A Model for the Genesis of Arterial Pressure Mayer Waves from Heart Rate and Sympathetic Activity

Both theoretic models and cross-spectral analyses suggest that an oscillating sympathetic nervous outflow generates the low frequency arterial pressure fluctuations termed Mayer waves. Fluctuations in heart rate also have been suggested to relate closely to Mayer waves, but empiric models have not assessed the joint causative influences of hemt rate and sympathetic activity. Therefore, we constructed a model based simply upon the hemodynamic equation deriving from Ohm's Law. With this model, we determined time relations and relative contributions of heart rate and sympathetic activity to the genesis of arterial pressure Mayer waves. We assessed data from eight healthy young volunteers in the basal state and in a high sympathetic state known to produce concurrent increases in sympathetic nervous outflow and Mayer wave amplitude. We fit the Mayer waves (0.05-0.20 Hz) in mean arterial pressure by the weighted sum ofleading oscillations in heart rate and sympathetic nerve activity. This model of our data showed heart rate oscillations leading by 2-3.75 seconds were responsible for almost half of the variance in arterial pressure (basal R^2=0.435±0.140, high sympathetic R^2=0.438±0.180). Surprisingly, sympathetic activity (lead 0-5 seconds) contributed only modestly to the explained variance in Mayer waves during either sympathetic state (basal: ∆R^2=0.046±0.026; heightened: ∆R^2=0.085±0.036). Thus, it appears that heart rate oscillations contribute to Mayer waves in a simple linear fashion, whereas sympathetic fluctuations contribute little to Mayer waves in this way. Although these results do not exclude an important vascular sympathetic role, they do suggest that additional Ji1ctors, such as sympathetic transduction into vascular resistance, modulate its influence.Binda and Fred Shuman Foundation; National Institute on Aging (AG14376)

A Model for the Genesis of Arterial Pressure Mayer Waves from Heart Rate and Sympathetic Activity

Both theoretic models and cross-spectral analyses suggest that an oscillating sympathetic nervous outflow generates the low frequency arterial pressure fluctuations termed Mayer waves. Fluctuations in heart rate also have been suggested to relate closely to Mayer waves, but empiric models have not assessed the joint causative influences of hemt rate and sympathetic activity. Therefore, we constructed a model based simply upon the hemodynamic equation deriving from Ohm's Law. With this model, we determined time relations and relative contributions of heart rate and sympathetic activity to the genesis of arterial pressure Mayer waves. We assessed data from eight healthy young volunteers in the basal state and in a high sympathetic state known to produce concurrent increases in sympathetic nervous outflow and Mayer wave amplitude. We fit the Mayer waves (0.05-0.20 Hz) in mean arterial pressure by the weighted sum ofleading oscillations in heart rate and sympathetic nerve activity. This model of our data showed heart rate oscillations leading by 2-3.75 seconds were responsible for almost half of the variance in arterial pressure (basal R^2=0.435±0.140, high sympathetic R^2=0.438±0.180). Surprisingly, sympathetic activity (lead 0-5 seconds) contributed only modestly to the explained variance in Mayer waves during either sympathetic state (basal: ∆R^2=0.046±0.026; heightened: ∆R^2=0.085±0.036). Thus, it appears that heart rate oscillations contribute to Mayer waves in a simple linear fashion, whereas sympathetic fluctuations contribute little to Mayer waves in this way. Although these results do not exclude an important vascular sympathetic role, they do suggest that additional Ji1ctors, such as sympathetic transduction into vascular resistance, modulate its influence.Binda and Fred Shuman Foundation; National Institute on Aging (AG14376)

A delay recruitment model of the cardiovascular control system.

Copyright will be owned by Springer. We develop a nonlinear delay-differential equation for the human cardiovascular control system, and use it to explore blood pressure and heart rate variability under short-term baroreflex control. The model incorporates an intrinsically stable heart rate in the absence of nervous control, and features baroreflex influence on both heart rate and peripheral resistance. Analytical simplifications of the model allow a general investigation of the rôles played by gain and delay, and the effects of ageing.

Анализ взаимосвязи между центральной нервной и сердечно-сосудистой системами

В роботі розглянуто взаємозв’язок між центральною нервовою та серцево-судинними системами. Описані існуючі методи оцінки зв’язку між сигналами варіабельності серцевого ритму і електроенцефалограми людини: кореляція, когерентність, взаємна інформація, ентропія передачі, ймовірність синхронізації. Найбільш перспективними напрямами визнано дослідження нелінійного взаємозв’язку між розглянутими системами, розгляд методів оцінки нелінійного зв’язку між сигналами ЕЕГ та сигналами варіабельності серцевого ритму та їх порівняння. Визначені шляхи покращення існуючих підходів до даної задачі та напрямки подальших досліджень.In the paper the aspects of collaboration and interconnection between central nervous and cardiovascular systems are described. Existing methods to estimate the connectivity between HRV and EEG signals and corresponding up-to-date studies are reviewed. It can be affirmed that there is an apparent interconnection between central nervous and cardiovascular systems on the basis of examined papers. But the definite method of assessment of this interconnection capable to take into account the underlying manner of this connection is yet to be defined. It was determined that further research should be directed into examination of non-linear connectivity between HRV and EEG signals, methods for non-linear connectivity assessment and comparison of their performance. On this basis the new ways to improve the current approaches are expounded.В работе рассмотрена взаимосвязь между центральной нервной и сердечно-сосудистой системой. Описаны существующие методы оценки связи между сигналами вариабельности сердечного ритма и электроэнцефалограммы человека: корреляция, когерентность, взаимная информация, энтропия передачи, вероятность синхронизации. Установлены наиболее перспективные направления исследований: определение нелинейной взаимосвязи между рассмотренными системами, рассмотрение методов оценки нелинейной связи межу сигналами ЭЭГ и сигналами вариабельности сердечного ритма и их сравнение. Обозначены пути улучшения существующих подходов к данной задаче и направления последующих исследований

The role of the central chemoreceptor in causing periodic breathing.

In a previous publication (Fowler et aL, 1993), we reduced the classical cardiorespiratory control model of (Grodins et aL, 1967) to a much simpler form, which we then used to study the phenomenon of periodic breathing. In particular, cardiac output was assumed constant, and a single (constant) delay representing arterial blood transport time between lung and brain was included in the model. In this paper we extend this earlier work, both by allowing for the variability in transport delays, due to the dependence of cardiac output on blood gas concentrations, and also by including further delays in the system. In addition, we extensively discuss the physiological implications of parameter variations in the model; several novel mechanisms for periodic breathing in clinical situations are proposed. The results are discussed in the light of recent observational studies. Keywords: Periodic breathing; Cheyne-Stokes respiration; heart-rate variability*, differential-delay equations. 1

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales