Nonlinear identification of the total baroreflex arc

Area of Science:

• Physiology
• Biomedical Engineering
• Systems Biology

Background:

• The total baroreflex arc, relating carotid sinus pressure (CSP) to arterial pressure (AP), exhibits known nonlinear behaviors.
• Quantitative characterization of these nonlinear dynamics remains limited.

Purpose of the Study:

• To develop a nonlinear model of the sympathetically mediated total baroreflex arc without pre-assuming a model form.
• To quantitatively characterize the nonlinear dynamics of the baroreflex arc.

Main Methods:

• Nonparametric identification using a second-order Volterra model applied to measurements from anesthetized rats.
• Carotid sinus pressure (CSP) was perturbed with Gaussian white noise, while arterial pressure (AP) and sympathetic nerve activity (SNA) were measured.
• A reduced second-order Uryson model was developed and compared to a linear model.

Main Results:

• The developed Uryson model predicted AP changes 12% better than a linear model (P < 0.01) in response to new CSP perturbations.
• The nonlinear model successfully predicted thresholding and mean responses to CSP variations.
• Models of the neural and peripheral arcs, representing subsystems, showed predominantly linear behaviors.

Conclusions:

• The validated nonlinear Uryson model reveals the total baroreflex arc possesses a Uryson structure.
• Nonlinearity is a significant characteristic of the total baroreflex arc, primarily residing in the overall system rather than its subsystems.