Assessing cardiorespiratory interactions via lagged joint symbolic dynamics during spontaneous and controlled breathing

Frontiers in Network Physiology

Network Physiology

Francesca Gelpi¹  Beatrice Cairo¹  Vlasta Bari²  Alberto Porta²  Beatrice De Maria³ 

[1] Department of Biomedical Sciences for Health, University of Milan, Milan, Italy;Department of Biomedical Sciences for Health, University of Milan, Milan, Italy;Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato Milanese, Milan, Italy;IRCCS Istituti Clinici Scientifici Maugeri, Milan, Italy;

关键词: coupling strength;    phase relationship;    nonlinear interactions;    heart rate variability;    respiratory sinus arrhythmia;    cardiac control;    autonomic nervous system;   

DOI  :  10.3389/fnetp.2023.1211848

 received in 2023-04-25, accepted in 2023-07-13,  发布年份 2023

来源: Frontiers

【 摘 要 】

Introduction: Joint symbolic analysis (JSA) can be utilized to describe interactions between time series while accounting for time scales and nonlinear features. JSA is based on the computation of the rate of occurrence of joint patterns built after symbolization. Lagged JSA (LJSA) is obtained from the more classical JSA by introducing a delay/lead between patterns built over the two series and combined to form the joint scheme, thus monitoring coordinated patterns at different lags.Methods: In the present study, we applied LJSA for the assessment of cardiorespiratory coupling (CRC) from heart period (HP) variability and respiratory activity (R) in 19 healthy subjects (age: 27–35 years; 8 males, 11 females) during spontaneous breathing (SB) and controlled breathing (CB). The R rate of CB was selected to be indistinguishable from that of SB, namely, 15 breaths·minute−1 (CB15), or slower than SB, namely, 10 breaths·minute−1 (CB10), but in both cases, very rapid interactions between heart rate and R were known to be present. The ability of the LJSA approach to follow variations of the coupling strength was tested over a unidirectionally or bidirectionally coupled stochastic process and using surrogate data to test the null hypothesis of uncoupling.Results: We found that: i) the analysis of surrogate data proved that HP and R were significantly coupled in any experimental condition, and coupling was not more likely to occur at a specific time lag; ii) CB10 reduced CRC strength at the fastest time scales while increasing that at intermediate time scales, thus leaving the overall CRC strength unvaried; iii) despite exhibiting similar R rates and respiratory sinus arrhythmia, SB and CB15 induced different cardiorespiratory interactions; iv) no dominant temporal scheme was observed with relevant contributions of HP patterns either leading or lagging R.Discussion: LJSA is a useful methodology to explore HP–R dynamic interactions while accounting for time shifts and scales.

【 授权许可】

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