In this study we employed both detrended fluctuation analysis [1] (DFA) and multiscale entropy [2] (MSE) measurements to assess the long-range temporal correlation (LRTC) of multifibre renal sympathetic nerve activity (RSNA) signals in conscious (n=10) and anaesthetized Wistar rats (n=10, anaesthetized with a mixture of urethane/chloralose, 650 mg kg^-1/50 mg kg^-1, respectively). The left kidney was exposed retroperitoneally and a branch of the nerve to the kidney was placed on a bipolar electrode. Neural signals were amplified, filtered, digitized with a sampling frequency of 1 KHz and displayed on an oscilloscope and stored for later analysis. The neural signals were sampled for 164 s. Data are expressed as mean ± S.E.M., and analysed using repeated measures ANOVA. Statistical differences were considered significant when p<0.05. For details of preparation, and conditions of recording in conscious animals see Huang et al. (2006). It was found that a clear power-law scaling relationship is detected for the RSNA with the scaling exponent of 0.612; however, the shuffled RSNA with the scaling exponent of 0.501 deviated sharply from the original scaling profiles. Furthermore, the shuffled RSNA produced less complex MSE values compared to that of the original, which suggested that the MSE profiles for the shuffled sequence were qualitative similar to that of an uncorrelated process. The scaling exponent of the RSNA in conscious rats was significantly higher than that of the RSNA in anaesthetized rats (0.615±0.018 vs 0.529±0.019, P<0.001), indicating the reduction of LRTC in the anaesthetized condition. The results of MSE analysis of RSNA demonstrated that the entropy values, derived from the conscious group, increased on small time scales and then stabilized to a relatively constant value, however, the entropy measure, derived from animals with anaesthesia, almost monotonically decreased. We conclude that unlike existing approaches that require the multifibre RSNA to be stationary, DFA provides a simple quantitative parameter to represent the characterization of LRTC embedded in non-stationary RSNA time series. The present study shows that while LRTC in the temporal dynamics of energy fluctuations of RSNA does not implicate a unique mechanism, the data for the first time provide evidence of much less temporal correlation in anaesthetized condition. This suggests the LRTC of underlying dynamics of the system has been effectively eliminated by anaesthesia. These results demonstrate that apparently random fluctuations in multifibre RSNA are dictated by a complex deterministic process that imparts “long-term” memory to the dynamic system. However, this ‘memory’ is significantly weakened by anesthesia.