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Short‐term cardiovascular oscillations in man: measuring and modelling the physiologies
Open accessAbstract
Research into cardiovascular variabilities intersects both human physiology and quantitative modelling. This is because respiratory and Mayer wave (or 10 s) cardiovascular oscillations represent the integrated control of a system through both autonomic branches by systemic haemodynamic changes within a fluid‐filled, physical system. However, our current precise measurement of short‐term cardiovascular fluctuations does not necessarily mean we have an adequate understanding of them. Empirical observation suggests that both respiratory and Mayer wave fluctuations derive from mutable autonomic and haemodynamic inputs. Evidence strongly suggests that respiratory sinus arrhythmia both contributes to and buffers respiratory arterial pressure fluctuations. Moreover, even though virtual abolition of all R‐R interval variability by cholinergic blockade suggests that parasympathetic stimulation is essential for expression of these variabilities, respiratory sinus arrhythmia does not always reflect a purely vagal phenomenon. The arterial baroreflex has been cited as the mechanism for both respiratory and Mayer wave frequency fluctuations. However, data suggest that both cardiac vagal and vascular sympathetic fluctuations at these frequencies are independent of baroreflex mechanisms and, in fact, contribute to pressure fluctuations. Results from cardiovascular modelling can suggest possible sources for these rhythms. For example, modelling originally suggested low frequency cardiovascular rhythms derived from intrinsic delays in baroreceptor control, and experimental evidence subsequently corroborated this possibility. However, the complex stochastic relations between and variabilities in these rhythms indicate no single mechanism is responsible. If future study of cardiovascular variabilities is to move beyond qualitative suggestions of determinants to quantitative elucidation of critical physical mechanisms, both experimental design and model construction will have to be more trenchant.
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“Just as parasympathetic activation exerts profound influences on the LF component of HRV, sympathetic neural activity may modulate the HF component of the R–R interval variability (Taylor et al., 2001; Cohen and Taylor, 2002).”
BackgroundInfluentialThe physiological effects of slow breathing in the healthy human
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Metadata
- Authors
- Cohen, M. A., & Taylor, J. A.
- Venue
- The Journal of Physiology
- Publisher
- Wiley
- Published
- 2002-08
- Volume
- 542
- Issue
- 3
- Pages
- 669-683
- ISSN
- 0022-3751 (ISSN-L)
- 1469-7793
- OpenAlex
- W2050133849
- Cited by
- 362
- References
- 118
- FWCI
- 5.40
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.