(Hypertension. 1995;25:531-538.)
© 1995 American Heart Association, Inc.
Articles |
Analysis of Renal Sympathetic Nerve Responses to Stress
From the Department of Internal Medicine, University of Iowa College of Medicine, and Veterans Administration Medical Center, Iowa City.
Correspondence to Gerald F. DiBona, MD, Department of Internal Medicine, University of Iowa College of Medicine, Iowa City, IA 52242.
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Abstract We studied sympathetic nerve activity responses to acute environmental stress (air jet stress) in conscious Wistar-Kyoto, spontaneously hypertensive, and borderline hypertensive rats. The borderline hypertensive rats were fed either 1% (normotensive) or 8% (hypertensive) NaCl. Renal sympathetic nerve activity responses were analyzed with three methods: mean integrated voltage over time, power spectrum analysis, and sympathetic peak detection analysis. Measurements of mean integrated voltage over time showed that air jet stress increased renal sympathetic nerve activity in spontaneously hypertensive rats and in borderline hypertensive rats on 8% NaCl but not in the other groups. In the NaCl responders, power spectrum analysis of renal sympathetic nerve activity indicated that the increase in relative power was at the heart rate frequency, indicating that it was related to renal sympathetic nerve discharge coupled to the cardiac cycle. Sympathetic peak detection analysis of renal sympathetic nerve activity indicated that there was an increase in frequency of sympathetic peaks of greater height and shorter duration because of sinoaortic baroreceptor deactivation (increased peak frequency) and the recruitment of more active fibers (greater peak height) firing with greater synchronization (shorter peak duration). Additional methods of analysis of renal sympathetic nerve activity provide information in addition to that derived from measurement of mean integrated voltage over time.
Key Words: kidney • sympathetic nervous system • renal nerves • stress
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Introduction |
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The borderline hypertensive rat (BHR) is a genetic model of environmentally induced hypertension. The BHR, the first-generation offspring of a female spontaneously hypertensive rat (SHR) and a male normotensive Wistar-Kyoto rat (WKY), possesses genetic information from both a normotensive WKY parent and a hypertensive SHR parent. As described by Lawler and colleagues,1 2 3 4 5 BHR become permanently hypertensive when subjected to time-limited exposure to environmental stress or to increased dietary sodium intake. Renal denervation, performed early but not late, can prevent the development of environmental stress–induced hypertension in BHR.6
Increased dietary sodium intake causes the BHR to exhibit characteristics of the phenotype of the hypertensive SHR parent. In addition to developing sustained hypertension, BHR subjected to increased dietary sodium intake also manifest exaggerated natriuretic and renal sympathoinhibitory responses to intravenous isotonic saline loading compared with BHR on a normal dietary sodium intake.7 The exaggerated natriuresis is mediated by the exaggerated renal sympathoinhibition because it does not occur in BHR with renal denervation. These responses are similar to those of the hypertensive SHR parent.8 9 Alterations in cardiac volume receptor10 as well as arterial baroreceptor11 reflex function are similar in BHR on increased dietary sodium intake and their hypertensive SHR parents, whereas BHR on a normal dietary sodium intake exhibit normal reflex function, as do their normotensive WKY parents.
In response to acute environmental stress (air jet stress, which elicits the defense reaction), BHR on an increased dietary sodium intake exhibit increased cardiovascular, renal excretory, and sympathetic nerve activity responses compared with BHR on a normal dietary sodium intake.7 The pattern of response (increased arterial pressure, heart rate [HR], and renal sympathetic nerve activity [RSNA] and decreased urinary flow rate and sodium excretion) in BHR on an increased dietary sodium intake is similar to that of their hypertensive SHR parents, whereas BHR on a normal dietary sodium intake are unaffected by air jet stress, as are their normotensive WKY parents.
In several studies,7 10 11 assessment of the RSNA response was measured with a resetting voltage integrator that integrated (over 1-second intervals) a full-wave–rectified, amplified, and filtered neurogram obtained from a multifiber renal sympathetic nerve preparation in conscious, chronically instrumented rats. This method provides a reliable steady-state assessment of mean integrated voltage multifiber RSNA over time. Other analytical methods have been used to obtain additional information from recordings of RSNA. Power spectrum analysis has been used to measure the relative power present in various frequency domains of the RSNA signal as a potential index of sympathetic and parasympathetic contributions.12 Sympathetic peak detection analysis has been used to more precisely characterize (in terms of duration, height, and frequency) the synchronized bursts that are characteristic of postganglionic RSNA discharge.13 The purpose of the present study was to compare power spectrum and sympathetic peak detection analysis of the RSNA response to air jet stress in conscious WKY, SHR, and BHR (the latter on either 1% or 8% NaCl intake).
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Animals
SHR females and WKY males were purchased from Taconic Farms (Germantown, NY) and bred to produce BHR; only male BHR were used in this study. The rats, including age-matched WKY and SHR, were weaned at 4 weeks of age. Standard laboratory rat chow and tap water were available to all rats until the dietary regimens described below were instituted. All animal procedures were in accordance with the guidelines of the University of Iowa Animal Care and Use Committee.
Anesthesia
The rats were anesthetized with pentobarbital (Nembutal, Abbott
Laboratories) 50 mg/kg IP, supplemented with 10 mg/kg IV as needed.
Procedures
Catheterization
The rats were instrumented with polyethylene catheters in the
right jugular vein and right carotid artery for infusion of isotonic
saline (0.05 mL/min maintenance) and the measurement of arterial
pressure. The catheters were tunneled to the dorsum of the neck, where
they were exteriorized and plugged.
Electrode Recording RSNA
The left kidney was exposed through a left flank incision with a
retroperitoneal approach. With the use of a dissecting microscope
(x25), a renal nerve branch from the aorticorenal ganglion was
isolated and carefully dissected free. The renal nerve branch was then
placed on a bipolar platinum wire (Cooner Wire Co) electrode. RSNA was
amplified (x50 000) and filtered (low, 30 Hz; high, 3000 Hz) with a
high-impedance probe and preamplifier (models HIP 511 and P511,
respectively; Grass Instrument Co). The output of the amplifier was
channeled to a model 5113 oscilloscope (Tektronix, Inc) for visual
evaluation and to an audio amplifier/loudspeaker (model AM 8 audio
monitor, Grass Instrument Co) for aural evaluation. The quality of the
RSNA signal was assessed by examination of its pulse synchronous
rhythmicity and of the magnitude of decrease in recorded RSNA during
sinoaortic baroreceptor loading with an intravenous bolus injection of
norepinephrine (3 µg). The RSNA remaining after maximal inhibition
following norepinephrine administration was similar to the background
noise observed approximately 30 minutes postmortem; this postmortem
background noise value was subtracted from all experimental RSNA
values. When an optimal RSNA signal (pulse synchronous rhythmicity,
abolition by norepinephrine-induced arterial pressure
increase) was observed, the recording electrode was fixed to the renal
nerve branch with a silicone cement (Wacker Sil-Gel 604,
Wacker-Chemie). The electrode cable was then secured in position by
being sutured to the abdominal trunk muscles and further tunneled to
the dorsum of the neck, where it was exteriorized. The flank incision
was closed in layers.
Experimental Protocol
At 4 weeks of age, BHR were randomly assigned to one of two
dietary groups, 1% or 8% NaCl, with tap water drinking solution
available ad libitum. WKY and SHR received a 1% NaCl diet and tap
water drinking solution ad libitum. At 16 weeks of age, all rats were
chronically instrumented as described above. They were studied on the
following day in the conscious, unrestrained state. During a 15-minute
control period, continuous recordings of arterial pressure, HR, and
RSNA were made. Acute environmental stress (continuous air jet) was
then begun; 5 minutes thereafter, a 15-minute experimental period was
begun during which continuous recordings of arterial pressure, HR, and
RSNA were made. The air jet stress was stopped, the rats were killed,
and recordings of postmortem RSNA were obtained. Acute environmental
stress consisted of an air jet delivered continuously to the dorsum of
the rat's head through a tube located 4 to 5 cm behind the rat.
Repeated applications of air jet stress to the same rat result in
similar increases in HR, mean arterial pressure (MAP), and RSNA and in
decreases in urinary flow rate and sodium
excretion.14 15 16 17 18 19 20 21 22
Methods of Analysis
The amplified and filtered renal neurogram was
full-wave–rectified and integrated (model 7P3 Resistance-Capacitance
Integrator, 20-millisecond time constant, Grass Instrument Co) and
stored as RSNA on videotape (Vetter 4000A PCM, Vetter) along with the
neurogram, MAP (Statham 23Db pressure transducer; Statham-Gould), and
HR (model 7P4 tachograph, Grass Instrument Co) signals for later
off-line analysis by each of the three methods described below.
Steady-State Averaging
With an analog-to-digital converter (model 2801, Data
Translation) and standard data acquisition software (LABTECH
NOTEBOOK 7.3, LabTech), the steady-state RSNA, MAP, and HR were
sampled at 5 Hz and averaged over the middle 10 minutes of both control
and experimental air jet stress periods.
Power Spectral Analysis
With an analog-to-digital converter (Data Translation 2801) and
standard data acquisition software (LABTECH NOTEBOOK
7.3), the steady-state RSNA was sampled at 40 Hz over the 10-minute
periods described above. A fast Fourier transformation
program12 was used to perform time series analysis.
This consisted of (1) dividing the record into data blocks of 1024
values each, (2) subjecting each data block to cosine tapering (to
alleviate leakage) of the first and last 100 values and to a baseline
correction by subtracting the mean value from each individual value,
(3) dividing each power estimate by the total power of the block to
obtain the relative power, (4) plotting the periodograms against the
time in which the block of values was obtained, (5) calculating the
power of the variations for the 0.15 to 10.0 Hz range over the
recording period, and (6) calculating the volume (relative power versus
frequency versus time) for the range of 0.15 to 10.0 Hz.
The Nyquist frequency was 20 Hz. Selection of a data block size of 1024 values provided a frequency resolution of 0.039 Hz. Obtaining sequential power spectra over time permitted a three-dimensional display (SIGMAPLOT 5.0, Jandel Scientific). Grids for surface plots were calculated according to the inverse distance method, which generates z values for an evenly spaced xy grid from xyz triplet data. The inverse distance method uses a weighting power to minimize the effect of distant points on the interpolation of values. A larger weighting power places less emphasis on distant points; a weighting power of 2 was used.
As previously noted,12 it was possible to identify three spectral components in the RSNA signal. The most obvious were the HR fluctuations of RSNA. In addition to the HR oscillations, two lower-frequency areas with substantial power were identified: (1) Traube-Hering waves, which are linked to respiration, that had a frequency range between 0.7 and 2 Hz, and (2) low-frequency (LF) variability. However, because very low-frequency noise (1/f [noise]<0.1 Hz) could obscure this frequency domain, the LF range was defined as 0.15 to 0.6 Hz. Because there was a noticeable increase in HR oscillations during air jet stress, the high-frequency (HF) range was defined as 0.6 to 3.0 Hz to allow assessment independent of the effect of the HR oscillations. In addition, an HR range was defined as a 0.5-Hz window centered on mean HR frequency to allow separate assessment of HR oscillations. Thus, the spectral estimate for each range (LF, HF, HR) was divided by the total power of the range between 0.15 to 10.0 Hz. Simpson's rule was used to calculate the volume related to the LF, HF, and HR ranges.
Sympathetic Peak Detection Program
The steady-state RSNA displayed positive deflections that were
proportional to the frequency discharge in the original neurogram and
that generally occurred with each cardiac cycle. Individual nerve
bursts still observable in the RSNA record were smoothed by subsequent
filtering at 35 Hz. The smoothed RSNA was used for analysis of
synchronized discharge characteristics. With an analog-to-digital
converter (Data Translation 2801) and standard data acquisition
software (LABTECH NOTEBOOK 7.3), the steady-state RSNA
was sampled at 200 Hz over the 10-minute periods used above. The
characteristics of RSNA were determined with a statistically based
computerized algorithm, the SYMPATHETIC PEAK DETECTION PROGRAM,
VERSION 2.13 This program is based on a cluster
analysis developed by Veldhuis and Johnson23 that was
designed to detect peaks in episodic hormone secretion. The Sympathetic
Peak Detection Program allows the simultaneous determination of the
amplitude (height), duration, and periodicity of synchronized
sympathetic discharges or peaks. The program examined sequential groups
of samples (clusters) of RSNA voltages, searching for significant
increases and then significant decreases within the series. It began by
searching for significant increases by comparing two sequential
clusters of an operator-defined size using a t test. The
first cluster of samples is defined as a possible nadir and the second
as a possible peak. All significant increases in voltage throughout the
series are detected by shifting the nadir cluster by one sample and
retesting against a corresponding possible peak shifted by one sample.
After all significant increases were marked, the series was rescanned
in consecutive order to search for significant decreases. An
operator-defined test peak size was compared with a nadir immediately
postpeak (the size of the postpeak nadir was the same as that specified
for the prepeak nadir). The occurrence of a peak in synchronized RSNA
is defined as a significant increase followed by a significant decrease
with a nadir on each side. It is necessary to decide what constitutes
synchronized RSNA because the program relies on the detection of peaks
in RSNA. For this study, the minimal acceptable peak height was set at
greater than 25% of the maximal peak height in the data series; ie, at
least 25% of possible nerve fibers were active together to be
classified as a synchronized peak in RSNA. After the synchronized peaks
had been identified for each data series, the peak-to-peak interval
(periodicity, in milliseconds), peak duration (milliseconds), and the
absolute (microvolts) and relative (percent of mean peak height)
heights of the peaks were calculated. Peak height was recorded as a
percentage of the mean peak height in each rat because the absolute
voltage values vary between rats.
A 5x4 cluster configuration (five samples in test nadir, four samples in test peak) was chosen because this configuration and a t statistic of 4.1 for both significant peak upstrokes and downstrokes have been shown to give a false-positive/false-negative rate of approximately 4% at a sampling frequency of 200 Hz.13
Statistics
Statistical analysis was conducted with ANOVA and
Scheffé's test for pairwise comparisons among
means.24 Statistical significance was taken at a value of
P<.05. Data in text, tables, and figures are mean±SEM.
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Results |
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Steady-State Averaging
In the control period, MAP and HR were significantly greater in SHR than in WKY and greater in BHR consuming 8% NaCl (BHR-8%) than in BHR consuming 1% NaCl (BHR-1%) (Fig 1). During air jet stress, MAP and HR increased in SHR and BHR-8% but were unchanged in WKY and BHR-1% (Fig 1). During air jet stress, RSNA increased similarly (50% to 60%) in SHR and BHR-8% but was unchanged in WKY and BHR-1% (Fig 2).
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ERSNA) for Wistar-Kyoto rats (WKY),
spontaneously hypertensive rats (SHR), borderline hypertensive rats
consuming 1% NaCl (BHR 1%), and borderline hypertensive rats
consuming 8% NaCl (BHR 8%). *P<.05.
Power Spectrum Analysis
The results for a single SHR are shown in Fig 3.
During the control period (Fig 3a), volume at the HR frequency of 7.42
Hz or 445 beats per minute (0.0239 Hz · h) was lower than that in
either the LF (0.0785 Hz · h) or HF (0.1565 Hz · h) ranges.
However, during air jet stress (Fig 3b), there was a substantial
increase in volume at the HR frequency of 7.89 Hz or 473 beats per
minute (0.0715 Hz · h), with little change in that in the LF
(0.0734 Hz · h) and HF (0.1588 Hz · h) ranges.
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The group data for LF, HF, and HR volume for WKY and SHR are shown in Fig 4a. In the control period, values for LF, HF, and HR volume were not significantly different between WKY and SHR. Air jet stress produced significant increases in HF volume in WKY and in HR volume in SHR.
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The group data for LF, HF, and HR volume for BHR-1% and BHR-8% are shown in Fig 4b. In the control period, values for LF, HF, and HR volume were not significantly different between BHR-1% and BHR-8%. Air jet stress produced significant increases in HF volume in BHR-1% and in HR volume in BHR-8%.
Sympathetic Peak Detection Program
Within the entire data set (120 000 samples for each control and
experimental air jet stress period per rat), air jet stress
significantly increased mean voltage and maximal peak voltage in SHR
and BHR-8% but not in WKY and BHR-1% (Table 1). The
increases in mean voltage calculated from this analysis
(approximately 50% to 60%) were similar to those derived from
steady-state averaging (Fig 2).
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The results of the synchronized peak detection analysis are shown in Table 2 (mean values) and Figs 5 through 8 (frequency histograms). During the control period, peak frequency was significantly higher and peak periodicity (peak-to-peak interval) was significantly lower in SHR than in WKY and in BHR-8% than in BHR-1%. Peak duration was significantly lower in BHR-1% and BHR-8% than in WKY and SHR. Air jet stress did not affect peak frequency, periodicity, duration, or height in WKY or BHR-1%. Air jet stress significantly increased peak frequency, decreased peak periodicity, and increased peak height in both SHR and BHR-8%.
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In WKY (Fig 5), periodicity was unimodal at 150 ms during control and 160 ms during air jet stress. Peak duration and peak height were unimodal, 110 ms and 110%, respectively, during control, and there was no effect of air jet stress. In SHR (Fig 6), periodicity was bimodal at 130 and 240 ms during both control and air jet stress. Air jet stress significantly increased the percentage of peaks with periodicity at the 130-ms mode but not at the 240-ms mode. Peak duration was also bimodal at 100 and 190 ms during control and air jet stress. Air jet stress significantly increased the percentage of peaks with duration of 90 ms. Peak height was unimodal at 110% during control and 120% during air jet stress. Air jet stress significantly increased the percentage of peaks with height at 120% and 130% and significantly decreased the percentage of peaks with height at 110%. Thus, in SHR compared with WKY, air jet stress resulted in an increased occurrence of HF peaks (shorter period) with shorter duration and increased height.
In BHR-1% (Fig 7), periodicity was unimodal at 150 ms during control and 160 ms during air jet stress. Peak duration and peak height were unimodal, 100 ms and 110%, respectively, during control, and there was no effect of air jet stress. In BHR-8% (Fig 8), periodicity was bimodal at 130 and 210 ms during control and 130 and 250 ms during air jet stress. Air jet stress significantly increased the percentage of peaks with periodicity at 110, 120, 130, and 140 ms and significantly decreased the percentage of peaks with periodicity at 190, 200, 210, 220, and 230 ms. Peak duration was also bimodal at 90 and 190 ms during control and air jet stress. Air jet stress significantly increased the percentage of peaks with duration of 90 and 100 ms and significantly decreased the percentage of peaks with duration of 140, 150, 160, 170, and 180 ms. Peak height was unimodal at 110% during control and 120% during air jet stress. Air jet stress significantly increased the percentage of peaks with height at 120%, 130%, and 140% and significantly decreased the percentage of peaks with height at 100% and 110%. Thus, in BHR-8% compared with BHR-1%, air jet stress resulted in an increased occurrence of HF peaks (shorter period) with shorter duration and increased height.
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Steady-State Averaging
Acute environmental stress produced by air jet stress elicits the defense reaction in conscious SHR. Like the hypertensive SHR parent, BHR-8% but not BHR-1% become hypertensive and demonstrate an increase in MAP, HR, and mean integrated RSNA during air jet stress. The present results confirm our previous findings.17 22
Power Spectrum Analysis
Power spectrum analysis of RSNA indicated that during the
control period in all four rat groups, HF volume was greater than both
LF and HR volume, which were similar. LF, HF, and HR volume were not
different between WKY and SHR or between BHR-1% and BHR-8%. Thus,
despite a chronic increase in RSNA in SHR compared with WKY, LF volume
of SHR was not higher than in WKY. This confirms the finding of Persson
et al,12 who found that LF volume of splanchnic
sympathetic nerve activity (SSNA) was not higher in SHR than in WKY and
drew the conclusion that spectrum analysis only measures the
variability of a system and not the activity of its generating
components.
During air jet stress, there were increases in HF volume (HR volume was unaffected) in WKY and BHR-1% and in HR volume (HF volume was unaffected) in SHR and BHR-8%. LF volume was not affected by air jet stress in any group. Note that air jet stress increased HR, MAP, and RSNA in SHR and BHR-8% but not in WKY and BHR-1%. These results would suggest that increases in RSNA produced by air jet stress are reflected mainly in increases in HR volume rather than in changes of LF or HF volume.
Arguments have been put forward that LF oscillations in blood pressure
and HR spectrum analysis are mediated by the sympathetic nervous
system, whereas HF oscillations are mediated by the parasympathetic
nervous system.25 Persson et al12
administered prazosin, an 
1-adrenoceptor antagonist, to
antagonize the effect of sympathetic nerve activity on vascular
1-adrenoceptors. This produced a decrease in blood
pressure of 50 to 60 mm Hg in WKY and SHR. Spectrum analysis of
blood pressure showed that LF volume was significantly decreased and HF
volume significantly increased in both WKY and SHR. These results
indicate that acute decreases in the sympathetic neural contribution to
blood pressure decrease LF power in the blood pressure spectrum
analysis. However, although data were not provided, the decrease in
blood pressure might be expected to have resulted in a reflex increase
in SSNA. It appears that LF power decreased and HF power increased in
the spectrum analysis of SSNA.12 These results would
suggest that acute reflex increases in SSNA result in decreased LF
power in the SSNA spectrum analysis. In the current study,
increases in RSNA were not associated with a change in LF power but
rather were reflected in increases in HR power. These results suggest
that, at least in response to air jet stress (which elicits a defense
reaction), increased RSNA is reflected in the power spectrum as an
increase in the oscillations that are related to the synchronous
discharge coupled to the cardiac cycle (ie, HR).
In both WKY and BHR-1%, air jet stress did not affect MAP, HR, or RSNA but increased HF volume in the RSNA power spectrum analysis. Persson et al12 were unable to demonstrate a contribution of the parasympathetic nervous system to either the LF or HF volume of the blood pressure spectrum analysis in WKY and SHR. It is known that the central nervous system induces HF oscillations in both sympathetic and parasympathetic efferent fibers.26 Furthermore, as defined here, the HF range (0.6 to 3.0 Hz) included the Traube-Hering waves, which are linked to respiration. Although respiratory frequency was not precisely measured in the rats (it was generally approximately 1 Hz), it is possible that the increase in HF volume in the RSNA spectrum analysis during air jet stress may have been related to respiratory influences.
Sympathetic Peak Detection Program
The discharge of postganglionic renal sympathetic nerve fibers is
synchronized into bursts related to the cardiac cycle. The synchronized
bursts exhibit continuously fluctuating variability in terms of
periodicity, duration, and amplitude. Although measurement of RSNA as
mean integrated voltage over time provides basic information concerning
the overall level of nerve activity, it does not characterize the
synchronized bursting nature of RSNA because the typical synchronized
burst has a duration (approximately 100 to 150 ms) far shorter than
that generally used for calculating the mean integrated voltage (eg,
1000 ms7 ). The Sympathetic Peak Detection Program, derived
from cluster analysis, allows the identification of synchronized
bursts or peaks of postganglionic RSNA and characterization of each
peak as to its periodicity (peak-to-peak interval), duration, and
amplitude. Previous studies in cats13 27 28 29 and
rats30 have demonstrated its utility. For example,
sinoaortic baroreflex activation is known to decrease mean integrated
RSNA and might have been expected to decrease the amplitude of
sympathetic peaks. However, a decrease in mean integrated RSNA could
also be due to an increase in the period between sympathetic peaks (ie,
decreased frequency) without a decrease in the amplitude of the peaks.
In fact, this has been observed,27 a finding masked by
previous methods of analysis. Conversely, sinoaortic deactivation
was found to decrease the period (ie, to increase frequency) between
sympathetic peaks without increasing their amplitude.27
Thus, the frequency (but not the amplitude) of sympathetic peaks,
reflecting rhythmic activation of the multifiber units by the central
nervous system, is closely related to baroreceptor activity.
Because each individual nerve fiber has a constant discharge voltage,31 it was proposed that changes in the amplitude of sympathetic peaks were due to changes in the number, recruitment, or both of active fibers. This hypothesis was supported by a study in which the periodicity and amplitude of sympathetic peaks occurring in postganglionic cardiac sympathetic nerve activity was analyzed before and after successive denervation of T1-5 preganglionic nerves to the stellate ganglion. Peak amplitude but not periodicity was progressively decreased, supporting the view that peak amplitude reflects the number of active fibers.29
It was found that peak amplitude and peak duration were significantly correlated, and it was suggested that peak duration is related to differences in the conduction times among individual nerve fibers.29 Thus, when fewer fibers are active, the range of conduction times is less. Analysis of the response to hypoxia supported this suggestion.28 Hypoxia, which increased mean integrated RSNA, increased both amplitude and duration but did not change periodicity; thus, when more fibers were active (amplitude was increased) the range of conduction times was greater (duration was increased). Another factor suggested was the effect of differences in the timing of input to the postganglionic neurons, ie, the degree of synchronization.13 Not all central or preganglionic neurons are likely to fire at the same time. Thus, increased synchronization would result in a decrease in peak duration.
In the present study, analysis of the RSNA responses in SHR and BHR-8% showed that air jet stress significantly increased mean peak frequency, decreased mean peak period, increased mean peak height, and did not affect mean peak duration (Table 2). Analysis of the frequency histograms of the RSNA responses in SHR and BHR-8% (Figs 5 through 8) showed that air jet stress produced an increased occurrence of HF (shorter-period) peaks of shorter duration and increased height. For period and duration, which were bimodal, there was a shift from the higher to the lower mode (shorter period and duration). The defense reaction overrides sinoaortic baroreceptor regulation of both HR and RSNA32 in that MAP, HR, and RSNA increase together. This reaction is similar to sinoaortic baroreceptor deactivation, which, as noted above, causes peak frequency to increase (ie, shortens the period). The increased peak height indicates that more active fibers have been recruited, and the shorter peak duration suggests that the degree of synchronization has increased. Because there are precise neural pathways for the defense reaction, it is possible that this might facilitate a more synchronized central and preganglionic input to RSNA, resulting in the observed shorter peak duration.
In summary, the increase in RSNA that occurs as part of the defense reaction in response to air jet stress in SHR and BHR-8% but not WKY and BHR-1% has been analyzed using power spectrum and sympathetic peak detection analyses. Power spectrum analysis indicated that the increase in RSNA was mainly reflected in an increase in relative power occurring at the HR frequency, presumably representing the discharge related to the cardiac cycle. The data from sympathetic peak detection analysis are consistent with the interpretation that the increase in RSNA was related to sinoaortic baroreceptor deactivation that increased the frequency (ie, decreased the periodicity) of sympathetic peaks and to recruitment of more active fibers (as indicated by increased peak height) with increased synchronization (as indicated by decreased peak duration). These combined approaches to the analysis of postganglionic RSNA provide additional information beyond that derived from the measurement of mean integrated voltage over time.
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Acknowledgments |
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This work was supported by National Institutes of Health grants DK 15843 and HL-44546 and by the Veterans Administration. The authors are grateful to Pontus B. Persson and Uwe Wittmann (fast Fourier transformation) and to Simon Malpas (Sympathetic Peak Detection Program, Version 2) for generous provision of copies of software and encouraging advice and consultation.
Received May 6, 1994; first decision July 27, 1994; accepted October 25, 1994.
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