AI 中文总结
研究针对脑电连接性分析中现有方法的不足，引入空间相邻散射变换，通过扩展小波散射变换到多通道设置，获取幅度包络耦合及跨频率调制信息，经实验验证其能系统恢复相关耦合结构，为脑电分析提供新方法。
AI 中文摘要
大脑的功能组织依赖于空间分布区域间的协同活动，分析区域间依赖性至关重要。现有连接性测量主要通过相位同步，易受容积传导伪影影响且忽略幅度域耦合。本研究引入空间相邻散射变换，将小波散射变换扩展到多通道设置，产生两个描述符来联合捕获通道间幅度包络耦合及其跨频率尺度的调制。在BCI竞赛IV-2a运动想象数据集上评估，用偏差校正、错误发现率控制的统计管道，验证标准为跨受试者显著耦合的空间一致性。一阶描述符识别出中央顶叶电极邻域内具有统计学意义的幅度耦合，二阶描述符揭示该耦合受慢节律周期性控制。与相位滞后指数等对比，表明幅度包络耦合构成独特连接信号。结果表明空间相邻散射变换是一种基于跨通道散射的连接性描述符，可系统恢复幅度包络和跨频率耦合结构，适用于关注幅度域区域间依赖性的多通道脑电分析。
英文摘要
The functional organization of the brain relies on coordinated activity across spatially distributed regions, making the analysis of inter-regional dependencies fundamental. Existing connectivity measures address this predominantly through phase synchronization, which is vulnerable to volume conduction artifacts and discards amplitude-domain coupling. This study introduces the Spatial Neighboring Scattering Transform, which extends the wavelet scattering transform to the multichannel setting, yielding two descriptors that jointly capture amplitude-envelope coupling between channels and its modulation across frequency scales. SNST was evaluated on the BCI Competition IV-2a motor imagery dataset using a bias-corrected, false-discovery-rate-controlled statistical pipeline, with the validation criterion defined as spatial consistency of significant coupling across subjects. The first-order descriptor identified statistically significant amplitude coupling within a central-parietal electrode neighborhood, reproduced consistently across all subjects and both imagery conditions. The second-order descriptor revealed that this coupling is periodically gated by slow rhythms, indicating a cross-frequency amplitude-modulation structure absent from single-frequency connectivity measures. Phase lag index and weighted phase lag index, computed under an identical correction procedure and verified robust to volume conduction, identified negligible significant coupling with zero overlap with SNST findings, demonstrating that amplitude envelope coupling constitutes a largely distinct connectivity signal. These results establish SNST as a cross-channel scattering-based connectivity descriptor that recovers amplitude-envelope and cross-frequency coupling structure systematically, applicable to any multichannel EEG analysis where amplitude-domain inter-regional dependence is of interest.
Comments12 pages, 7 Figures
