Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis

K. H. Chon, Y. M. Chen, V. Z. Marmarelis, D. J. Marsh and N. H. Holstein-Rathlou Department of Biomedical Engineering, University of Southern California, Los Angeles 90033. Previous studies using linear techniques have provided valuable insights into the dynamic characteristics of whole kidney autoregulation and have led to the general conclusion that the myogenic mechanism and tubuloglomerular feedback (TGF) are highly nonlinear control mechanisms. To explore further the dynamic nature of these nonlinear autoregulatory mechanisms, we introduce the technique of nonlinear modeling using Volterra-Wiener kernels. In the past several years, use of Volterra-Wiener 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 mediating renal autoregulation. In this study, the general theory and requirements 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 interactions between physiological control mechanisms is established. As a result of this method, we have identified the presence of interactions between the oscillating components of the myogenic and the TGF mechanisms 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.