I. Patterns of Innervation of Renal Neuroeffectors One pattern is a single renal sympathetic nerve fiber making contact with each of the 3 neuroeffectors. This suggests that each effector possesses response characteristics enabling it to respond to effector-specific information encoded in the RSNA signal. The other pattern is a selective and specific single renal sympathetic nerve fibers making contact with 1 neuroeffector but not the other 2, functionally specific renal sympathetic nerve fibers. This suggests that unique fibers are coupled to separate central sites with specific and selective afferent inputs. Renal sympathetic nerve fibers show a bimodal distribution of diameters. The strength duration curves for the antidiuretic and renal vasoconstrictor responses have different rheobase and chronaxie values, indicating they are different fiber populations. Single fiber analysis discloses a heterogeneous response to many afferent inputs supporting the existence of functionally specific renal sympathetic nerve fibers. II. Importance of Dynamic Information Encoded in RSNA Renal nerves were stimulated with a square wave or diamond wave stimulation pattern, matched for integrated voltage and peak amplitude. Diamond wave pattern produced greater renal vasoconstrictor response. When 2 stimuli were matched for intensity that was subthreshold for renal vasoconstriction, only diamond wave pattern decreased UNaV. Two reflex stimuli, peripheral thermal stimulation (heat) and tail pinch, while eliciting same increase in total integrated RSNA voltage, produced different effects on RBF. Heat produced greater decrease in RBF and greater increase in renal vascular resistance. Power spectral and transfer function analysis disclosed additional oscillations in RSNA signal during heat (not present in tail pinch) that were transferred into RBF signal; they were absent following renal denervation indicating their derivation from RSNA. Renal vasculature acts as a low pass filter (i.e. renal vascular frequency response), passing oscillations at frequencies 〈 0.4 Hz without significant attenuation but progressively attenuating (filtering out) oscillations at frequencies 〉 0.4 Hz. III. Dynamic Role of Subvasoconstrictor versus Vasoconstrictor Intensities of RSNA Using rat models with subvasoconstrictor (control, WKY) and vasoconstrictor (congestive heart failure, CHF; SHR) intensities of RSNA, effect of renal denervation (DNX) on dynamic autoregulation of RBF and spontaneous variability of RBF was examined. DNX did not affect basal RBF, dynamic autoregulation of RBF and spontaneous variability of RBF in control and WKY. In CHF and SHR, DNX significantly increased basal RBF, significantly improved abnormal dynamic autoregulation of RBF toward normal and significantly increased spontaneous variability of RBF. Vasoconstrictor intensities of RSNA: (a) impair the dynamic coupling (coherence) between AP and RBF; (b) minimize spontaneous variability of RBF (i.e. improve stability) which may contribute to stability of GFR. IV. Dynamic Effects of Angiotensin II This was studied in CHF rats who have increased activity of the renin-angiotensin system (and increased RSNA) with increased circulating plasma angiotensin II concentration (ang II) and in normal rats fed low, normal and high dietary sodium to produce physiological changes in ang II. Losartan was used to assess role of ang II acting on AT1 receptors. In low dietary sodium rats (not normal or high), physiological elevations in circulating ang II impaired renal vascular frequency response but had a selective effect to enhance slower tubuloglomerular feedback component (but not myogenic component) of dynamic RBF autoregulation. In CHF rats, the pathophysiological elevations in ang II impaired both renal vascular frequency response and dynamic RBF autoregulation. These changes are functional (losartan reversible) occurring at interface between renal sympathetic nerve terminals and renal resistance vasculature. V. Dynamic Models of Renal Blood Flow RBF can be modeled as single output of a system with 2 inputs, arterial pressure (AP) and RSNA, considered separately or combined. To assess role of RSNA in modeling process, RBF was modeled as single output of a system using single input of AP before and after DNX. DNX did not affect ability to model RBF from AP in rats with subvasoconstrictor intensities of RSNA (WKY) and significantly improved it in rats with vasoconstrictor intensities of RSNA (SHR). In comparing modeling efficacy using 2 inputs separately or combined, RSNA or AP&RNSA was no better than AP alone in WKY. In SHR, RSNA was worse than AP and AP&RSNA was still less efficacious than AP alone.