发现大脑皮层说话时存在两成分激活抑制模式。
Two-component spatiotemporal template for activation-inhibition of speech in ECoG
- 用主成分分析提取电极信号的时空特征。
- 揭示β与γ频段活动呈现两成分拮抗关系。
- 适用于研究语言运动控制与神经调控机制。
我计算了多例受试者在辅音-元音发音任务中，高密度皮层脑电图（ECoG）多通道数据在不同时间窗内的带通功率平均值。结果显示，在感觉运动皮层（SMC）中，先前报道的β频段（12-35 Hz）与高频频段γ活动（70-140 Hz）之间的负相关关系可在单个电极间观察到。基于此，我对会话平均的SMC电极带通功率数据进行方差建模，采用主成分分析（PCA）提取低维主成分，并将各电极投影至其主成分空间。通过滑动窗口相关性分析，将两个频段的主成分与各电极信号随时间的相关性进行关联。结果表明，主成分区域与感觉运动区之间存在明显的双成分激活-抑制型表征，类似近期发现的全身运动控制、抑制与姿势调节中的复杂交互作用。值得注意的是，第三主成分在所有受试者中均无显著相关性，说明仅需两个主成分即可充分表示说话过程中的SMC活动。
原文摘要 · Abstract (English)
I compute the average trial-by-trial power of band-limited speech activity across epochs of multi-channel high-density electrocorticography (ECoG) recorded from multiple subjects during a consonant-vowel speaking task. I show that previously seen anti-correlations of average beta frequency activity (12-35 Hz) to high-frequency gamma activity (70-140 Hz) during speech movement are observable between individual ECoG channels in the sensorimotor cortex (SMC). With this I fit a variance-based model using principal component analysis to the band-powers of individual channels of session-averaged ECoG data in the SMC and project SMC channels onto their lower-dimensional principal components. Spatiotemporal relationships between speech-related activity and principal components are identified by correlating the principal components of both frequency bands to individual ECoG channels over time using windowed correlation. Correlations of principal component areas to sensorimotor areas reveal a distinct two-component activation-inhibition-like representation for speech that resembles distinct local sensorimotor areas recently shown to have complex interplay in whole-body motor control, inhibition, and posture. Notably the third principal component shows insignificant correlations across all subjects, suggesting two components of ECoG are sufficient to represent SMC activity during speech movement.
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