Cairo Beatrice, Bari Vlasta, Gelpi Francesca, De Maria Beatrice, Porta Alberto
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.
Front Netw Physiol. 2023 Aug 3;3:1211848. doi: 10.3389/fnetp.2023.1211848. eCollection 2023.
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. 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 (CB15), or slower than SB, namely, 10 breaths·minute (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. 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. LJSA is a useful methodology to explore HP-R dynamic interactions while accounting for time shifts and scales.
联合符号分析（JSA）可用于描述时间序列之间的相互作用，同时考虑时间尺度和非线性特征。JSA基于对符号化后构建的联合模式出现率的计算。滞后联合符号分析（LJSA）是通过在两个序列上构建的模式之间引入延迟/超前，并将其组合形成联合方案，从更经典的JSA中获得的，从而监测不同滞后时的协调模式。在本研究中，我们应用LJSA评估了19名健康受试者（年龄：27 - 35岁；8名男性，11名女性）在自主呼吸（SB）和控制呼吸（CB）期间，从心率变异性（HP）和呼吸活动（R）中得到的心-肺耦合（CRC）情况。CB的呼吸频率被选择为与SB的呼吸频率难以区分，即15次呼吸·分钟（CB15），或比SB慢，即10次呼吸·分钟（CB10），但在这两种情况下，已知心率和R之间存在非常快速的相互作用。通过单向或双向耦合随机过程测试了LJSA方法跟踪耦合强度变化的能力，并使用替代数据检验解耦的零假设。我们发现：i）替代数据分析证明，在任何实验条件下HP和R都显著耦合，且耦合不太可能在特定的时间滞后发生；ii）CB10在最快的时间尺度上降低了CRC强度，同时在中间时间尺度上增加了CRC强度，从而使整体CRC强度不变；iii）尽管SB和CB15表现出相似的呼吸频率和呼吸性窦性心律不齐，但它们诱导了不同的心-肺相互作用；iv）未观察到具有HP模式领先或滞后R的相关贡献的主导时间方案。LJSA是一种有用的方法，可用于探索HP - R动态相互作用，同时考虑时间偏移和尺度。
