0.89 μV vs. 1.26±1.05 μV, p=0.005) and N400 (invalid: -3.96±1.87 μV vs. -2.24±1.43 μV, p=0.023) amplitudes, as well as greater ERN amplitude (p=0.03). A significant three-way interaction (group × phase × outcome) for accuracy was observed (p<0.01), and group differences in ERP latencies were noted (p<0.05).Conclusion:Competitive swimmers develop specialized perceptual-cognitive schemas and neural adaptations (reflected in modulated ERP components) that support efficient anticipation of valid movements and sensitivity to technical errors. Practically, these findings inform two key applications: (1) Designing phase-specific training protocols (e.g., targeted drills for the start/stroke phases to enhance valid action prediction in CG) and (2) developing ERP marker-based neurofeedback interventions (e.g., using P300/N400 signals to optimize error monitoring) to refine personalized training strategies for swimmers at different skill levels.
Keywords: swimming athletes, Action prediction, event-related potentials (ERPs), Expertise, Judgment accuracy
Received: 24 Jul 2025; Accepted: 15 Sep 2025.
Copyright: © 2025 chen, chen, Yu, xian and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: tong chen, 852063164@qq.com
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