Low-frequency renal sympathetic nerve activity, arterial BP, stationary "1/f noise," and the baroreflex

Citation
De. Burgess et al., Low-frequency renal sympathetic nerve activity, arterial BP, stationary "1/f noise," and the baroreflex, AM J P-REG, 46(3), 1999, pp. R894-R903
Citations number
24
Categorie Soggetti
Physiology
Journal title
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY
ISSN journal
03636119 → ACNP
Volume
46
Issue
3
Year of publication
1999
Pages
R894 - R903
Database
ISI
SICI code
0363-6119(199909)46:3<R894:LRSNAA>2.0.ZU;2-#
Abstract
The object of this study is to quantify the very low frequency (i.e., <0.1 Hz) interactions between renal sympathetic nerve activity (SNA) and arteria l blood pressure (ABP). Six rats were instrumented for chronic recordings o f SNA and ABP. Data were collected 24 h after surgery at 10 kHz for 2-5 h a nd subsequently compressed to a 1-kHz signal. The power spectra and ordinar y coherence were calculated from data epochs up to Ih in length. The very l ow frequency spectra for both variables were fitted to a constant times f(- beta). The peak magnitude squared of the coherence near 0.4 Hz was 0.82 +/- 0.08, but the apparent linear coherence fell off quickly at lower frequenc ies so that it was close to zero for frequencies <0.1 Hz. Moreover, at thes e low frequencies beta, as computed by a coarse grain spectral analysis, wa s significantly (P < 0.01) different for SNA (0.66 +/- 0.12) and ABP (1.12 +/- 0.14). Assuming that SNA and ABP are stationary time series, the result s of our classical spectral analysis would indicate that SNA and ABP are no t linearly correlated at frequencies with a period more than similar to 10 s. Accordingly, we tested for stationarity by computing the spectral cohere nce and found that SNA and ABP are not stationary "1/f noise" within the fr equency range from 0.02 to 2.0 Hz. Rather the SNA exerts control over the c ardiovascular system through intermittent bursts of activity. Such intermit tent behavior can be modeled by nonlinear dynamics.