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Nonlinear Identification of the Total Baroreflex Arc
Author(s) -
Moslehpour Mohsen,
Kawada Toru,
Sunagawa Kenji,
Sugimachi Masaru,
Mukkamala Ramakrishna
Publication year - 2015
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.29.1_supplement.648.4
Subject(s) - carotid sinus , baroreflex , nonlinear system , control theory (sociology) , baroreceptor , linear model , system identification , arc (geometry) , mathematics , physics , anesthesia , medicine , computer science , blood pressure , reflex , statistics , heart rate , data modeling , artificial intelligence , geometry , control (management) , quantum mechanics , database
The total baroreflex arc – the open‐loop system relating carotid sinus pressure (CSP) to arterial pressure (AP) – exhibits nonlinear behaviors such as saturation, thresholding, and steady‐state responses to pulsatile changes. However, few studies have quantitatively characterized the nonlinear system dynamics. The aim was to develop a nonlinear dynamic model of the total baroreflex arc. Five normal rats were studied according to a protocol approved by the Animal Subjects Committee of the National Cerebral and Cardiovascular Center. Under anesthesia, the vagal and aortic arch depressor nerves were sectioned; the carotid sinus regions were isolated and attached to a servo‐controlled piston pump; and AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second‐order Volterra model was established using nonparametric identification. The second‐order kernel was mainly diagonal, but the main diagonal was not the same as the first‐order kernel. A simplified second‐order nonlinear model was accordingly developed using nonparametric identification. This model predicted AP changes 15% better than a linear model in response to Gaussian white noise CSP data not used in model development. Linear and nonlinear models of the neural arc – the system relating CSP to SNA – and peripheral arc – the system relating SNA to AP – were likewise established. These two models indicated that the nonlinearity of the total baroreflex arc mainly arises from the neural arc rather than the peripheral arc.