Continuous brain-computer interfaces (BCIs) that decode motion trajectories from imagined movement offer intuitive motor control, yet how feedback modality and longitudinal training shape neural representations and decoding performance remains poorly understood. We present the first systematic investigation of embodied virtual reality (VR) feedback during real-time 3D virtual limb control driven by motor imagery, across ten longitudinal sessions in ten participants. Performance was evaluated using three strategies: actual online performance (Fixed Decoder Generalisation, FDG), periodic retraining (Sequential Adaptive Training, SAT), and within-session upper-bound estimation (Within-Session Reconstruction, WSR). A CNN-LSTM decoder achieved within-session imagined movement correlations of r = 0.762 under VR and r = 0.672 under screen feedback. VR significantly outperformed screen feedback across all strategies and movement dimensions (improvements of 8.9-13.0%, all p <= 0.002, d = 1.42-2.05). This advantage persisted under fixed decoders without retraining, demonstrating that embodied VR feedback elicits inherently more decodable and generalisable neural representations. Linear mixed-effects modelling confirmed robust main effects of feedback modality and movement axis with no interaction. Neurophysiologically, VR produced stronger sensorimotor-parietal desynchronisation and enhanced motor-frontal functional connectivity, with pervasive anterior insula engagement across all frequency bands and increased superior parietal lobule coupling, paralleling patterns associated with real movement execution. These findings establish embodied spatial feedback as a key design principle for next-generation continuous BCIs targeting intuitive motor control and neurorehabilitation.

翻译：连续脑机接口（BCI）通过从想象运动中解码运动轨迹实现直观的运动控制，然而反馈模态和纵向训练如何塑造神经表征及解码性能仍待阐明。我们首次系统研究了在运动想象驱动的实时三维虚拟肢体控制过程中，具身虚拟现实（VR）反馈的作用，共涉及十名被试的十个纵向实验会话。采用三种策略评估性能：实际在线性能（固定解码器泛化，FDG）、周期性重训练（序贯自适应训练，SAT）以及会话内上限估计（会话内重建，WSR）。CNN-LSTM解码器在VR反馈下实现了会话内想象运动相关系数r=0.762，而在屏幕反馈下为r=0.672。在所有策略和运动维度上，VR反馈均显著优于屏幕反馈（改善幅度8.9-13.0%，所有p≤0.002，d=1.42-2.05）。该优势在无需重训练的固定解码器条件下依然保持，表明具身VR反馈可诱发本质上更易解码和泛化的神经表征。线性混合效应模型证实反馈模态和运动轴具有稳健的主效应且无交互作用。在神经生理层面，VR反馈产生了更强的感觉运动-顶叶去同步化和增强的运动-额叶功能连接，所有频段均出现广泛的前岛叶激活，并增加了顶上小叶耦合，这与实际运动执行的相关模式相平行。这些发现确立了具身空间反馈作为面向直观运动控制和神经康复的下一代连续BCI的关键设计原则。