DETECTION OF INTERACTIONS BETWEEN MYOGENIC AND TGF MECHANISMS USING NONLINEAR-ANALYSIS

Previous studies using linear techniques have provided valuable insigh ts into the dynamic characteristics of whole kidney autoregulation and have led to the general conclusion that the myogenic mechanism and tu buloglomerular feedback (TGF) are highly nonlinear control mechanisms. To explore further the dynamic nature of these nonlinear autoregulato ry mechanisms, we introduce the technique of nonlinear modeling using Volterra-Wiener kernels. In the past several years, use of Volterra-Wi ener kernels for nonlinear approximation has been most notably applied to neurophysiology. Recent advances in algorithms for computation of the kernels have made this technique more attractive for the study of the dynamics of nonlinear physiological systems, such as the system me diating renal autoregulation. In this study, the general theory and re quirements for using this technique are discussed. The feasibility of using the technique on whole kidney pressure and flow data is examined , and a basis for using the Volterra-Wiener kernels to detect interact ions between physiological control mechanisms is established. As a res ult of this method, we have identified the presence of interactions be tween the oscillating components of the myogenic and the TGF mechanism s at the level of the whole kidney blood flow in normotensive rats. An interaction between these oscillatory components had previously been demonstrated only at the single-nephron level.