Frequency domain characteristics of muscle sympathetic nerve activity in heart failure and healthy humans

Ando, Shin-ichi; Dajani, Hilmi R.; Floras, John S.

doi:10.1152/ajpregu.1997.273.1.r205

Cited by 68 publications

(98 citation statements)

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“…This approach relies on the assumption that a certain frequency band of HR variability, between 0.04 and 0.35 Hz (18), is modulated by the baroreflex. This construct is based on the coherent relationship between SBP and R-R (or MSNA), each of which oscillate at the same frequency in the power spectrum (2,13,85). Baroreflex sensitivity is expressed by the gain of the transfer function relating changes in blood pressure to coherent changes in R-R or MSNA (2,87,99).…”

Section: Physiology Of the Baroreflex And Methods To Explore Its Funcmentioning

confidence: 99%

“…48, 66), current evidence suggests that the baroreflex contributes substantially to LF oscillations in blood pressure, R-R interval, and MSNA variability (2,13,18,20,108). LF oscillation in the R-R interval has been related to cardiac sympathetic modulation resulting from the baroreflex response to the LF blood pressure oscillations (feedback theory) (108).…”

Section: Arterial Baroreflex and Cardiovascular Variabilitymentioning

confidence: 98%

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Arterial baroreflex function and cardiovascular variability: interactions and implications

Lanfranchi

Somers

2002

American Journal of Physiology-Regulatory, Integrative and Comp

257

183

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The arterial baroreflex contributes importantly to the short-term regulation of blood pressure and cardiovascular variability. A number of factors (including reflex, humoral, behavioral, and environmental) may influence gain and effectiveness of the baroreflex, as well as cardiovascular variability. Many central neural structures are also involved in the regulation of the cardiovascular system and contribute to the integrity of the baroreflex. Consequently, brain injuries or ischemia may induce baroreflex impairment and deranged cardiovascular variability. Baroreflex dysfunction and deranged cardiovascular variability are also common findings in cardiovascular disease. A blunted baroreflex gain and impaired heart rate variability are predictive of poor outcome in patients with heart failure and myocardial infarction and may represent an early index of autonomic activation in left ventricular dysfunction. The mechanisms mediating these relationships are not well understood and may in part be the result of cardiac structural changes and/or altered central neural processing of baroreflex signals.

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Section: Physiology Of the Baroreflex And Methods To Explore Its Funcmentioning

confidence: 99%

Section: Arterial Baroreflex and Cardiovascular Variabilitymentioning

confidence: 98%

Arterial baroreflex function and cardiovascular variability: interactions and implications

Lanfranchi

Somers

2002

American Journal of Physiology-Regulatory, Integrative and Comp

257

183

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“…Note that this representation is separate from the negative feedback (Ϫ1) effect, accounting for the "for- 1 This is clearly not the case in all situations, see Limitations. ward" S shape, as opposed to the more familiar reverse S seen more commonly in the baroreflex literature.…”

Section: A Nonlinear Feedback Modelmentioning

confidence: 96%

“…Experiments in a variety of animal models have shown that this oscillation is due to the action of the sympathetic nervous system on the vasculature. Although the oscillation in blood pressure is shifted to 0.4 Hz in the rat (7) and to 0.3 Hz in the rabbit (22), changes in the strength of this oscillation have been proposed to reflect changes in the mean level of sympathetic nerve activity (SNA) and/or baroreflex gain (6), raising the possibility that measurement of the strength of this oscillation may be used as a diagnostic measure of neural control of the cardiovascular system in humans (1,10,26).Current evidence favors the concept of feedback in the baroreflex loop as the origin for the 0.1-Hz oscillation in blood pressure (5,6,13,25,41). In this model, a change in blood pressure is sensed by the arterial baroreceptors altering the afferent signal to the central nervous system (CNS) and subsequently the mean SNA level, which, in turn, alters vascular tone in the target organ.…”

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confidence: 99%

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confidence: 99%

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Slow oscillations in blood pressure via a nonlinear feedback model

Ringwood

Malpas

2001

American Journal of Physiology-Regulatory, Integrative and Comp

101

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Ringwood, John V., and Simon C. Malpas. Slow oscillations in blood pressure via a nonlinear feedback model. Am J Physiol Regulatory Integrative Comp Physiol 280: R1105-R1115, 2001.-Blood pressure is well established to contain a potential oscillation between 0.1 and 0.4 Hz, which is proposed to reflect resonant feedback in the baroreflex loop. A linear feedback model, comprising delay and lag terms for the vasculature, and a linear proportional derivative controller have been proposed to account for the 0.4-Hz oscillation in blood pressure in rats. However, although this model can produce oscillations at the required frequency, some strict relationships between the controller and vasculature parameters must be true for the oscillations to be stable. We developed a nonlinear model, containing an amplitude-limiting nonlinearity that allows for similar oscillations under a very mild set of assumptions. Models constructed from arterial pressure and sympathetic nerve activity recordings obtained from conscious rabbits under resting conditions suggest that the nonlinearity in the feedback loop is not contained within the vasculature, but rather is confined to the central nervous system. The advantage of the model is that it provides for sustained stable oscillations under a wide variety of situations even where gain at various points along the feedback loop may be altered, a situation that is not possible with a linear feedback model. Our model shows how variations in some of the nonlinearity characteristics can account for growth or decay in the oscillations and situations where the oscillations can disappear altogether. Such variations are shown to accord well with observed experimental data. Additionally, using a nonlinear feedback model, it is straightforward to show that the variation in frequency of the oscillations in blood pressure in rats (0.4 Hz), rabbits (0.3 Hz), and humans (0.1 Hz) is primarily due to scaling effects of conduction times between species. sympathetic nervous system; baroreflex; stability; describing function; artificial neural network IT IS WELL ESTABLISHED that blood pressure in humans can contain a distinct oscillation at 0.1 Hz, often referred to as the Mayer wave (26,38). Experiments in a variety of animal models have shown that this oscillation is due to the action of the sympathetic nervous system on the vasculature. Although the oscillation in blood pressure is shifted to 0.4 Hz in the rat (7) and to 0.3 Hz in the rabbit (22), changes in the strength of this oscillation have been proposed to reflect changes in the mean level of sympathetic nerve activity (SNA) and/or baroreflex gain (6), raising the possibility that measurement of the strength of this oscillation may be used as a diagnostic measure of neural control of the cardiovascular system in humans (1,10,26).Current evidence favors the concept of feedback in the baroreflex loop as the origin for the 0.1-Hz oscillation in blood pressure (5,6,13,25,41). In this model, a change in blood pressure is sensed by the arterial barorece...

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Reliability of transfer function estimates in cardiovascular variability analysis

Pinna¹,

Maestri²

2001

Med. Biol. Eng. Comput.

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Transfer function (TF) analysis is a widely diffused technique in the assessment of the relationship between short-term cardiovascular variability signals, particularly blood pressure, heart rate and respiration. To guarantee the reliability of the estimates, a conventional threshold of 0.5 on the magnitude squared coherence (MSC) is commonly used, although (i) other analysis parameters play a role and (ii) lower values of MSC are frequently unavoidable in physiological systems. In this study, computer simulations are performed to assess the dependency of the bias and standard deviation (SD) of TF estimates on record length (RL), spectral window bandwidth (Bw) and MSC; to evaluate the accuracy of theoretical expressions for the computation of the confidence interval (CI) of the estimates; and to assess, in some representative situations, how faithfully observed TF shapes reproduce the underlying true functions in conditions of very low MSC. The accuracy of TF estimates increases non-linearly with increasing RL, and the benefit over 7 min is small. Using this RL, the relative bias for the TF modulus is < 10% for MSC > 0.2. Estimates of TF phase are unbiased. The SD of both the modulus and phase increases linearly as the MSC decrease to 0.4 and then, for lower MSC, increases markedly with nonlinear behaviour. Bw= 0.03Hz appears to be most suitable to reduce the error, preserving spectral resolution. CIs for the TF phase are highly reliable, whereas those for the modulus tend to be slightly narrower than the nominal value at high coherence values. Major features of the TF shape appear to be preserved in simulations with very low MSC. The major problem in TF estimation is the sharp increase in the variability of the measurements as the coherence decreases towards the lowest values. The combination of RL > or = 420s and Bw= 0.03Hz should be suggested in short-term cardiovascular variability studies. Although basic features of the true TF can be recovered even when the MSC is < 0.5, much greater values can be necessary when accurate point estimates are needed. Theoretical expressions for the computation of confidence intervals of the TF are adequate for practical purposes.

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Frequency domain characteristics of muscle sympathetic nerve activity in heart failure and healthy humans

Cited by 68 publications

References 0 publications

Arterial baroreflex function and cardiovascular variability: interactions and implications

Arterial baroreflex function and cardiovascular variability: interactions and implications

Slow oscillations in blood pressure via a nonlinear feedback model

Reliability of transfer function estimates in cardiovascular variability analysis

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