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Coupling between Blood Pressure and Subarachnoid Space Width Oscillations during Slow Breathing
Entropy ( IF 2.1 ) Pub Date : 2021-01-15 , DOI: 10.3390/e23010113
Agnieszka Gruszecka , Magdalena K. Nuckowska , Monika Waskow , Jacek Kot , Pawel J. Winklewski , Wojciech Guminski , Andrzej F. Frydrychowski , Jerzy Wtorek , Adam Bujnowski , Piotr Lass , Tomislav Stankovski , Marcin Gruszecki

The precise mechanisms connecting the cardiovascular system and the cerebrospinal fluid (CSF) are not well understood in detail. This paper investigates the couplings between the cardiac and respiratory components, as extracted from blood pressure (BP) signals and oscillations of the subarachnoid space width (SAS), collected during slow ventilation and ventilation against inspiration resistance. The experiment was performed on a group of 20 healthy volunteers (12 females and 8 males; BMI=22.1±3.2 kg/m2; age 25.3±7.9 years). We analysed the recorded signals with a wavelet transform. For the first time, a method based on dynamical Bayesian inference was used to detect the effective phase connectivity and the underlying coupling functions between the SAS and BP signals. There are several new findings. Slow breathing with or without resistance increases the strength of the coupling between the respiratory and cardiac components of both measured signals. We also observed increases in the strength of the coupling between the respiratory component of the BP and the cardiac component of the SAS and vice versa. Slow breathing synchronises the SAS oscillations, between the brain hemispheres. It also diminishes the similarity of the coupling between all analysed pairs of oscillators, while inspiratory resistance partially reverses this phenomenon. BP-SAS and SAS-BP interactions may reflect changes in the overall biomechanical characteristics of the brain.

中文翻译:

慢呼吸期间血压与蛛网膜下腔宽度振荡的耦合

连接心血管系统和脑脊液 (CSF) 的精确机制尚不清楚。本文研究了心脏和呼吸成分之间的耦合,这些成分是从血压 (BP) 信号和蛛网膜下腔宽度 (SAS) 的振荡中提取的,这些信号是在缓慢通气和针对吸气阻力的通气过程中收集的。实验在一组 20 名健康志愿者(12 名女性和 8 名男性;BMI=22.1±3.2 kg/m2;年龄 25.3±7.9 岁)上进行。我们用小波变换分析了记录的信号。首次使用基于动态贝叶斯推理的方法来检测 SAS 和 BP 信号之间的有效相位连通性和潜在耦合函数。有几个新发现。有或没有阻力的缓慢呼吸增加了两个测量信号的呼吸和心脏分量之间的耦合强度。我们还观察到 BP 的呼吸分量和 SAS 的心脏分量之间的耦合强度增加,反之亦然。缓慢的呼吸使大脑半球之间的 SAS 振荡同步。它还降低了所有分析的振荡器对之间耦合的相似性,而吸气阻力部分地逆转了这种现象。BP-SAS 和 SAS-BP 相互作用可能反映大脑整体生物力学特征的变化。我们还观察到 BP 的呼吸分量和 SAS 的心脏分量之间的耦合强度增加,反之亦然。缓慢的呼吸使大脑半球之间的 SAS 振荡同步。它还降低了所有分析的振荡器对之间耦合的相似性,而吸气阻力部分地逆转了这种现象。BP-SAS 和 SAS-BP 相互作用可能反映大脑整体生物力学特征的变化。我们还观察到 BP 的呼吸分量和 SAS 的心脏分量之间的耦合强度增加,反之亦然。缓慢的呼吸使大脑半球之间的 SAS 振荡同步。它还降低了所有分析的振荡器对之间耦合的相似性,而吸气阻力部分地逆转了这种现象。BP-SAS 和 SAS-BP 相互作用可能反映大脑整体生物力学特征的变化。
更新日期:2021-01-15
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