Nonlinear identification of the total baroreflex arc.
The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This "Uryson" model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure.
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan;
Mohsen
M
Moslehpour
Department of Cardiovascular Dynamics, National Cerebral and Cardiovascular Center, Osaka, Japan; and.
Toru
T
Kawada
Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kenji
K
Sunagawa
Department of Cardiovascular Dynamics, National Cerebral and Cardiovascular Center, Osaka, Japan; and.
Masaru
M
Sugimachi
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan; rama@egr.msu.edu.
Ramakrishna
R
Mukkamala
D000818:Animals; D062186:Arterial Pressure; D017704:Baroreflex; D002346:Carotid Sinus / Q000294:innervation*; D016014:Linear Models; D040542:Mechanotransduction, Cellular; D023421:Models, Animal; D008955:Models, Cardiovascular; D017711:Nonlinear Dynamics; D011311:Pressoreceptors / Q000502:physiology*; D011921:Rats, Inbred WKY; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D018709:Statistics, Nonparametric; D013997:Time Factors; D014160:Transducers, Pressure
Gaussian white noise; Volterra model; arterial baroreflex; nonparametric system identification; sympathetic nervous system