Li Penghai, Yu Dongfang, Cheng Longlong, Wang Kun
School of Electrical Engineering and Electronics, Tianjin University of Technology, Tianjin, China.
China Electronics Cloud Brain (Tianjin) Technology Co., Ltd., Tianjin, China.
Front Hum Neurosci. 2025 May 21;19:1545492. doi: 10.3389/fnhum.2025.1545492. eCollection 2025.
Motor imagery (MI) has emerged as a promising technique for enhancing motor skill acquisition and facilitating neural adaptation training. Attention plays a key role in regulating the neural mechanisms underlying MI. This study aims to investigate how attentional states modulate EEG-based lower-limb motor imagery performance by influencing event-related desynchronization (ERD) and the alpha modulation index (AMI) and to develop a real-time attention monitoring method based on the theta/beta ratio (TBR).
Fourteen healthy right-handed subjects (aged 21-23) performed right-leg MI tasks, while their attentional states were modulated via a key-press paradigm. EEG signals were recorded using a 32-channel system and preprocessed with independent component analysis (ICA) to remove artifacts. Attentional states were quantified using both the traditional offline AMI and the real-time TBR index, with time-frequency analysis applied to assess ERD and its relationship with attention.
The results indicated a significant increase in ERD during high attentional states compared to low attentional states, with AMI values showing a strong positive correlation with ERD ( = 0.9641, < 0.01). Cluster-based permutation testing confirmed that this -band ERD difference was significant (corrected < 0.05). Moreover, the TBR index proved to be an effective real-time metric, decreasing significantly under focused attention. Offline paired -tests showed a significant TBR reduction [ = 5.12, = 2.4 × 10], and online analyses further validated second-by-second discrimination (Bonferroni-corrected < 0.01). These findings confirm the feasibility and efficacy of TBR for real-time attention monitoring and suggest that enhanced attentional focus during lower-limb MI can improve signal quality and overall performance.
This study reveals that attentional states significantly influence the neural efficiency of lower-limb motor imagery by modulating ERD/AMI and demonstrates that the TBR can serve as a real-time indicator of attention, providing a novel tool for optimizing attentional processes in motor skill training.
运动想象（MI）已成为一种有前景的技术，可用于提高运动技能习得和促进神经适应性训练。注意力在调节运动想象背后的神经机制中起着关键作用。本研究旨在探讨注意力状态如何通过影响事件相关去同步化（ERD）和阿尔法调制指数（AMI）来调节基于脑电图的下肢运动想象表现，并开发一种基于θ/β比率（TBR）的实时注意力监测方法。
14名健康的右利手受试者（年龄21 - 23岁）执行右腿运动想象任务，同时通过按键范式调节他们的注意力状态。使用32通道系统记录脑电图信号，并通过独立成分分析（ICA）进行预处理以去除伪迹。使用传统的离线AMI和实时TBR指数对注意力状态进行量化，应用时频分析来评估ERD及其与注意力的关系。
结果表明，与低注意力状态相比，高注意力状态下ERD显著增加，AMI值与ERD呈强正相关（r = 0.9641，p < 0.01）。基于聚类的置换检验证实该频段ERD差异具有显著性（校正p < 0.05）。此外，TBR指数被证明是一种有效的实时指标，在集中注意力时显著降低。离线配对t检验显示TBR显著降低[t = 5.12，p =
2.4 × 10 - 6]，在线分析进一步验证了逐秒辨别能力（Bonferroni校正p < 0.01）。这些发现证实了TBR用于实时注意力监测的可行性和有效性，并表明在下肢运动想象过程中增强注意力焦点可以提高信号质量和整体表现。
本研究表明注意力状态通过调节ERD/AMI显著影响下肢运动想象的神经效率，并证明TBR可作为注意力的实时指标，为优化运动技能训练中的注意力过程提供了一种新工具。
