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Title:: A review of methods for functional coupling and information transfer between the electric signal of heart and brain

作者:: 吴清缘1; 2; 3; 陈蕾4; 刘超1; 2; 3△; 伍海燕5△?; 1.北京师范大学认知神经科学与学习国家重点实验室，IDG/麦戈文脑研究院，北京 100875；2.北京师范大学脑与学习协同创新中心，北京 100875；3.北京师范大学神经影像大数据与人脑连接组学北京市重点实验室，北京 100875；4.四川大学华西医院神经内科，高原健康联合研究所，成都610041；5.澳门大学认知与脑科学研究中心, 澳门大学心理系, 澳门 999078

Author(s):: WU Qingyuan1; 2; 3; CHEN Lei4; LIU Chao1; 2; 3*; WU Haiyan5*; 1.State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University,[Beijing 100875, China；2.Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875；3.Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875；4.Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, China；5.Research Center for Cognitive and Brain Sciences, Department of Psychology, University of Macau, Macau 999078, China

Keywords:: Brain-heart coupling; EEG; Heart rate variability; Directionless measurement; Directional measurement; Disease surveillance indicators

摘要:: 我国传统医学认为人体心脑相通，提出心脑同治。现代医学中，大量观察性研究也证实了心脏疾病与大脑疾病之间的相关性。随着从电生理视角对心脑共病的研究逐渐发展，研究者们通过定量地描述心脑电信号之间的耦合关系，探究心脑耦合系统中的精细结构。这对于一些心脑相关的生理和心理疾病的监测与治疗均有着重要意义。本文整理了处理心脑电信号耦合的方法，包括相关系数、谱相干系数、最大信息系数、回归分析、格兰杰因果关系分析及信息熵等，总结了这些方法的应用特点，展望了心脑耦合领域未来的探索方向与临床应用。

Abstract:: Traditional Chinese medicine has long thought that the brain and heart are interlinked, and the cardio-cerebral pathogenesis is put forward. A large number of observational studies in modern medicine have also confirmed the correlation between heart disease and brain disease. With the development of electrophysiological research on cardio-brain comorbidities, people try to quantitatively describe the coupling relationship between the brain and heart signals, to explore the fine structure of the brain-heart coupling system. Exploring the coupling relationship between heart and brain is of great significance to the monitoring and treatment of some physiological and psychological diseases. Therefore, we summarize the methods of processing the coupling of ECG and EEG signal, including correlation coefficient, spectral coherence coefficient, maximum information coefficient calculation, regression analysis, Granger causality analysis and information entropy, and summarize the characteristics, advantages, and disadvantages of these methods. Finally, the future exploration direction and clinical application in the field of mind-brain coupling are discussed.