Time–frequency analysis of the baroreflex control of renal sympathetic nerve activity in the rat

• Published in: Journal of neuroscience methods Vol. 198; no. 2; pp. 336 - 343
• Main Authors: Gallet, Clément, Chapuis, Bruno, Barrès, Christian, Julien, Claude
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.06.2011
• Subjects: Animals; Baroreflex - physiology; Blood Pressure - physiology; Empirical mode decompositionm; Heart Rate - physiology; Kidney - innervation; Kidney - physiology; Rats; Rats, Sprague-Dawley; Sympathetic baroreflex; Sympathetic Nervous System - physiology; Transfer function; Wavelet Analysis; Wavelet transform; Empirical mode decompositionm; Sympathetic baroreflex; Wavelet transform; Transfer function
• ISSN: 0165-0270; 1872-678X; 1872-678X
• DOI: 10.1016/j.jneumeth.2011.04.009

► Sympathetic baroreflex sensitivity is estimated in rats using time–frequency methods. ► It reveals fast spontaneous fluctuations of the baroreflex sensitivity. ► These fluctuations are strongly reduced by urethane anaesthesia. Cross-spectral analysis using the short-time Fourier transform (STFT) allows estimating the transfer function between spontaneous fluctuations of arterial pressure (AP) and renal sympathetic nerve activity (RSNA) at the heart rate (HR) frequency, which provides an index of sympathetic baroreflex sensitivity (sBRS) in rats. The method, however, cannot reliably compute more than one value per min. The goal of the present study was to achieve a better temporal resolution by using advanced methods. The first method is the continuous wavelet transform (CWT) using the Morlet wavelet. The second method is based on the empirical mode decomposition (EMD), a method that decomposes a signal into a sum of oscillating components. Using both methods, the transfer function was estimated over periods of 10 s. The two methods, together with STFT, were applied to AP and RSNA signals that were simultaneously recorded in conscious, freely behaving rats ( n = 10) during 1 h. When considering 1-h mean sBRS values obtained in each rat, both methods showed a strong correlation with STFT ( R = 0.96 and 0.91 for CWT and EMD, respectively, both P < 0.001). In each rat, sBRS values obtained by the CWT and EMD methods were tightly correlated ( R = 0.93 ± 0.01, n = 294 ± 13, P < 0.001). With both methods, high-frequency variations of sBRS (0.0083–0.5 Hz) accounted for about 40% of its overall variability. In urethane-anaesthetized rats ( n = 9), sBRS variability computed by either method was reduced by about two-thirds ( P < 0.001). Improving temporal resolution of sBRS computation reveals that in rats, sBRS exhibits fast, short-lasting fluctuations. These fluctuations largely depend on the state of vigilance.