Abstract
Saleem S, Teal PD, Kleijn WB, Ainslie PN, Tzeng YC. Identification of human sympathetic neurovascular control using multivariate wavelet decomposition analysis. Am J Physiol Heart Circ Physiol 311: H837–H848, 2016. First published June 17, 2016; doi:10.1152/ajpheart.00254.2016.—The dynamic regulation of cerebral blood flow (CBF) is thought to involve myogenic and chemoreflex mechanisms, but the extent to which the sympathetic nervous system also plays a role remains debated. Here we sought to identify the role of human sympathetic neurovascular control by examining cerebral pressure-flow relations using linear transfer function analysis and multivariate wavelet decomposition analysis that explicitly accounts for the confounding effects of dynamic end-tidal P CO2 (P ETCO2 ) fluctuations. In 18 healthy participants randomly assigned to the 1 -adrenergic blockade group (n = 9; oral Prazosin, 0.05 mg/kg) or the placebo group (n = 9), we recorded blood pressure, middle cerebral blood flow velocity, and breath-to-breath P ETCO2 . Analyses showed that the placebo administration did not alter wavelet phase synchronization index (PSI) values, whereas sympathetic blockade increased PSI for frequency components ≤0.03 Hz. Additionally, three-way interaction effects were found for PSI change scores, indicating that the treatment response varied as a function of frequency and whether PSI values were P ETCO2 corrected. In contrast, sympathetic blockade did not affect any linear transfer function parameters. These data show that very-low-frequency CBF dynamics have a composite origin involving, not only nonlinear and nonstationary interactions between BP and P ETCO2 , but also frequencydependent interplay with the sympathetic nervous system.
Original language | English |
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Pages (from-to) | H837-H848 |
Journal | American Journal of Physiology - Heart and Circulatory Physiology |
Volume | 311 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Sep 2016 |
Keywords
- Cerebral blood flow
- Cerebral hemodynamics
- Mathematical modeling
- Receptors
- Sympathetic nervous system