IEEE Trans Neural Syst Rehabil Eng. 2024;32:2482-2491. doi: 10.1109/TNSRE.2024.3424543. Epub 2024 Jul 11.
In recent years, there has been a surge in interest regarding the intricate physiological interplay between the brain and the heart, particularly during emotional processing. This has led to the development of various signal processing techniques aimed at investigating Brain-Heart Interactions (BHI), reflecting a growing appreciation for their bidirectional communication and influence on each other. Our study contributes to this burgeoning field by adopting a network physiology approach, employing time-delay stability as a quantifiable metric to discern and measure the coupling strength between the brain and the heart, specifically during visual emotional elicitation. We extract and transform features from EEG and ECG signals into a 1 Hz format, facilitating the calculation of BHI coupling strength through stability analysis on their maximal cross-correlation. Notably, our investigation sheds light on the critical role played by low-frequency components in EEG, particularly in the δ , θ , and α bands, as essential mediators of information transmission during the complex processing of emotion-related stimuli by the brain. Furthermore, our analysis highlights the pivotal involvement of frontal pole regions, emphasizing the significance of δ - θ coupling in mediating emotional responses. Additionally, we observe significant arousal-dependent changes in the θ frequency band across different emotional states, particularly evident in the prefrontal cortex. By offering novel insights into the synchronized dynamics of cortical and heartbeat activities during emotional elicitation, our research enriches the expanding knowledge base in the field of neurophysiology and emotion research.
近年来,人们对大脑和心脏之间复杂的生理相互作用,特别是在情绪处理过程中的相互作用,产生了浓厚的兴趣。这导致了各种信号处理技术的发展,旨在研究脑心相互作用(BHI),反映出人们对它们之间双向通信和相互影响的认识不断提高。我们的研究通过采用网络生理学方法为这个蓬勃发展的领域做出了贡献,使用时滞稳定性作为可量化的指标,来区分和测量大脑和心脏之间的耦合强度,特别是在视觉情绪诱发期间。我们从 EEG 和 ECG 信号中提取和转换特征,并将其转换为 1 Hz 的格式,通过对它们最大互相关的稳定性分析来计算 BHI 耦合强度。值得注意的是,我们的研究揭示了 EEG 中低频成分(特别是 δ、θ 和 α 波段)在大脑对情绪相关刺激进行复杂处理过程中信息传输的关键作用。此外,我们的分析强调了额极区域的关键作用,突出了 δ-θ 耦合在介导情绪反应中的重要性。此外,我们观察到不同情绪状态下 θ 频段的显著唤醒依赖变化,在前额叶皮层中尤为明显。通过提供情绪诱发过程中皮质和心跳活动同步动力学的新见解,我们的研究丰富了神经生理学和情绪研究领域不断扩大的知识库。