Lin D C, Sharif A
Department of Mechanical and Industrial Engineering, Ryerson University Toronto, ON, Canada.
Front Physiol. 2012 Feb 7;2:123. doi: 10.3389/fphys.2011.00123. eCollection 2011.
The aim of this study was to characterize the central-autonomic interaction underlying the multifractality in heart rate variability (HRV) of healthy humans.
Eleven young healthy subjects participated in two separate ~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt (HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG) and electrocardiogram (ECG) were collected and fractal correlation of brain and heart rate data was analyzed based on the idea of relative multifractality. The fractal correlation was further examined with the EEG, HRV spectral measures using linear regression of two variables and principal component analysis (PCA) to find clues for the physiological processing underlying the central influence in fractal HRV.
We report evidence of a central-autonomic fractal correlation (CAFC) where the HRV multifractal complexity varies significantly with the fractal correlation between the heart rate and brain data (P = 0.003). The linear regression shows significant correlation between CAFC measure and EEG Beta band spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is significant correlation between CAFC measure and HRV LF component in the SUP position (P = 0.04), whereas the correlation with the HRV HF component approaches significance (P = 0.07). The correlation between CAFC measure and HRV spectral measures in the UPR position is weak. The PCA results confirm these findings and further imply multiple physiological processes underlying CAFC, highlighting the importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in the supine position.
The findings of this work can be summarized into three points: (i) Similar fractal characteristics exist in the brain and heart rate fluctuation and the change toward stronger fractal correlation implies the change toward more complex HRV multifractality. (ii) CAFC is likely contributed by multiple physiological mechanisms, with its central elements mainly derived from the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is qualitatively different, with a more predominant central influence in the fractal HRV of the UPR position.
本研究旨在描述健康人心率变异性(HRV)多重分形背后的中枢 - 自主神经相互作用。
11名年轻健康受试者参加了两个单独的约40分钟实验环节,一个是仰卧位(SUP),另一个是头高位倾斜(HUT)直立位(UPR)。采集头皮表面脑电图(EEG)和心电图(ECG),并基于相对多重分形的概念分析脑电和心率数据的分形相关性。使用两个变量的线性回归和主成分分析(PCA)进一步研究EEG、HRV频谱测量的分形相关性,以寻找分形HRV中枢影响背后生理过程的线索。
我们报告了中枢 - 自主神经分形相关性(CAFC)的证据,其中HRV多重分形复杂性随心率与脑数据之间的分形相关性显著变化(P = 0.003)。线性回归显示CAFC测量值与EEGβ频段频谱成分之间存在显著相关性(仰卧位P = 0.01,直立位P = 0.002)。仰卧位时CAFC测量值与HRV低频成分之间存在显著相关性(P = 0.04),而与HRV高频成分的相关性接近显著水平(P = 0.07)。直立位时CAFC测量值与HRV频谱测量值之间的相关性较弱。PCA结果证实了这些发现,并进一步暗示了CAFC背后的多种生理过程,突出了仰卧位时EEGα、β频段以及HRV低频、高频频谱测量的重要性。
本研究结果可总结为三点:(i)脑电和心率波动中存在相似的分形特征,分形相关性增强意味着HRV多重分形复杂性增加。(ii)CAFC可能由多种生理机制导致,其核心要素主要源于EEGα、β频段动态变化。(iii)仰卧位和直立位的CAFC在性质上不同,直立位时分形HRV的中枢影响更为显著。