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Evolution of cardiorespiratory interactions with age.

Iatsenko D, Bernjak A, Stankovski T, Shiogai Y, Owen-Lynch PJ, Clarkson PB, McClintock PV, Stefanovska A - Philos Trans A Math Phys Eng Sci (2013)

Bottom Line: We describe an analysis of cardiac and respiratory time series recorded from 189 subjects of both genders aged 16-90.By application of the synchrosqueezed wavelet transform, we extract the respiratory and cardiac frequencies and phases with better time resolution than is possible with the marked events procedure.We show that the direct and indirect respiratory modulations of the heart rate both decrease with age, and that the cardiorespiratory coupling becomes less stable and more time-variable.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Lancaster University, Lancaster LA1 4YB, UK.

ABSTRACT
We describe an analysis of cardiac and respiratory time series recorded from 189 subjects of both genders aged 16-90. By application of the synchrosqueezed wavelet transform, we extract the respiratory and cardiac frequencies and phases with better time resolution than is possible with the marked events procedure. By treating the heart and respiration as coupled oscillators, we then apply a method based on Bayesian inference to find the underlying coupling parameters and their time dependence, deriving from them measures such as synchronization, coupling directionality and the relative contributions of different mechanisms. We report a detailed analysis of the reconstructed cardiorespiratory coupling function, its time evolution and age dependence. We show that the direct and indirect respiratory modulations of the heart rate both decrease with age, and that the cardiorespiratory coupling becomes less stable and more time-variable.

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Wavelet phase coherence (WPC) as a function of frequency. The full black lines show the median (over all subjects) WPC between (a) respiration and instantaneous heart frequency (IHF) and (b) instantaneous respiration frequency (IRF) and IHF. The dashed grey lines indicate the mean of the surrogates, and the full grey lines show the surrogates' 95% significance level: the phase coherence is regarded as significant if it is higher than this. Vertical dotted lines indicate the boundaries of frequency regions corresponding to different physiological components [41, p. 74]: (I) cardiac, (II) respiratory, (III) myogenic, (IV) neurogenic, (V) NO-related endothelial.
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RSTA20110622F4: Wavelet phase coherence (WPC) as a function of frequency. The full black lines show the median (over all subjects) WPC between (a) respiration and instantaneous heart frequency (IHF) and (b) instantaneous respiration frequency (IRF) and IHF. The dashed grey lines indicate the mean of the surrogates, and the full grey lines show the surrogates' 95% significance level: the phase coherence is regarded as significant if it is higher than this. Vertical dotted lines indicate the boundaries of frequency regions corresponding to different physiological components [41, p. 74]: (I) cardiac, (II) respiratory, (III) myogenic, (IV) neurogenic, (V) NO-related endothelial.

Mentions: Figure 4 shows the results for all subjects, but we have found that the same considerations apply to males and females separately. In the respiration–IHF phase coherence (figure 4a), there is a highly significant peak in the respiratory frequency range, corresponding to the well-known respiratory sinus arrhythmia (RSA). It was also observed previously in the cardiorespiratory coherence function, although the corresponding significance levels were not always estimated reliably (see [53] for discussion and references therein). We have observed a decrease with age in the respiratory peak WPC (not shown: ρ=−0.38 for males and ρ=−0.35 for females with p<0.001 for both). Coupled with the fact that the respiratory frequency and its standard deviation do not depend on age (figure 1b), this suggests that RSA becomes more unstable with age.Figure 4.


Evolution of cardiorespiratory interactions with age.

Iatsenko D, Bernjak A, Stankovski T, Shiogai Y, Owen-Lynch PJ, Clarkson PB, McClintock PV, Stefanovska A - Philos Trans A Math Phys Eng Sci (2013)

Wavelet phase coherence (WPC) as a function of frequency. The full black lines show the median (over all subjects) WPC between (a) respiration and instantaneous heart frequency (IHF) and (b) instantaneous respiration frequency (IRF) and IHF. The dashed grey lines indicate the mean of the surrogates, and the full grey lines show the surrogates' 95% significance level: the phase coherence is regarded as significant if it is higher than this. Vertical dotted lines indicate the boundaries of frequency regions corresponding to different physiological components [41, p. 74]: (I) cardiac, (II) respiratory, (III) myogenic, (IV) neurogenic, (V) NO-related endothelial.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4042892&req=5

RSTA20110622F4: Wavelet phase coherence (WPC) as a function of frequency. The full black lines show the median (over all subjects) WPC between (a) respiration and instantaneous heart frequency (IHF) and (b) instantaneous respiration frequency (IRF) and IHF. The dashed grey lines indicate the mean of the surrogates, and the full grey lines show the surrogates' 95% significance level: the phase coherence is regarded as significant if it is higher than this. Vertical dotted lines indicate the boundaries of frequency regions corresponding to different physiological components [41, p. 74]: (I) cardiac, (II) respiratory, (III) myogenic, (IV) neurogenic, (V) NO-related endothelial.
Mentions: Figure 4 shows the results for all subjects, but we have found that the same considerations apply to males and females separately. In the respiration–IHF phase coherence (figure 4a), there is a highly significant peak in the respiratory frequency range, corresponding to the well-known respiratory sinus arrhythmia (RSA). It was also observed previously in the cardiorespiratory coherence function, although the corresponding significance levels were not always estimated reliably (see [53] for discussion and references therein). We have observed a decrease with age in the respiratory peak WPC (not shown: ρ=−0.38 for males and ρ=−0.35 for females with p<0.001 for both). Coupled with the fact that the respiratory frequency and its standard deviation do not depend on age (figure 1b), this suggests that RSA becomes more unstable with age.Figure 4.

Bottom Line: We describe an analysis of cardiac and respiratory time series recorded from 189 subjects of both genders aged 16-90.By application of the synchrosqueezed wavelet transform, we extract the respiratory and cardiac frequencies and phases with better time resolution than is possible with the marked events procedure.We show that the direct and indirect respiratory modulations of the heart rate both decrease with age, and that the cardiorespiratory coupling becomes less stable and more time-variable.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Lancaster University, Lancaster LA1 4YB, UK.

ABSTRACT
We describe an analysis of cardiac and respiratory time series recorded from 189 subjects of both genders aged 16-90. By application of the synchrosqueezed wavelet transform, we extract the respiratory and cardiac frequencies and phases with better time resolution than is possible with the marked events procedure. By treating the heart and respiration as coupled oscillators, we then apply a method based on Bayesian inference to find the underlying coupling parameters and their time dependence, deriving from them measures such as synchronization, coupling directionality and the relative contributions of different mechanisms. We report a detailed analysis of the reconstructed cardiorespiratory coupling function, its time evolution and age dependence. We show that the direct and indirect respiratory modulations of the heart rate both decrease with age, and that the cardiorespiratory coupling becomes less stable and more time-variable.

Show MeSH
Related in: MedlinePlus