Re-Parameterization the Logistic Model in Assessing Changes in the Baroreceptor Reflex

Chen, Shande; Shi, Xiangrong

doi:10.4236/nm.2011.22016

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…The use of a threshold and saturation and a second order system was essential for the implementation of the model as a relaxation oscillator. Thresholds and saturation have been a cornerstone of models of the baroreflex, which is a fundamental feedback circuit controlling BP (Chen and Kuo-Chu, 1991 ; Ottesen, 2000 ; Chen and Shi, 2011 ; Ottesen and Olufsen, 2011 ; Mahdi et al, 2013 ). Adding stochastic variations to the threshold in the feedback loop not only simulated the low frequency variations in systolic levels referred to as Mayer waves (Cheng et al, 2004 ; Julien, 2006 ), but also demonstrated that the model naturally implemented the Baroreceptor Sensitivity, which has been an important feature when describing cardiovascular regulation (Davos et al, 2002 ; La Rovere et al, 2008 ).…”

Section: Discussionmentioning

confidence: 99%

A Model of Blood Pressure, Heart Rate, and Vaso-Vagal Responses Produced by Vestibulo-Sympathetic Activation

et al. 2016

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Blood Pressure (BP), comprised of recurrent systoles and diastoles, is controlled by central mechanisms to maintain blood flow. Periodic behavior of BP was modeled to study how peak amplitudes and frequencies of the systoles are modulated by vestibular activation. The model was implemented as a relaxation oscillator, driven by a central signal related to Desired BP. Relaxation oscillations were maintained by a second order system comprising two integrators and a threshold element in the feedback loop. The output signal related to BP was generated as a nonlinear function of the derivative of the first state variable, which is a summation of an input related to Desired BP, feedback from the states, and an input from the vestibular system into one of the feedback loops. This nonlinear function was structured to best simulate the shapes of systoles and diastoles, the relationship between BP and Heart Rate (HR) as well as the amplitude modulations of BP and Pulse Pressure. Increases in threshold in one of the feedback loops produced lower frequencies of HR, but generated large pulse pressures to maintain orthostasis, without generating a VasoVagal Response (VVR). Pulse pressures were considerably smaller in the anesthetized rats than during the simulations, but simulated pulse pressures were lowered by including saturation in the feedback loop. Stochastic changes in threshold maintained the compensatory Baroreflex Sensitivity. Sudden decreases in Desired BP elicited non-compensatory VVRs with smaller pulse pressures, consistent with experimental data. The model suggests that the Vestibular Sympathetic Reflex (VSR) modulates BP and HR of an oscillating system by manipulating parameters of the baroreflex feedback and the signals that maintain the oscillations. It also shows that a VVR is generated when the vestibular input triggers a marked reduction in Desired BP.

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Section: Discussionmentioning

confidence: 99%

A Model of Blood Pressure, Heart Rate, and Vaso-Vagal Responses Produced by Vestibulo-Sympathetic Activation

et al. 2016

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“…The non-linear element ( f 1 , Figure 1 ), was modeled as piecewise linear with threshold, T , and saturation, S . This nonlinear feedback is responsible for making the system oscillate, mimics the non-linear feedback present in the baroreflex ( 28 , 29 ) and is a minimal structure for inducing relaxation oscillations ( 25 ). The realization of these integrators by central circuits is not known, but may be accomplished through functional commissural connections between neurons in the rostral ventrolateral medulla (RVLM) and those in the nucleus tractus solitarius NTS) ( 30 , 31 ).…”

Section: Resultsmentioning

confidence: 99%

“…The model was implemented as a state determined second order relaxation oscillator, whose oscillation characteristics are governed essentially by a threshold and saturation mechanism in the feedback loop and a driving signal that maintains the oscillations. The threshold non-linearity, which has been observed in the baroreflex feedback ( 28 , 29 , 49 ), puts the system into systolic or diastolic mode. The model was adapted from work done on modeling oculomotor oscillations during nystagmus ( 25 ) and repetitive motion of the legs during locomotion ( 50 , 51 ) where there are also oscillating fast and slow components of the stepping.…”

Section: Discussionmentioning

confidence: 99%

Predicting Vasovagal Responses: A Model-Based and Machine Learning Approach

Raphan

Yakushin

2021

Front. Neurol.

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Vasovagal syncope (VVS) or neurogenically induced fainting has resulted in falls, fractures, and death. Methods to deal with VVS are to use implanted pacemakers or beta blockers. These are often ineffective because the underlying changes in the cardiovascular system that lead to the syncope are incompletely understood and diagnosis of frequent occurrences of VVS is still based on history and a tilt test, in which subjects are passively tilted from a supine position to 20° from the spatial vertical (to a 70° position) on the tilt table and maintained in that orientation for 10–15 min. Recently, is has been shown that vasovagal responses (VVRs), which are characterized by transient drops in blood pressure (BP), heart rate (HR), and increased amplitude of low frequency oscillations in BP can be induced by sinusoidal galvanic vestibular stimulation (sGVS) and were similar to the low frequency oscillations that presaged VVS in humans. This transient drop in BP and HR of 25 mmHg and 25 beats per minute (bpm), respectively, were considered to be a VVR. Similar thresholds have been used to identify VVR's in human studies as well. However, this arbitrary threshold of identifying a VVR does not give a clear understanding of the identifying features of a VVR nor what triggers a VVR. In this study, we utilized our model of VVR generation together with a machine learning approach to learn a separating hyperplane between normal and VVR patterns. This methodology is proposed as a technique for more broadly identifying the features that trigger a VVR. If a similar feature identification could be associated with VVRs in humans, it potentially could be utilized to identify onset of a VVS, i.e, fainting, in real time.

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“…the maximal gain) and standard error were calculated as described previously. 37 The significance of the difference in the maximal gains of the active versus sedentary groups was determined using the z -statistics.…”

Section: Methodsmentioning

confidence: 99%

Habitual physical activity improves vagal cardiac modulation and carotid baroreflex function in elderly women

Cai

Wang

Kline

et al. 2023

Exp Biol Med (Maywood)

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The impact of habitual physical activity on vagal-cardiac function and baroreflex sensitivity in elderly women is poorly characterized. This study compared vagal-cardiac modulation and carotid baroreflex (CBR) function in eight physically active (67.6 ± 1.9 years; peak O2 uptake 29.1 ± 2.5 mL/min/kg) versus eight sedentary (67.3 ± 1.8 years; peak O2 uptake 18.6 ± 0.9 mL/min/kg) elderly women. Heart rate (HR) variabilities and maximal changes of HR and mean arterial pressure (MAP) elicited by 5-s pressure pulses between +40 and −80 mmHg applied to the carotid sinus were measured at rest and during carotid baroreceptor unloading effected by −15 mmHg lower-body negative pressure (LBNP). HR variability was greater in active than sedentary women in both low (0.998 ± 0.286 versus 0.255 ± 0.063 bpm2; P = 0.036) and high (0.895 ± 0.301 versus 0.156 ± 0.045 bpm2; P = 0.044) frequency domains. CBR-HR gains (bpm/mmHg) were greater (fitness factor P < 0.001) in active versus sedentary women at rest (−0.146 ± 0.014 versus −0.088 ± 0.011) and during LBNP (−0.105 ± 0.014 versus −0.065 ± 0.008). CBR-MAP gains (mmHg/mmHg) tended to be greater (fitness factor P = 0.077) in active versus sedentary women at rest (−0.132 ± 0.013 versus −0.110 ± 0.011) and during LBNP (−0.129 ± 0.015 versus −0.113 ± 0.013). However, LBNP did not potentiate CBR-MAP gains in either sedentary or active women (LBNP factor P = 0.94), and it depressed CBR-HR gains in both groups (LBNP factor P = 0.003). CBR-HR gains in the sedentary women did not differ (sex factor P = 0.65) from gains reported in age-matched sedentary men, although CBR-MAP gains tended to be greater (sex factor P = 0.109) in the men. Thus, tonic vagal modulation indicated by HR variability and dynamic vagal responses assessed by CBR-HR gain were augmented in physically active women. Enhanced vagal-cardiac function may protect against senescence-associated cardiac electrical and hemodynamic instability in elderly women.

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Re-Parameterization the Logistic Model in Assessing Changes in the Baroreceptor Reflex

Abstract: ABSTRACT

Cited by 6 publications

References 11 publications

A Model of Blood Pressure, Heart Rate, and Vaso-Vagal Responses Produced by Vestibulo-Sympathetic Activation

A Model of Blood Pressure, Heart Rate, and Vaso-Vagal Responses Produced by Vestibulo-Sympathetic Activation

Predicting Vasovagal Responses: A Model-Based and Machine Learning Approach

Habitual physical activity improves vagal cardiac modulation and carotid baroreflex function in elderly women

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