Key result
Linear and nonlinear systems analyses using a white noise approach reveal that the neural arc of the carotid sinus baroreflex exhibits derivative characteristics while the peripheral arc exhibits low-pass characteristics.
Why the study?
Dynamic nonlinearities of the arterial baroreflex system are less understood, which is relevant for device-based cardiovascular therapies targeting sympathetic hyperactivity.
Mathematical modeling and systems analysis of the arterial baroreflex in animal models reveal how the neural and peripheral arcs interact to optimize blood pressure regulation, providing foundational knowledge for potential device-based autonomic therapies.
Animal baroreflex analysis reveals complementary neural-peripheral dynamics; leaves open translation to human device therapies.
The arterial baroreflex system is an important negative feedback system that controls arterial pressure (AP) within a normal range during daily activities. We have analyzed this system in anesthetized animals. Several issues need to be considered: the presence of physiological and measurement noises that interfere with the system identification, the closed-loop nature of the arterial baroreflex system, the existence of parallel feedback systems that may modify the system responses, and the presence of nonlinear responses. We opened the negative feedback loop by surgically isolating the carotid sinus baroreceptor regions from the systemic circulation. We eliminated the effects from parallel feedback systems by sectioning the aortic depressor and vagal nerves. We used a white noise approach to estimate the system characteristics under contamination of physiological and measurement noises. The arterial baroreflex system may be divided into the neural and peripheral arc subsystems. The neural arc represents the relationship between pressure inputs and efferent sympathetic nerve activity (SNA), which may be regarded as a controller subsystem. The peripheral arc represents the relationship between SNA and AP, which may be regarded as a plant subsystem. The neural arc reveals derivative characteristics whereas the peripheral arc reveals low-pass characteristics. Numerical simulations based on the analytical results indicate that the neural arc compensates for the slow peripheral arc to optimize the arterial baroreflex system in achieving both stability and quickness. Impairment of arterial baroreflex function is associated with cardiovascular diseases, and artificial activation of the arterial baroreflex system could be a device-based treatment for cardiovascular diseases associated with sympathetic hyperactivity. To improve the efficacy of such device-based therapy, we may need to understand the interactions between stimulated and non-stimulated baroreflex systems. Although static sigmoidal nonlinearity of the arterial baroreflex with threshold and saturation phenomena is well documented, dynamic nonlinearities are less understood. Further efforts are warranted to fully understand arterial baroreflex function and to apply the knowledge to the medical field.
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Kawada et al. (2019) conducted a review in Baroreflex dynamic characteristics. White noise approach for system identification was evaluated. Linear and nonlinear systems analyses using a white noise approach reveal that the neural arc of the carotid sinus baroreflex exhibits derivative characteristics while the peripheral arc exhibits low-pass characteristics.
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