Calibrated variability of muscle sympathetic nerve activity during graded head-up tilt in humans and its link with noradrenaline data and cardiovascular rhythms

Abstract

Muscle sympathetic nerve activity (MSNA) variability is traditionally computed through a low-pass filtering procedure that requires normalization. We proposed a new beat-to-beat MSNA variability computation that preserves dimensionality typical of an integrated neural discharge (i.e., bursts per unit of time). The calibrated MSNA (cMSNA) variability technique is contrasted with the traditional uncalibrated MSNA (ucMSNA) version. The powers of cMSNA and ucMSNA variabilities in the low-frequency (LF, from 0.04 to 0.15 Hz) band were computed with those of the heart period (HP) of systolic and diastolic arterial pressure (SAP and DAP, respectively) in seven healthy subjects (age, 20-28 years; median, 22 years; 5 women) during a graded head-up tilt. Subjects were sequentially tilted at 0°, 20°, 30°, 40°, and 60° table inclinations. The LF powers of ucMSNA and HP variabilities were expressed in normalized units (LFnu), whereas all remaining spectral markers were expressed in absolute units. We found that 1) the LF power of cMSNA variability was positively correlated with tilt angle, whereas the LFnu power of the ucMSNA series was uncorrelated; 2) the LF power of cMSNA variability was correlated with LF powers of SAP and DAP, LFnu power of HP and noradrenaline concentration, whereas the relationship of the LFnu power of ucMSNA variability to LF powers of SAP and DAP was weaker and that to LFnu power of HP was absent; and 3) the stronger relationship of cMSNA variability to SAP and DAP spectral markers compared with the ucMSNA series was confirmed individually. The cMSNA variability appears to be more suitable in describing sympathetic control in humans than traditional ucMSNA variability.

Physiological Mechanisms Mediating the Coupling between Heart Period and Arterial Pressure in Response to Postural Changes in Humans

“…We found that SAP-LFSD significantly increased during HUTT (Table 1, Figure 2E) and also in the seated and active standing positions (Figure 4B) compared to baseline recordings in the supine position, in line with a previous reports (Veerman et al, 1994; Barnett et al, 1999; Cooke et al, 1999; Marchi et al, 2016). On the other hand, we found that SAP-LFSD increased more modestly if at all in the supine position after blood loss (Figure 6B).…”

Assessing the strength of cardiac and sympathetic baroreflex controls via transfer entropy during orthostatic challenge

“…three variations) that met the following prerequisites [9]: (i) the absolute value of the total MSNA burst rate variation was larger than 0 bursts · s −1 ; (ii) the absolute value of the total DAP variation was larger than 1 mm Hg; (iii) the linear correlation coefficient, r MSNA-DAP , computed in the [DAP(i), MSNA(i + τ MSNA-DAP )] plane over the correspondent MSNA burst rate and DAP sequences, was larger than 0.85, where τ MSNA-DAP represents the lag between MSNA burst rate and DAP. τ MSNA-DAP was set to 0 [9] fully in agreement with the typical latency of sBR [36,37] given the definition of MSNA burst rate variability [23]. The slope of the regression line was calculated for each sBR sequence and subsequently averaged over all sequences.…”

“…This signal represents the modulation of the MSNA burst rate, its values are expressed in bursts s −1 and has the same time resolution as the original integrated MSNA signal [23]. The HP, SAP, DAP, RM and MSNA measures were taken on a beat-to-beat basis as follows: (i) the current HP was measured as the temporal distance between two consecutive R-wave peaks detected on the ECG; (ii) the kth SAP value was taken as the maximum of AP in the kth HP; (iii) the kth DAP was computed as the minimum of the AP preceding the kth SAP; (iv) the kth RM measure was taken by sampling the RM signal at the first R-wave delimiting the kth HP; (v) the kth MSNA burst rate value was obtained by sampling the signal representing the modulation of the MSNA burst rate at the first R-wave delimiting the kth HP [23]. HP, SAP, DAP, RM and MSNA burst rate beat-to-beat variability series of N = 256 consecutive values were randomly selected within each experimental condition and linearly detrended.…”

A Transfer Entropy Approach for the Assessment of the Impact of Inspiratory Muscle Training on the Cardiorespiratory Coupling of Amateur Cyclists

“…the tilt table inclination during graded head-up tilt test), was observed via a causal method decomposing the variance of HP series using a multivariate partial power spectral decomposition technique (Porta et al, 2012) and via a model-based conditional TE approach . The sympathetic activation and vagal withdrawal associated to the orthostatic challenge (Montano et al, 1994;Cooke et al, 1999;Furlan et al, 2000;Marchi A. et al, 2016) is likely to be responsible for the decoupling of the respiratory rhythm modulating vagal drive and HP dynamics. This decoupling is favored by the decrease of the gain of the HP-RM transfer function (Saul et al, 1991;Yana et al, 1993) and by the reduction of the RSA (Pomeranz et al, 1985) known to occur when cardiac vagal control is limited like during parasympathetic blockade performed via high dose administration of atropine.…”