Howard Florey Institute of Experimental Physiology and Medicine, University of Melbourne, Victoria 3010, Australia
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ABSTRACT |
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McAllen, R. M., D. Trevaks, and A. M. Allen. Analysis of Firing Correlations Between Sympathetic Premotor Neuron Pairs in Anesthetized Cats. J. Neurophysiol. 85: 1697-1708, 2001. The activity of sympathetic premotor neurons in the rostral ventrolateral medulla (subretrofacial nucleus) supports sympathetic vasomotor tone, but the factors that drive these premotor neurons' activity have not been determined. This study examines whether either direct interconnections between subretrofacial neurons or synchronizing common inputs to them are important for generating their tonic activity. Simultaneous extracellular single-unit recordings were made from 32 pairs of sympathetic premotor neurons in the subretrofacial nucleus of chloralose-anesthetized cats. Paired spike trains were either separated by spike shape from a single-electrode recording (14 pairs) or recorded from two electrodes less than 250 µm apart (18 pairs). All neurons were inhibited by carotid baroreceptor stimulation and most had a spinal axon proven by antidromic stimulation from the spinal cord. Autocorrelation, inter-spike interval, and cardiac cycle-triggered histograms were constructed from the spontaneous activity of each neuron, and cross-correlation histograms covering several time scales were generated for each neuron pair. No significant peaks or troughs were found in short-term cross-correlation histograms (2 ms bins, ±100 ms range), providing no support for important local synaptic interactions. On an intermediate time scale (20 ms bins, ±1 s range), cross-correlation revealed two patterns indicating shared, synchronizing inputs. Repeating peaks and troughs (19/32 pairs) were due to the two neurons' common cardiac rhythmicity, of presumed baroreceptor origin. Single, zero time-spanning peaks of 40-180 ms width were seen in 5/32 cases. Calculations based on the prevalence and strength of these synchronizing inputs indicate that most of the ensemble spike activity of the subretrofacial neuron population is derived from asynchronous sources (be they intrinsic or extrinsic). If synchronizing sources such as neuronal oscillators were responsible for more than a minor part of the drive, they would be multiple, dispersed, and weak.
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INTRODUCTION |
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Understanding the mechanisms
responsible for generating sympathetic vasomotor tone represents an
essential step in our attempts to define the role of the CNS in the
regulation of cardiovascular function. It is known that vasomotor tone
depends critically on supraspinal drive, and work over the last two
decades has highlighted the role of premotor neurons in the
subretrofacial nucleus [synonymous with the rostral ventrolateral
medulla (RVLM)] as the major relay for that drive (Dampney
1994; Dampney and Moon 1980
; Guyenet
1990
; McAllen 1986
). But the mechanisms
responsible for the generation of the tonic activity of the premotor
neurons remain uncertain.
Recent intracellular recordings from rat RVLM sympathetic premotor
neurons in vivo demonstrate that under normal experimental conditions,
action potentials in sympathetic premotor neurons invariably arise from
depolarizing events with the characteristics of excitatory synaptic
inputs (Lipski et al. 1996). The observation, in the
rat, that blockade of excitatory amino acid receptors or synaptic
transmission in the RVLM does not affect sympathetic activity or blood
pressure, raises some question about the nature of this synaptic
driving input in this species (Sun and Guyenet 1987
;
Trzebski and Baradziej 1992
). However, bilateral
microinjections of the synaptic blocker, cobalt chloride, into the RVLM
of cats markedly reduce both tonic sympathetic nerve activity and blood pressure (Seller et al. 1990
). Similarly in rabbits,
bilateral microinjections of the excitatory amino acid receptor
antagonist, kynurenic acid, into the RVLM induce a decrease in blood
pressure (Blessing and Nalivaiko 2000
). Thus while this
area is not entirely resolved, much of the activity of sympathetic
premotor neurons may be dependent on excitatory synaptic inputs under
basal conditions in anesthetized animals.
Currently there is little information regarding the nature of the
driving inputs to sympathetic premotor neurons. We reasoned that there
were two main possibilities. First the sympathetic premotor neurons may
themselves form part of the generator network, in which case the
premotor neurons must directly or indirectly influence each
otherbecause interconnections define a network. Second, an antecedent
source or sources could drive the premotor neurons. In that case, the
activity of premotor neurons might be synchronized by common inputs
from those driving sources, especially if they are rhythmic, as
suggested by Gebber, Barman and colleagues (see Gebber 1980
,
1990
). Alternatively the driving inputs might come from
multiple, asynchronous sources, causing little synchrony between
premotor neurons.
To examine these possibilities, we made simultaneous extracellular
recordings from pairs of sympathetic premotor neurons in the
subretrofacial nucleus, where the RVLM premotor neurons in the cat are
concentrated (McAllen 1986; Polson et al.
1992
). We used cross-correlation analysis to detect synchrony
between their spike trains on both short (millisecond) and medium (tens
of milliseconds to seconds) time scales to describe the degree of
synchrony quantitatively in terms of spikes per second
(Nordstrom et al. 1992
). These data have enabled us to
estimate the spiking synchrony of the subretrofacial population as a
whole. We asked the following questions: do subretrofacial neurons
interact synaptically as part of a local network? Do they receive
common inputs from antecedent sources that synchronize their activity?
If so, how important are those influences for these neurons' overall activity?
Preliminary accounts of part of this work have appeared in abstract
form (Allen and McAllen 1994; McAllen and Allen
1995
).
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METHODS |
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Preparation
All experiments were performed in accordance with the Australian National Health and Medical Research Council code of practice for the care and use of animals for scientific purposes and were approved by the Animal Experimentation Ethics Committee of the Howard Florey Institute. Experiments were performed on 17 cats of either sex [4.1 ± 0.2 (SE) kg], anesthetized with alpha chloralose (70 mg/kg iv) given after 11 mg/kg im ketamine hydrochloride. Supplementary doses of chloralose (7-20 mg/kg iv) or pentobarbitone (12-18 mg iv) were given if the cats showed any signs of inadequate anesthesia. Corneal and withdrawal reflexes were tested at least every 20-30 min. During recording periods, animals were paralyzed with bolus doses of pancuronium bromide (2 mg iv). Paralysis was induced after the completion of surgery and was allowed to wear off at intervals when the level of anesthesia was tested conventionally by corneal and withdrawal reflexes. At other times, anesthesia was monitored by reference to blood pressure and the meiotic state of the pupils.
All animals were given a tracheotomy and ventilated artificially with oxygen-enriched air, maintaining end-tidal CO2 levels near 4%. Rectal temperature was maintained near 38°C by a servo-controlled heating blanket. The right femoral artery and vein were cannulated for the measurement of blood pressure and the administration of anesthetic, respectively. The bladder was catheterized and drained.
The animal was held supine in a stereotaxic frame and fixed
additionally by clamping two thoracic spines. The medulla was then
exposed from a ventral approach as described previously (McAllen et al. 1982). The spinal cord was exposed at the
C3/C4 junction from a
ventral approach using a dental drill. A fine stainless steel
stimulating electrode, made from an insect pin insulated with lacquer
up to approximately 0.3 mm from the tip, was inserted obliquely into
the left dorsolateral funiculus by a micromanipulator.
One carotid sinus was prepared as a blind sac by tying all vascular branches except the external and common carotid arteries. To stimulate baroreceptors, the common carotid artery was reversibly occluded with a pneumatic cuff. The sinus was inflated, through a cannula in the external carotid artery with heparinized normal saline solution (10 U/ml) to a pressure of 200 mmHg. In some experiments, the remaining baroreceptor areas were denervated by section of the contralateral sinus nerve and both cervical vago-sympathetic trunks. The one intact carotid sinus could then, at will, be isolated and exposed to a steady perfusion pressure to remove the pulsatile component of the baroreceptor signal.
In two animals, from which two subretrofacial neuron pairs were recorded, the left renal nerve was isolated and placed on a bipolar recording electrode. The nerve and electrode were covered in paraffin oil. Activity was amplified, filtered (1-1,000 Hz) and recorded on magnetic tape for later analysis.
Before recording, animals were given a bilateral pneumothorax to reduce brain movement associated with ventilation, and the dura was opened over the medulla.
Unit recording
The subretrofacial nucleus was defined as the region immediately caudal to the facial nucleus where microinjections of 1-5 nl of sodium glutamate (0.1 M) produced a brisk rise in blood pressure. At this site, small patches were opened in the pia mater through which either one or two glass-insulated tungsten microelectrodes were inserted by independent, hydraulic microdrives. In experiments where two electrodes were inserted, the second drive was inserted caudally and aimed rostrally at an angle of 26° such that the electrodes converged to record from sites within 250 µm of each other. Signals from each electrode were recorded differentially with respect to a metal ring, which was held against the medullary surface around the recording site to stabilize recordings. Spike potentials were amplified and filtered (band-pass: 300-3,000 Hz) and recorded along with blood pressure, sinus pressure, and a voice/event channel on magnetic tape for later analysis. Discriminated spikes (see next section), blood pressure, and an event marker were also recorded with a computer-based analysis system (Spike2, CED, Cambridge, UK). This program was used to generate autocorrelation, cross-correlation, and cardiac cycle-triggered histograms of unit activity as well as spike-triggered averages and frequency spectra of renal nerve activity.
Spike discrimination
Spike potentials were monitored on a variable persistence storage oscilloscope. Units were discriminated on-line by their spike shape using a custom-built, two-channel, time + amplitude window discriminator. The discriminator output pulse was used to trigger the stimulator for antidromic activation during the collision test. In all cases, the discrimination process was repeated off-line from tape recordings. Great care was taken first to eliminate the effects of electrical or mechanical artifacts, which occasionally interfered with both channels. To achieve this, close monitoring of spike discrimination was required throughout.
In the cases where paired recordings were discriminated from a single electrode, extra precautions were needed to avoid misleading artifacts. First, it was critical to check that one neuron's spike was never counted simultaneously by two discriminator channels. Second, in cases where one neuron fired doublet or triplet spikes, which always became progressively smaller and wider during the burst, great care was necessary to identify them as such rather than as action potentials of another neuron. Third, in cases where the amplitude of the second spike was relatively low, it was important to check that the discrimination included no false-negative or false-positive counts due to "waveriding." Following a large spike, the afterpotentials and the settling time of a filtered signal will include positive and negative swings in baseline potential, on which small spikes may sum to reach, or fail to reach, detection threshold. Such a mechanism could erroneously produce cross-correlation patterns suggestive of short-term neuronal interaction. Close scrutiny was needed to ensure that the desired spikes were all detected and that undesired spikes were not.
Independent evidence for the adequacy of unit discrimination was sought in all cases by plotting the autocorrelogram of each unit (see following text) and assessing its postspike refractory period. If a significant number of spikes appeared in this trough (more than 5% of the mean spike count at times distant from the refractory period), the record was reanalyzed from tape and the discrimination process repeated. A spike-shape analysis program (Discovery, Datawave, Longmont, CO) was used to discriminate spikes in a few difficult cases. Units that failed to pass these tests were eliminated from further analysis.
Analysis
Discriminated spike signals were analyzed off-line from tape, using the Spike2 program to generate auto- and cross-correlation histograms (cross-correlograms) of subretrofacial nucleus neuron activity. For cross-correlograms, one spike train was arbitrarily chosen as the trigger and the other as the response. (The opposite choice merely gives the same histogram, reversed in the time axis.) Cross-correlograms were plotted for every unit pair using 2, 20, and 200 ms bins as well as other bin sizes where this helped to clarify particular features. Autocorrelograms and inter-spike interval histograms were also generated for each unit to check the adequacy of unit discrimination and to examine the firing characteristics of individual neurons. Arterial pulse-triggered correlograms (20 ms bins) were generated for every unit by cross-correlating subretrofacial nucleus neuron spikes with the times of peak systolic blood pressure.
Histogram peaks and troughs were detected initially by inspection and
were classified as single or recurring. In cases where a putative
single peak was superimposed on a slower periodic wave, judgement had
to be used to determine the appropriate control value for comparison
(Kirkwood 1979). Significance was tested by two methods.
First, single-bin counts were considered significantly different from
the mean count if their value had a probability of less than 0.1%, as
calculated from the mean bin count on the basis of a Poisson process
(Abeles 1982
; Graham and Duffin 1981
). This P value allowed for the null hypothesis being tested
simultaneously over approximately 50 bins: inspection of the
distribution of bin counts at times remote from the trigger, and thus
presumably due to random fluctuations, confirmed that this choice was
appropriate. To test the significance of peaks (or troughs) that were
spread over several adjacent bins, the cumulative sum (CUSUM) test
(Davey et al. 1986
; Imamura and Onoda
1983
) was then applied. In this case, the CUSUM of the counts
in consecutive bins was required to deviate robustly (in a manner not
critically dependent on the choice of binwidth, or starting point)
beyond the 1% probability value for five consecutive bins to be
considered significant (McAllen and May 1994
). Finally,
in cases where the histogram showed an obvious periodicity, neither
method was considered applicable, but the influence on the neuron
pair's synchrony of a common cardiac periodicity (presumably from
baroreceptors) was analyzed graphically by plotting two dimensional
cross-correlation matrices (see following text).
A custom-written program within Spike2 was used to generate two-dimensional cross-correlation matrices. The occurrence times of response spikes were plotted in 20 ms bins with respect to both the cardiac cycle (abscissa) and the trigger spike (ordinate). The counts in each 20 ms × 20 ms square were color coded and presented as quintiles between the minimum and the maximum values in the matrix (blue, green, red, yellow, white, in ascending order). The process was repeated for each neuron pair, with the "trigger" and "response" spike trains interchanged.
In cases where a significant peak was present in the cross-correlation
histogram, its magnitude was expressed as a percentage, comparing the
total number of excess counts in the peak (above the mean baseline
value) with the geometric mean of the total spike counts of the two
neurons (Nordstrom et al. 1992).
Histology
At the end of experiments, direct anodal current (approximately 2 µA for 1 min) was passed through one recording electrode. The electrode was removed, and 50 nl of 2% pontamine blue dye was pressure injected into the same spot to mark the area and help later histological identification. The cat was killed with an overdose of pentobarbitone, and the medulla was removed and immersed overnight in 4% paraformaldehyde. Forty-micrometer transverse frozen sections were cut of the region containing the mark. Marked sites were located microscopically and traced from the X30 projected image on a microfilm reader. Recording sites were reconstructed from depth measurements in the marked tracts.
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RESULTS |
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Paired extracellular single-unit recordings were made from one or
two electrodes with tips located within the immediate vicinity of the
left subretrofacial nucleus. Additionally, every neuron considered here
showed spontaneous activity that was abruptly inhibited on inflation of
a carotid blind sac preparation (Fig. 1A). Once two such unit
recordings were isolated, attempts were made to determine whether
either neuron possessed a spinal axon by looking for an antidromic
response to electrical stimulation of the dorsolateral funiculus in the
third to fourth cervical segments (Fig. 1B). Standard tests,
including the collision test, were then performed to confirm the
presence of a spinally projecting axon (Lipski 1981). In
all cases, at least one neuron of every pair was demonstrated to
possess a spinal axon. Both neurons were proven bulbospinal in the
cases of 14/32 pairs, and in a further five cases, the second unit
showed a constant latency response to spinal stimulation although
formal collision tests were not concluded.
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In two animals, whole nerve activity was also recorded from the left
(ipsilateral) renal sympathetic nerve. This showed the well-described
pattern of large, synchronized bursts whose association with the
arterial pulse was probabilistic rather than precise (cf. Gebber
1980, 1990
). Spectral analysis confirmed this by showing that
in both cases, less than 10% of the power within the 2-15 Hz range
was at the cardiac frequency (data not shown). A positive spike-triggered average in renal nerve discharge (cf. Barman and Gebber 1997
) could be demonstrated with two of the four
subretrofacial neurons recorded at the same time, the peak renal nerve
responses occurring 150 and 190 ms after the medullary neuron spikes,
respectively (data not shown).
Neuronal characteristics
The basic properties of the neural population studied are
illustrated in Fig. 1. Their firing rates and conduction velocities were as previously established for this population of sympathetic premotor neurons in cats (Barman and Gebber 1985;
McAllen 1986
). Autocorrelation and inter-spike interval
histograms were generated to reveal details of these neurons' firing
patterns (and to confirm single unit discrimination
see
METHODS). Inter-spike interval histograms were usually
unimodal with a leftward skew (Fig.
2A) although 7/55 neurons
showed a second peak due to the presence of doublet (and in 1 case,
triplet) spikes separated by 4-20 ms. All but two neurons' modal
firing intervals were shorter than the cardiac cycle (Fig.
2B), and none was locked 1:1 with the pulse. Firing patterns
were classified broadly as regular (where obvious peaks reflecting the
modal inter-spike interval appeared in the autocorrelogram: 22/55
neurons, 15 proven bulbospinal; Fig. 2Ai) or irregular
(where no such peaks were evident: 25/55 neurons, 16 proven
bulbospinal). The remaining eight neurons (6 proven bulbospinal; Fig.
2Aii) showed less distinct peaks in their autocorrelograms
and were classified as intermediate. To look for any preferred firing
intervals that might be expressed by this neuronal population, their
modal inter-spike intervals (including multiple peaks) were plotted in
a population histogram (Fig. 2B). Within the range of
50-500 ms, no preferred interval was apparent.
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Arterial pulse-triggered correlograms were also plotted from the spontaneous activity of all neurons. Although all neurons were shown by carotid sinus inflation to be barosensitive, a clear cardiac periodicity was found in the discharge of only 41/55 neurons, even though arterial pressure was maintained within the appropriate range (Figs. 1A and 3). Among those neurons where such a relation was present, its strength varied considerably (Figs. 3 and 5).
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Cross-correlation
The spontaneous activity of 32 subretrofacial nucleus neuron pairs was recorded for periods of between 3 and 30 min (range of individual neuron spike counts 457-20,305; 4,958 ± 436; mean ± SE). Spike trains of 14 pairs were discriminated by spike shape from a single-electrode recording; 18 pairs were recorded from two separate electrodes positioned within 250 µm of each other. From these data, cross-correlograms were plotted for every unit pair, using 2, 20, and 200 ms time bins (Figs. 3 and 4).
SHORT TIME SCALE INTERACTIONS (PEAKS OR TROUGHS OF DURATION LESS
THAN 20 MS).
Evidence was sought for excitatory or inhibitory interactions on the
millisecond time scale, as may be caused by local feedback or common
inputs (Feldman et al. 1980; Kirkwood
1979
; Perkel et al. 1967
). A methodological
limitation of single electrode recordings is the inability to
discriminate two spike shapes at once, which imposes a central "dead
time" of 1-2 ms duration on their cross-correlogram. Very short-term
interactions between those 14 neuron pairs could therefore have been
missed. That aside, no significant peaks or troughs were detected in
the cross-correlograms plotted on this scale, using data from either
one- or two-electrode recordings (Fig. 3C).
INTERMEDIATE TIME SCALE INTERACTIONS (20 MS BINS, 50 TO 300 MS PEAKS). The most common patterns observed in cross-correlograms plotted on this time scale were either a flat histogram (8/32) or a small ripple with a periodicity similar to the cardiac interval (19/32) (Figs. 3C and 4, A and B). In 5/32 cases, however, a significant peak was observed spanning the origin (Fig. 4C). In two cases, the relation was strong, such that the synchronous firing amounted to 13.0 and 13.6% of the two neurons' mean activity. These two cases were found in the same animal and included one common neuron (all 3 neurons were proven bulbospinal). Three other neuron pairs showed significant peaks on this time scale that were much weaker (synchronous activity amounting to 7.7, 3.6, and 2.8% of mean activity in each case). When expressed as a percentage of the individual neurons' spike activity, the extra spikes attributable to synchrony amounted to 8.7 ± 2.4% (range 2-26%, n = 10) of their mean activity.
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SYNCHRONY OF CARDIAC- AND NONCARDIAC-RELATED ORIGINS.
Synchrony between neurons on the 10 to 100 ms time scale could be due
either to the known common influence of arterial baroreceptors or to
common influences of other, unknown sources. Rhythmic influences would
be expected to produce a repeating pattern on the cross correlogram
(Moore et al. 1970). To clarify the origin of these patterns, every neuron's activity was plotted in the form of a two-dimensional matrix cross-correlation histogram. In this display, each spike occurrence was plotted on two axes: on the abscissa in its
time relation to trigger spikes fired by the companion neuron (as in a
basic cross-correlogram) and in its time relation to the
cardiac cycle on the ordinate (as in a pulse-triggered correlogram;
Fig. 5). Correlations due to common
inputs with a cardiac periodicity then show up as lines of increased
count in the direction of the two axes' common time vector
(diagonally, bottom left to top right, Fig. 5,
C and D). This was the case for all 19 neuron
pairs whose basic cross-correlation showed the "repeating ripple"
pattern noted in the preceding text. Horizontal lines recurring at
specific times in the cardiac cycle axis reflect the cardiac
periodicity of the "response" neuron (Fig. 5, B and C). Any synchrony between the unit pair that is
independent of the cardiac cycle will show up as a vertical
line (Fig. 5D). All five of the unit pairs that had central
peaks in the intermediate time-scale cross-correlogram showed this
latter type of correlation, indicating synchrony due to common,
nonbaroreceptor inputs. No other unit pairs showed this pattern.
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LONG TIME SCALE INTERACTIONS (PEAKS OF MORE THAN 1 S
DURATION).
Where 200 ms binwidths were employed, most neuron pairs showed a flat
cross-correlation function (Fig. 4D). In 3/32 pairs, however, repetitive peaks of 4 to 6 s cycle period showed up in their
cross- and autocorrelograms (Fig. 4E). It was presumed to reflect synchrony due to common inputs related to the central respiratory cycle, which are known to affect the firing patterns of
subretrofacial neurons (McAllen 1987). No
respiratory-related trigger signal was recorded in these experiments,
however, so this idea was not directly tested.
Reversible baroreceptor denervation
Five neuron pairs were recorded under conditions in which phasic baroreceptor inputs could be removed by maintaining the carotid sinus at constant pressure after section of the contralateral sinus nerve and both vago-aortic trunks. In these cases, the baroreceptor-related activity in the unit pulse histogram and in the cross-correlograms was absent or very small (data not shown). No other synchronizing influences became evident under these conditions other than the presumed respiratory-like synchrony with a period of several seconds, which became stronger in three of these five cases (Fig. 4E).
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DISCUSSION |
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This study provides new information on the firing properties of
the main bulbospinal neuron group that supports basal sympathetic vasomotor tone (Dampney 1994; Guyenet
1990
; Kumada et al. 1990
; Lipski et al.
1996
). In cats, these cells are concentrated in the
subretrofacial nucleus (McAllen 1986
; Polson et
al. 1992
). These sympathetic premotor neurons were selected by
established criteria: by their location, by their inhibitory response
to baroreceptor activation, and in most cases by the possession of an
axonal projection to the spinal cord with a conduction velocity in the
appropriate range (Coote and Macleod 1984
and cf.
Barman and Gebber 1985
; Brown and Guyenet
1985
; Guyenet 1990
; Kanjhan et al.
1995
; Kumada et al. 1990
; Lipski et al.
1996
; McAllen 1986
). We deliberately did not
select them with regard to a temporal correlation between their
activity and subsequent bursts in sympathetic nerve activity (e.g.,
Barman and Gebber 1997
) because we wished our sample to be representative of this premotor neuron population as a whole.
The purpose of this study was to examine the correlations between
the firing patterns of pairs of sympathetic premotor neurons so as to
shed light on how their tonic activity, and thus vasomotor drive, may
be generated. This approach has been used with good effect to analyze
respiratory drive pathways (e.g., Sears and Stagg 1976;
Vaughan and Kirkwood 1997
). We sought evidence both for
local synaptic interactions, which might indicate that subretrofacial neurons participate in a local generator network, and for
rhythmic, synchronizing inputs that might suggest that the
subretrofacial nucleus transmits the output from a dynamically coupled
network oscillator of the type proposed to generate sympathetic drive (Gebber 1990
).
Evidence for synaptic interactions between subretrofacial neurons
If subretrofacial neurons are themselves constituent parts of a
brain stem oscillator circuit, they should show evidence of interactions of a strength and time course appropriate to support oscillatory behavior. Such interconnections have been inferred for
other neuron populations, most clearly where their cross-correlogram shows a sharp (typically 0.5 to 2 ms wide) paracentral peak centered 1-5 ms before or after the trigger time (Abeles 1982;
Feldman et al. 1980
; Kirkwood 1979
;
Perkel et al. 1967
). This pattern is generally
interpreted as evidence that one neuron excites the other after a short
delay (or possibly that both are excited, at slightly different
latencies, by a common input). They have been found commonly for pairs
of adjacent respiratory or reticular neurons (Feldman and Speck
1983
; Feldman et al. 1980
; Long and Duffin 1984
; Schulz et al. 1985
). They were also
found to be present in a substantial proportion of ventrolateral
medullary neuron pairs, selected on the basis of their
"sympathetic-related" activity (Barman et al. 1982
;
Gebber et al. 1987
).
No significant short time scale correlations of that type were found
here. This sharp discrepancy with the findings of two apparently
similar studies (Barman et al. 1982; Gebber et
al. 1987
) is surprising, especially since the paracentral
cross-correlogram peaks identified in their studies were prevalent,
prominent, and obvious. If such strong interactions had been present
between the neurons studied here, they would not have been missed. It seems unlikely that the animals' physiological states differed grossly
enough to explain such different findings. In both cases, blood
pressure was well maintained, and sympathetic vasomotor nerve discharge
showed the typical bursting pattern. But we believe that a likely
explanation for the difference is that the neuronal populations sampled
were not the same. Gebber and colleagues (Barman et al.
1982
; Gebber et al. 1987
) selected medullary
neurons on the basis of "sympathetic-related activity," whereas
ours were selected by the generally accepted criteria for sympathetic
premotor neurons (see preceding text). While sympathetic-related
activity is a property shown by a proportion of premotor neurons
(Barman and Gebber 1985
, 1997
; also limited data from
this study), it is also shown by propriobulbar and other neuronal
populations as well (Barman and Gebber 1982
, 1997
;
Varner et al. 1988
). Since spinal axons were not
verified in the neuron pairs showing short time scale correlations
(Barman et al. 1982
; Gebber et al. 1987
), it is possible that they were not premotor neurons. On the basis of our
sample of identified sympathetic premotor neurons, we are forced to
conclude that such short-term interactions are not common or obvious in
this neuronal population.
Several factors limit this negative conclusion. First, the connections
might be weak, and require longer data samples for detection. Second,
the synaptic responses might have been dispersed over time (e.g., if
they were mediated by non-amino acid neurotransmitters), again causing
the response to fall below detection levels (Kirkwood 1979; Moore et al. 1970
). Third, their
interconnections could have been rare or selective and thus been missed
by our sample. Such interconnections have been reported to be
prevalent, for example, between adjacent medullary respiratory neurons
in cats (Feldman et al. 1980
; Long and Duffin
1984
), but rarer (10 vs.
40%) between pairs separated by
2-4 mm (Vachon and Duffin 1978
). But we found no
evidence for interactions of this type between subretrofacial neuron
pairs, whether recorded from one electrode or from two separated by up
to 250 µm.
Evidence for common synchronizing inputs
Our analysis focuses on the evidence for synchronizing influences
other than those attributable to known sources such as arterial baroreceptors. This is first because we are interested in defining the
nature of excitatory drive to subretrofacial neurons. The baroreceptor-derived input is inhibitory, mediated by GABAergic inhibitory synapses (Sun and Guyenet 1985) on
sympathetic premotor neurons themselves (Dembowsky and McAllen
1990
; Lipski et al. 1996
). Shared inhibitory as
well as excitatory inputs can cause cross-correlation peaks
(Moore et al. 1970
). A second reason is that the
postulated oscillators driving sympathetic nerve activity are able to
function independently of baroreceptor signals (Gebber 1980
,
1990
; Kocsis 1995
; Kocsis et al.
1990
; Taylor and Gebber 1975
). Whether the
proposed oscillator circuits are wholly or partly independent of
baroreceptor signals, or even if they drift between those two states,
their influence should be detectable as a baroreceptor-independent
source of synchrony. Baroreceptor-independent synchrony should
therefore be detectable in the subretrofacial neuron population if such
oscillator circuits drive them. Respiratory-related drive to
subretrofacial neurons has been studied elsewhere (Haselton and
Guyenet 1989
; McAllen 1987
) and appears to be
relatively minor unless respiratory drive is artificially raised.
Moreover, its periodicity is an order of magnitude below the
oscillation frequencies proposed to drive sympathetic tone
(Gebber 1990
).
The following calculation uses our measures of the prevalence and strength of synchrony between subretrofacial neuron pairs to estimate the upper limit of its effect on the overall activity of this premotor neuron population. Certain simplifying assumptions are made but, as discussed in Effects of simplifying assumptions, their effects are likely to be small or to result in an overestimate of the synchronous drive to subretrofacial neurons.
Calculation of the effect of synchronizing inputs on subretrofacial neuron population activity
If we consider there to be N independent (i.e.,
uncoupled over the time of the test) synchronizing sources, each of
which gives synaptic connections to a proportion P of the
subretrofacial neuron population, the probability that a randomly
selected neuron pair receives any one common input is then
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The probability that any single subretrofacial neuron receives such an
input would then be
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Effects of simplifying assumptions
The effects of the following assumptions need to be considered. 1) Equal values for P: if P values were inhomogeneous, the summed probability of finding a correlated subretrofacial neuron pair (0.156) would be achieved from fewer independent sources (lower N). 2) Independence of sources: any coupling of activity between sources (e.g., coupled oscillators) would again effectively reduce the estimated value of N. In both cases this would tend to lower our estimate of the contribution of synchronizing sources to subretrofacial population activity. 3) Random sampling of subretrofacial neuron pairs: selecting neurons close together may have increased the chance of finding a correlation. If so, compensation for this effect would again cause us to lower our estimate of the synchronous contribution to subretrofacial neuron population activity. 4) Attribution of synchrony solely to excitatory inputs: any contribution to synchrony from shared inhibitory inputs would also lower the estimate of the contribution of common excitatory inputs.
On the other hand, it is possible that some neuron pairs that we considered to show no synchrony did in fact do so at a level below our detection threshold (ca. 2%). If so, this would increase our estimate of the contribution of synchronous inputs to subretrofacial neuron population activity although the low strength of such inputs would lessen the error. The additional effect of missing one such neuron pair, showing 2% of synchronized spikes due to a single common input, may be calculated as follows.
The probability of this input reaching two subretrofacial neurons (P2) may be taken as 1 in 32 (0.031), and so its probability of reaching one subretrofacial neuron (P) would be 0.177. The effect on the subretrofacial population activity would then be 0.177 × 0.02 = 0.0035 (i.e., 0.35%). The estimated number of independent sources needed to account for 50% of subretrofacial neuron population activity would then be reduced from 216 to 209. These effects would be greater, however, if we postulate that more than one source was responsible.
Finally, if more than one common synchronizing input was needed to give
a detectable level of spike synchrony between subretrofacial neuron
pairs, this would imply a higher value of P but a lower value of S. In the case where two common inputs were
required for detection, the probability of finding these would be
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Inferences from calculation
Common, synchronizing inputs to subretrofacial neurons are likely to account for only a minor percentage of the spiking activity of this neuron population. The calculations are compatible with synchronizing (including oscillatory) inputs, providing a greater share of the drive to subretrofacial neurons only if those inputs are multiple, dispersed and weak. The assumptions made are unlikely to have affected these conclusions.
Neurons with sympathetic-related activity
One question that arises from the calculations above is how they
relate to the finding of Barman and Gebber (1997) that
around 25% of the neurons in this region of the ventrolateral medulla show sympathetic related activity. This feature is demonstrated by a
positive spike-triggered average (a time-locked wave of averaged sympathetic nerve activity at least 3 times the amplitude of one generated by a "dummy" trigger sequence) (Barman and Gebber
1985
). Presumably two subretrofacial neurons that have
sympathetic-related activity should also show some enhanced tendency to
fire in time with each other. The present data are entirely consistent
with such a view. If one neuron in four shows this type of activity, then two randomly selected neuron pairs in a sampled population of 32 would be expected to share that feature. In fact we found five
correlated pairs in our sample of 32. The higher than expected number
could have been a consequence either of nonrandom selection (we sampled
subretrofacial neurons obeying set criteria and located close to each
other) or perhaps the existence of yet other sources of synchrony.
With regard to the strength of those correlations, however,
it is not possible to compare our measurements with predictions from
spike-triggered averages of sympathetic activity. The analog averages
of sympathetic nerve activity used by Barman and Gebber (e.g.,
1985, 1997
) are not calibrated in a manner that can be related
to ongoing activity or its zero level. This sensitive technique may, in
fact, pick up quite weak correlations.
Subretrofacial neuron ensemble activity and sympathetic drive
The nature of the ensemble of activity conveyed to the spinal cord by the subretrofacial neuron population will be determined not only by the between-neuron correlated activity discussed in the preceding text but also by the spike patterns of individual neurons. For this reason and because they had not previously been documented for this neural population in cats, we studied the firing characteristics of subretrofacial neurons.
About half of the subretrofacial neurons identified in this study fired
with a regular discharge, and their mean firing rates (regular and
irregular groups) were in the range of 1-14 Hz. They evidently fire
more slowly than the analogous, fast-firing neurons in the rat, whose
regular discharge is in the 20-40 Hz range (Guyenet 1990). But in either case, it is not easy to understand how
more than a small percentage of the spike activity of regularly firing neurons could be seconded to the task of transmitting oscillations in
the 2-10 Hz range to the spinal cord. Such a task would best be served
by neurons that fired irregularly at rates comparable to the
frequencies concerned. The bulbospinal neurons that Barman and
Gebber (1985
, 1997
) selected on the basis of
sympathetic-related activity did indeed show such characteristics. It
seems clear, however, that conventional selection criteria used in the
present study have identified a broader neural population, with a more diverse range of firing patterns and generally faster firing rates.
One further possibility we considered is that if subretrofacial neurons
shared a common, limited range of preferred firing frequencies, they
might imprint that frequency band on sympathetic nerve discharge. Their
modal firing intervals covered a broad range, however, without any
obvious clustering around a particular value. They were nearly all
shorter than both the heart period and the reciprocal of the major
(2-6 Hz) frequency component of sympathetic nerve discharge
(Gebber 1990). This possibility therefore seems unlikely
to be a major factor.
While we can make estimates from the present data about the ensemble
activity that the subretrofacial neuron population sends to the cord,
we cannot determine how this is translated into pre- and postganglionic
neuron activity. But the low level of synchrony between subretrofacial
neurons contrasts starkly with the strongly synchronous activity seen
in sympathetic nerves (McAllen and Malpas 1997). One is
led to consider the possibility that while tonic vasomotor drive is
largely transmitted by subretrofacial neurons (Dampney
1994
), the rhythmic component of sympathetic nerve activity may
have other origins.
Conclusion
Subretrofacial neurons, whose activity supports most basal
vasomotor tone, are not interconnected in the same way as (e.g.) certain respiratory premotor neurons. Common synchronizing, possibly oscillatory, inputs have some influence on the activity of this neural
population but are unlikely to provide the dominant source of
excitatory drive that maintains these cells' tonic discharge, except
in the case that they embody several hundred independent sources.
Overall it appears that the sources of drive that maintain subretrofacial neuron activity, be they synaptic (Lipski et al. 1996) or due to intrinsic cellular properties (Guyenet
1990
), are asynchronous or highly dispersed.
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ACKNOWLEDGMENTS |
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The assistance of Dr. F. Edwards with calculating the estimates of the number and strength of synchronizing inputs is gratefully acknowledged.
This work was supported by Australian National Health and Medical Research Council Grant 983001 and the National Heart Foundation of Australia.
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FOOTNOTES |
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Address for reprint requests: R. M. McAllen (E-mail: r.mcallen{at}hfi.unimelb.edu.au).
Received 11 September 2000; accepted in final form 18 December 2000.
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REFERENCES |
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