Download Mechanical Response Properties of A and C Primary Afferent

J Neurophysiol 88: 3021–3031, 2002;
10.1152/jn.00029.2002.
Mechanical Response Properties of A and C Primary Afferent
Neurons Innervating the Rat Intracranial Dura
DAN LEVY AND ANDREW M. STRASSMAN
Department of Anesthesia and Critical Care, Beth Israel Deaconess Medical Center and Harvard Medical School,
Boston, Massachusetts 02215
Received 14 January 2002; accepted in final form 26 July 2002
Major blood vessels of the intracranial meninges receive a
predominantly small-fiber sensory innervation from the trigem-
inal ganglion as well as the upper cervical dorsal root ganglia
(Feindel et al. 1960; Keller et al. 1985; Mayberg et al.1984;
O’Connor and van der Kooy 1986; Penfield and McNaughton
1940). Stimulation of meningeal blood vessels in neurosurgical
patients can evoke painful sensations that are typically referred
to a region of the trigeminal dermatome (Fay 1935; Feindel et
al. 1960; Ray and Wolff 1940) and are abolished by lesion or
blockade of the trigeminal nerve or ganglion (Penfield and
McNaughton 1940). Pain is the only sensation that can be
evoked by stimulation of the intracranial meninges, regardless
of whether the stimulus is electrical, mechanical, thermal, or
chemical (Ray and Wolff 1940). Because meningeal blood
vessels are the only intracranial sites from which pain can be
evoked, headaches that accompany intracranial pathologies
(e.g., meningitis, subarachnoid hemorrhage, tumor) are thought
to result from meningeal stimulation and consequent activation
of meningeal sensory fibers (Wolff 1963). Migraine headache,
although not accompanied by any detectable pathology, shares
certain clinical features with headaches of intracranial origin,
and has also been postulated to result from activation of the
meningeal sensory innervation (reviewed in Strassman and
Raymond 1997).
Mechanosensitivity in particular seems to be important in
intracranial headaches as well as migraine. Both are characterized by an extreme sensitivity to actions such as coughing,
straining, or sudden head movement (Blau and Dexter 1981),
which would all be expected to produce a transient alteration in
the distribution of mechanical forces within the intracranial
space. In addition, the throbbing quality that is characteristic of
migraine has typically been attributed to arterial pulsation,
which might produce pain either through stretching/displacement of peri-arterial tissue or through the generation of pressure pulses that propagate throughout the closed intracranial
space. The headache that develops after lumbar puncture (post
dural puncture headache) has a strict positional dependence
that is indicative of a gravity-induced tension or displacement
of intracranial tissue (Wolff 1963). Each of these clinical
phenomena point to the presence of mechanosensitive neural
elements within the intracranial space that can, under some
circumstances, contribute to clinically occurring headache.
Peripheral and central neurons in the meningeal sensory
pathway have been identified by recording unit responses to
Address for reprint requests: A. M. Strassman, Dept. Anesthesia, DA-717,
Beth Israel Deaconess Med. Ctr., 330 Brookline Ave., Boston, MA 02215
(E-mail: [email protected]).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked ‘‘advertisement’’
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
INTRODUCTION
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0022-3077/02 $5.00 Copyright © 2002 The American Physiological Society
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Levy, Dan, and Andrew M. Strassman. Mechanical response properties of A and C primary afferent neurons innervating the rat intracranial
dura. J Neurophysiol 88: 3021–3031, 2002; 10.1152/jn.00029.2002. The
intracranial dura receives a small-fiber sensory innervation from the
trigeminal ganglion that is thought to be involved in some types of
headaches, including migraine. Mechanical response properties of dural
afferent neurons were examined to investigate variation across the population in the properties of threshold, slope, adaptation, and incidence of
mechanosensitivity. Dural afferent neurons were recorded in the trigeminal ganglion of urethan-anesthetized rats and were identified by their
constant-latency response to dural shock. Neurons were classified as fast
A (⬎5 m/s), slow A (5 ⱖ conduction velocity (CV) ⱖ 1.5 m/s), or C
(⬍1.5 m/s), based on response latency to dural shock. Mechanical receptive fields were identified by stroking or indenting the outer surface of the
dura. Stimulus-response curves were obtained from responses to 2-s
constant-force indenting stimuli of graded intensities delivered to the
dural receptive field with a servo force-controlled mechanical stimulator.
The slow A population had the highest percentage of mechanosensitive
units (97%) as well as the highest slopes and the lowest thresholds. Thus
by all three criteria, the slow As had the highest mechanosensitivity.
Conversely, the fast A population had the lowest mechanosensitivity in
that it had the lowest percentage of mechanosensitive units (66%), the
lowest slopes, and the highest thresholds. The C population was intermediate with respect to all three properties but was much more similar to
the slow As than to the fast As. All three fiber classes showed a negative
correlation between slope and threshold. The majority of neurons showed
a slowly adapting response to a maintained 2-s stimulus. Adapting
neurons could be subdivided based on whether the fitted exponential
curve decayed to zero or to a nonzero plateau; the latter group contained
the most sensitive neurons in that they had the lowest thresholds and
highest slopes. Nonadapting neurons generally had lower initial firing
rates than adapting neurons. Fast A neurons exhibited greater and more
rapid adaptation than slow A and C neurons. Neurons with the lowest
slopes, regardless of CV, had relatively rapid adaptation. The more
slowly conducting portion of the C population was distinguished from the
other C neurons by a number of properties: more mechanically insensitive neurons, higher thresholds, and more nonadapting neurons. These
differences in mechanical response properties may be related in part to
differences in membrane currents involved in impulse generation that
have been described in subpopulations of dorsal root ganglion cells.
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D. LEVY AND A. M. STRASSMAN
METHODS
Surgery and electrophysiological recording
Experiments were carried out on male Sprague-Dawley rats (330 –
450 g). Data was obtained from 302 rats, of which 117 were tested
with the mechanical stimulator (see following text). The experimental
protocol was approved by the institutional Animal Care and Use
Committee of the Beth Israel Deaconess Medical center. Rats were
anesthetized with urethan (1.8 g/kg ip, Sigma-Aldrich, St Louis MO)
and were maintained under anesthesia throughout the experiment with
supplemental injections as needed to suppress blink reflexes. Rats
were killed at the end of the experiment by anesthetic overdose or
intravenous bolus injection of 1 M KCl.
Anesthetized rats were placed in a stereotaxic head-holder. A
craniotomy was made to expose the left transverse sinus as well as the
adjacent dura extending ⬃2 mm rostral and caudal to the sinus
(overlying the cerebral and cerebellar cortices, respectively). The
transverse sinus was exposed from the midline laterally ⱖ4 mm. In
some experiments, the exposure was extended to include the entire
sinus, a length of ⬃8 mm (as measured along the curved surface of the
sinus, extending first laterally and then ventrally around the lateral
convexity of the cerebral/cerebellar cortex, to a point just dorsal to the
auditory canal).
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The exposed dura was bathed with a modified synthetic interstitial
fluid (SIF) consisting of (in mM) 135 NaCl, 5 KCl, 1 MgCl2, 5 CaCl2,
10 glucose, and 10 HEPES at pH 7.2.
A second craniotomy was made more anteriorly to allow platinumcoated tungsten microelectrodes to be advanced through the forebrain
into the left trigeminal ganglion, at ⬃2 mm caudal to Bregma, 2–2.5
mm lateral, and 9.5–10 mm below the cortical surface. Single-shock
electrical search stimuli (0.5 ms, 5 mA, 0.5 Hz) were delivered
through bipolar stimulating electrodes (1- to 1.5-mm separation) to the
outer dural surface of the transverse sinus, usually at 3–5 mm from the
midline, which is the region where most of the dural projecting axons
join the sinus in their course from the underlying tentorium. Singleunit recordings were made from dural afferent neurons in the trigeminal ganglion that were identified by their constant-latency response to
the electrical search stimulus (Strassman et al. 1996). Response
thresholds and latencies were mapped at multiple sites to identify the
site associated with the shortest latency response (Strassman and
Raymond 1999). The response latency at this site was used to calculate CV, based on a conduction distance to the trigeminal ganglion of
12.5 mm. Neurons were classified as either C units (CV ⱕ 1.5 m/s),
slow A units (1.5 ⬍ CV ⬍ 5 m/s), or fast A units (CV ⬎ 5 m/s). We
previously referred to these latter two groups as slow and fast A␦ units
(Strassman and Raymond 1999; Strassman et al. 1996), but we are
now omitting the “␦” because the fast A group includes a number of
units that are more properly classified as A␤, according to the CV
criteria of some investigators (see DISCUSSION). Action potentials were
processed with a real-time waveform discriminator (SPS-8701, Signal
Processing Systems, Prospect, South Australia, Australia) and acquired for on- and off-line analysis with the Discovery data-acquisition program (DataWave Technologies, Longmont, CO).
Mechanical stimulation and data analysis
Mechanical receptive fields of dural afferents were mapped by
stroking the dura with blunt forceps and indenting it with von Frey
monofilaments (0.03– 6.9 g, exerting 38 –510 kPa; Stoelting, Chicago,
IL). The 510-kPa filament was the highest intensity used to avoid
damaging the dura or causing subarachnoid bleeding. For quantitative
determination of mechanical stimulus-response functions, graded
stimuli were applied to the dural surface at the lowest threshold site
with a servo force-controlled mechanical stimulator (Series 300B
Dual Mode Servo System, Aurora Scientific, Aurora, Ontario) (Khalsa
et al. 1997; Levy and Strassman 2002). A flat-ended cylindrical plastic
probe was attached to the tip of the stimulator arm. Because the dural
surface is curved, the stimulator was mounted on a universal joint to
allow the probe angle to be made perpendicular to the dural surface at
the stimulation site. One of three probe diameters (0.5, 0.8, or 1.1 mm)
was selected for each neuron, depending on the sensitivity of the
neuron. The smallest probe was used unless the neuron’s baseline
threshold was so low that responses were evoked even at the stimulator’s minimum setting of 2 mN. In this case, to deliver subthreshold
stimuli, one of the larger probes was used (resulting in lower stimulus
pressures). Stimulus intensity is reported in units of force/area (kPa,
where 1 kPa ⫽ 1 mN/mm2). Only one probe was used for each
neuron.
Each stimulus trial consisted of a graded series of square-wave
stimuli (100-ms rise time, 2-s width, 10-s inter-stimulus interval)
delivered in ascending order (Fig. 1). The response to each mechanical stimulus was calculated by subtracting the spontaneous firing rate
from the mean firing rate during the stimulus. The spontaneous firing
rate for each trial was calculated from the 10-s interval preceding the
first stimulus of that trial. The majority of units had low (⬍0.5 Hz), or
no spontaneous firing.
An initial series of stimulus trials were delivered in which stimulus
intensity was systematically varied to determine response threshold,
which was defined as the lowest intensity that evoked a response of
one to two spikes. The baseline stimulus-response curve was then
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electrical stimulation of the intracranial dura in the trigeminal
nerve (Bove and Moskowitz 1997) or ganglion (Strassman et
al. 1996), medullary and upper cervical dorsal horn (Burstein et
al. 1998; Davis and Dostrovsky 1986, 1988a; Kaube et al.
1992; Lambert et al. 1991; Strassman et al. 1986), and the
ventrobasal thalamus (Davis and Dostrovsky 1988b; Zagami
and Lambert 1990). These studies found neuronal responses to
punctate probing and other forms of mechanical stimulation
applied to the intracranial dura, primarily at sites on or near the
dural venous sinuses or middle meningeal artery.
Our initial study of dural afferents used von Frey hairs for
measurement of mechanical response thresholds and demonstrated that these thresholds could be lowered by dural application of inflammatory mediators (Strassman et al. 1996). In
subsequent experiments, to obtain more precise measurements
of mechanosensitivity, we have used a force servo-controlled
mechanical stimulator in place of the von Frey hairs for dural
stimulation. Using this stimulator to study both threshold and
suprathreshold components of sensitization, we observed sensitizing effects on these two response components occurring
separately in individual neurons (Levy and Strassman 2002).
The two patterns of sensitization seemed to be occurring in
separate subpopulations in that the neurons also showed some
differences in their conduction velocities (CVs) and their baseline stimulus-response properties (threshold and stimulus-response slope).
The present study was carried out to examine in more detail
how much these and other baseline response properties vary
across the entire population of dural afferents to provide a
stronger basis for the identification of potential subpopulations.
For this purpose, we have examined the baseline mechanical
response properties of slope, threshold, and adaptation, and the
relationship of these properties to each other, and to CV, in a
much larger sample of dural afferents (including those for
which slope and threshold were described in Levy and Strassman 2002). This information is fundamental to our ongoing
efforts to identify potential subpopulations among the dural
afferents and for understanding the different patterns of modulatory effects exhibited by different groups of neurons.
MECHANICAL RESPONSE PROPERTIES OF DURAL AFFERENTS
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in 10 200-ms bins, was also fitted to a first-order exponential decay,
according to the equation y ⫽ yo ⫹Ae-x/t (Origin 6.0, Microcal
Software). The fit was considered significant if P ⬍ 0.05.
ANOVA with the Fisher PLSD post hoc test was used for comparisons between fiber classes. Slope and threshold showed highly nonnormal distributions, so log values were used for statistical comparisons of slope and threshold. Comparisons between the fiber classes in
the distributions of slope and threshold were made by inspecting the
population histograms and comparing the proportion of neurons with
values above or below selected criterion values (␹2). Values for slope
and threshold are reported as median ⫾ inter-quartile range (IQR).
Ward’s method of hierarchical cluster analysis was performed with
slope, threshold, and CV as cluster variables, using JMP 3.1 (SAS
Institute). Other statistical analyses were carried out with StatView
5.0 (SAS Institute).
RESULTS
FIG. 1. A: mechanical stimulation paradigm for determination of stimulusresponse functions. Chart recorder-type display of discharge of a dural afferent
neuron is shown with concurrent recordings of force output from mechanical
stimulator during 3 stimuli of increasing intensity (threshold, 2 and 4 times
threshold) delivered to the lowest threshold spot of the neuron’s dural receptive
field. Stimulus intensity is reported in units of pressure (kPa), which was
calculated by dividing force by the tip area of the cylindrical probe. B:
recording of displacement resulting from the third stimulus (64 kPa) in A.
During the constant-force stimulus, the resultant displacement shows a very
slight, gradual increase throughout the duration of the stimulus. This “creep”
reflects tissue relaxation and is characteristic of constant-force indentation
applied to any viscoelastic material.
determined by delivering a stimulus trial that consisted of four stimuli:
a subthreshold (⬃0.5 times threshold), threshold, and two suprathreshold stimuli (usually 2 and 4 times threshold). Stimulus trials
consisting of these four stimuli were delivered at least three times,
with a 10-min inter-trial interval. The slope of the stimulus-response
curve was calculated by performing a linear regression analysis on the
responses to the threshold and the two suprathreshold stimuli, using
the mean responses from three trials. The subthreshold stimulus was
included for detection of possible decreases in threshold induced by
subsequent application of sensitizing agents (e.g., Levy and Strassman
2002), which are not described in the present report.
One of the suprathreshold responses was also used for calculation
of an adaptation index (AI), which was defined as the proportion of
total firing that occurred during the initial 400 ms of the 2-s stimulus
(modified from Knowlton and Larrabee 1946). The response, plotted
J Neurophysiol • VOL
A total of 454 units were recorded from the trigeminal
ganglion that exhibited a constant-latency response to dural
shock (Strassman et al. 1996) and were sufficiently wellisolated to allow recording of responses to mechanical stimulation. Units were subdivided into three fiber classes, based on
the conduction velocity between the trigeminal ganglion and
the electrical stimulation site on the dura: fast A (ⱖ5 m/s),
slow A (1.5 ⬍ CV ⬍ 5 m/s), and C (ⱕ1.5 m/s). Mechanical
receptive fields were located by stroking the outer surface of
the dura with a blunt probe and indenting it with von Frey
hairs. Receptive fields were primarily on the dura overlying or
immediately adjacent to the ipsilateral transverse sinus (Strassman and Raymond 1999; Strassman et al. 1996).
A mechanical receptive field could not be found for 29%
(133/454) of the units that responded to dural shock. This
percentage was smaller in experiments in which the entire
length of the transverse sinus was exposed (20%, 54/265) as
compared with experiments in which only the medial half of
the sinus was exposed (42%, 79/189) (see METHODS). Thus
doubling the area of the exposed dura reduced the percentage
of units with no identifiable mechanical receptive field by
approximately one-half.
The percentage of these mechanically insensitive units differed in the three fiber classes (Fig. 2, including only experiments with a complete exposure of the transverse sinus;
␹2 test for proportion of mechanically insensitive units: slow
A ⬍ C, P ⫽ 0.0077; C ⬍ fast A, P ⫽ 0.01). This percentage
was close to 0 among the slow A’s (3%, 2/59), but it increased
sharply among neurons with CVs ⬎5 m/s (33%, 33/99). This
difference in the percentage of mechanically insensitive units
was the basis for subdividing the A-fiber population at this CV
(as was done originally in Strassman et al. 1996 for a smaller
sample of 45 units, which are included in Fig. 2). The percentage of mechanically insensitive units was also somewhat
higher among C units (18%, 19/107) as compared with slow A
units, particularly among units ⬍1 m/s.
Stimulus-response relationships: slope and threshold
Responses to 2-s constant-force stimuli were used to obtain
stimulus-response curves of 120 mechanosensitive units (19
fast A, 47 slow A, and 54 C). The plots in Fig. 3 show that, in
each fiber class, some units had relatively low thresholds and
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Incidence of mechanosensitivity
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D. LEVY AND A. M. STRASSMAN
Adaptation
Adaptation was studied by examining discharge rate (averaged in 200-ms bins) during a maintained 2-s stimulus,
using stimulus intensities of three to four times threshold.
FIG. 2. A: histogram of conduction velocities of mechanically sensitive and
insensitive dural afferent neurons (neurons with and without a mechanical
receptive field). Bin width: 1 m/s; n ⫽ 265 units. B: percentage of mechanically insensitive units in different conduction velocity ranges, compiled from
the data in A. The sharp difference between A units above and below 5 m/s
shown in these plots was the basis for subdividing the A-fiber population at this
conduction velocity (CV). These plots only include units from experiments
with a complete exposure of the transverse sinus (see RESULTS).
steep slopes, whereas others had high-thresholds and flat
slopes. The plots also illustrate that the fast A population had
the highest proportion of units with high thresholds and flat
slopes, whereas the slow A population had the lowest proportion of such units. These relationships are illustrated more
quantitatively in Fig. 4, which shows the distribution of thresholds and slopes for each of the three fiber classes.
The three fiber classes differed significantly in the distribution of slopes and, to a lesser extent, thresholds (Fig. 4, A and
B). Fast A units had the lowest slopes, while slow A’s had the
highest (0.18 ⫾ 0.15, 0.25 ⫾ 0.24, and 0.44 ⫾ 0.30 Hz/kPa,
median ⫾ IQR for fast A, slow A, and C, respectively; slow
A ⬎ C, P ⬍ 0.005; C ⬎ fast A, P ⬍ 0.001, by ANOVA of log
slope). The majority (74%) of fast A units had slopes ⬍0.06
Hz/kPa, whereas only 11% of slow A and 30% of C units had
slopes below this level (P ⬍ 0.05, ␹2). Conversely, the majority of slow A (81%), but not fast A (21%) or C units (46%), had
slopes ⬎0.12 Hz/kPa (P ⬍ 0.0005, ␹2).
The relationship among the three fiber classes was reversed
with respect to the distribution of thresholds: slow A units had
the lowest thresholds, whereas fast A’s had the highest (41 ⫾
119, 10 ⫾ 16, and 16 ⫾ 34 kPa, median ⫾ IQR for fast A, slow
A, and C, respectively; fast A ⬎ C ⬎ slow A, P ⬍ 0.05, by
J Neurophysiol • VOL
FIG. 3. Stimulus response curves for fast A, slow A, and C units as
determined from the stimulus paradigm shown in Fig. 1. Note that only the
initial portion of the stimulus-response relationship was examined in this study
(up to ⬃4 times threshold).
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ANOVA of log threshold). The slow A population had a
significantly higher percentage of units with thresholds ⬍30
kPa (87%) than the fast A (47%) and C (64%) populations
(P ⬍ 0.01, ␹2).
Figure 4C illustrates that there was a strong tendency for
units with lower thresholds to have higher slopes and that this
negative correlation was present within each of the three fiber
classes (correlation coefficient for log slope versus log threshold, r ⫽ ⫺0.856; P ⬍ 0.0001). Thus insofar as high slopes and
low thresholds can both be regarded as indications of high
sensitivity, units that exhibited high sensitivity with respect to
one parameter also tended to have high sensitivity with respect
to the other. In the plots of slope versus threshold (Fig. 4C), the
most sensitive units occupy the upper left quadrant while the
least sensitive units occupy the lower right quadrant. The slow
A population had the highest sensitivity overall, while the fast
A population had the lowest.
MECHANICAL RESPONSE PROPERTIES OF DURAL AFFERENTS
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The majority of units (108/136, 79%) showed an adapting
response pattern in which discharge rate was highest during
the initial 200 – 400 ms of the stimulus and then declined
(e.g., Fig. 5, A and B). The remainder of units showed a
nonadapting response pattern in which firing rate was maintained or, in a few cells, showed a slight increase during the
2-s stimulus (e.g., Fig. 5C). Nonadapting responses were
especially common among the slowest C units (7/15, or
FIG. 5. Examples of different adaptation patterns, illustrated in histograms of discharge rate during single trials of the 2-s stimulus (binwidth: 200 ms). A: adaptation with exponential decay to 0. B: adaptation
with exponential decay to a positive plateau (the value of yo in the
equation y ⫽ yo ⫹Ae-x/t). C: nonadapting responses. t, time constant
of decay.
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FIG. 4. Histograms of slope (A) and threshold (B) and log plots of slope vs. threshold (C) for fast A, slow A, and C units. C,
bottom: C units with CV ⬎0.8 m/s are represented (E) to show that the subgroup of C units with high thresholds (⬎50 kPa) have
low CVs.
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D. LEVY AND A. M. STRASSMAN
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FIG. 6. A: histograms of adaptation index (AI), defined as the proportion of
the total firing that occurred during the initial 400 ms of the 2-s stimulus. ■,
units whose response was well fit by a first-order exponential decay (P ⬍
0.05). B: histograms of time constants for those units with exponential decay
(units represented by ■ in A).
Cluster analysis
The preceding analyses first grouped the neurons according
to fiber class (CV) and then compared the groups. However,
there was considerable heterogeneity within each fiber class.
To further investigate the presence of subpopulations, a cluster
analysis was carried out using CV, slope, and threshold as
cluster variables. The neurons were divided into six clusters as
illustrated in the plot of threshold versus CV shown in Fig. 7.
Cluster 3 consisted of predominantly fast A units with highthresholds (and correspondingly low slopes). Clusters 1 and 5
were predominantly slow A units with intermediate and low
thresholds, respectively. Clusters 2, 4, and 6 were predominantly C units with high, intermediate, and low thresholds,
respectively.
The clusters showed no systematic differences in AI but did
show some trends in the distribution of different adaptation
patterns. Clusters 1, 3, and 5 were predominantly adapting
neurons. Most of the neurons that showed adaptation to a
nonzero plateau were in clusters 1 and 5. Clusters 2, 4, and 6
contained both adapting and nonadapting neurons.
The clusters were also examined to determine the distribution of a subset of neurons that had been classified in a previous
study based on the pattern of PKA-dependent mechanical
sensitization (Levy and Strassman 2002). That study described
two groups of neurons that showed sensitizing effects predominantly on either their threshold (TH group, n ⫽ 15) or suprathreshold (STH group, n ⫽ 10) responses. That study also
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47%, of units with CV ⬍0.45 m/s). Nonadapting neurons
had relatively low peak firing rates, compared with adapting
neurons (Fig. 5); peak firing rates ⬎20 Hz were only found
in adapting neurons, at response onset.
In the majority of adapting units (88/108, 81%), the response
was well-fit by a first-order exponential decay (P ⬍ 0.01). A
subset of the neurons with exponential adaptation (31/88, 35%)
exhibited a response pattern in which the fitted exponential
curve did not decay to zero but rather decayed to a positive
plateau (the value of yo in the equation y ⫽ yo ⫹Ae-x/t). Such
responses might be described as having both an adapting and a
nonadapting component (e.g., Fig. 5B). Neurons with this
response pattern had the highest sensitivity in that they had
higher slopes and lower thresholds than other units (slope:
0.31 ⫾ 0.53 vs. 0.14 ⫾ 0.34 Hz/kPa; threshold: 10.2 ⫾ 15.4 vs.
18.3 ⫾ 33.1 kPa; median ⫾ IQR; P ⬍ 0.05 for t-tests on log
slope and log threshold). Slow As had the highest percentage
of units with this response pattern (35% vs. 17% of Cs and
11% of fast As).
Fast A units generally showed greater and more rapid adaptation than slow A and C units. No fast As were nonadapting
(as compared with 21% of slow As and 26% of Cs). Adaptation
was complete (i.e., firing had declined to 0) by the final 400 ms
of the 2-s stimulus in 53% (10/19) of fast A units but only 12%
(6/52) of slow A and 11% (7/65) of C units. A subset of fast A
units showed a particularly rapid adaptation pattern, in which
all firing occurred during the first 200 ms of the stimulus (e.g.,
Fig. 5A, 1st graph). Such a rapidly adapting response was
exhibited by 32% of fast A units, but no slow A or C units.
These rapidly adapting units were among the neurons with the
lowest mechanosensitivity, in that they had low slopes (⬍0.025
Hz/kPa) and high thresholds (⬎20 kPa). They mainly occupied
the upper end of the fast A range (⬎9 m/s).
Although this extremely rapid adaptation was only found
among fast As, the association between low slopes and adaptation held across fiber classes. Almost all units (16/17) with
low slopes of ⬍0.05 Hz/kPa, regardless of fiber class, had
relatively short adaptation time constants (⬍0.5 s). This lowslope group included eight fast A, four slow A, and five C
units.
To better quantify the degree of adaptation, an AI was
calculated for each neuron, defined as the proportion of total
firing that occurred during the initial 400 ms of the 2-s stimulus
(Fig. 6A). Thus a rapidly adapting response in which all firing
occurs in the first 400 ms has an AI of 1.0, whereas a nonadapting response in which firing is evenly maintained
throughout the stimulus has an AI of 0.2 (⫽400 ms/2 s). The
䡲 in Fig. 6A represent the units whose responses were well-fit
by a first-order exponential decay. The time constant of decay
for those units with an exponential decay is shown in Fig. 6B.
Figure 6 shows that fast A units had larger AIs and shorter time
constants than slow A and C units [mean AI of 0.64 ⫾ 0.32 for
fast A vs. 0.37 ⫾ 0.15 for slow A (P ⬍ 0.0001) and 0.35 ⫾
0.17 for C units (P ⬍ 0.0001); mean time constant of 0.19 ⫾
0.20 s for fast A vs. 0.52 ⫾ 0.34 s for slow A (P ⬍ 0.0005) and
0.67 ⫾ 0.33 s for C units (P ⬍ 0.0001)]. Figure 6A also shows
that the AI was generally larger for exponential than for nonexponential units.
MECHANICAL RESPONSE PROPERTIES OF DURAL AFFERENTS
3027
FIG. 7. Log plot of threshold vs. CV to illustrate the division of the neurons
into 6 groups by hierarchical cluster analysis. The cluster variables were slope,
threshold, and CV.
found that the TH and STH neurons also showed some differences in their CVs and baseline mechanical response properties. Consistent with those findings, the TH and STH neurons
showed a differential cluster distribution, in that 80% of the
STH neurons were in clusters 1 and 4, while 80% of the TH
neurons were in clusters 2, 3, 5, and 6.
DISCUSSION
Dural afferents were examined to investigate the degree of
variation across the population, and the relation to CV, of the
mechanical response properties of threshold, slope, adaptation,
and incidence of mechanosensitivity. These properties showed
a large variation that was partly related to conduction velocity.
In general, fast A neurons differed markedly from slow A and
C neurons, whereas the differences between the slow A and C
populations were more subtle.
The slow A population had the highest percentage of mechanosensitive units as well as the highest slopes and the lowest
thresholds. Thus by all three of these criteria, the slow As had
the highest mechanosensitivity. Conversely, the fast A population had the lowest mechanosensitivity in that it had the
lowest percentage of mechanosensitive units, the lowest slopes
and the highest thresholds. The C-fiber population was intermediate with respect to all three properties but was much more
similar to the slow As than to the fast As. All three fiber classes
showed a strong negative correlation between slope and threshold.
Fast A neurons exhibited greater and more rapid adaptation
than slow A and C neurons. Neurons with the lowest slopes,
regardless of CV, had relatively rapid adaptation. Neurons with
both an adapting and a nonadapting response component (adaptation to a non-0 plateau) were the most sensitive neurons in
that they had the lowest thresholds and highest slopes. The
more slowly conducting portion of the C population was dis-
J Neurophysiol • VOL
Subdivision of the A-fiber population
The 5-m/s cutoff used in this study for subdividing the A
fibers was made initially based on the observation of a sharp
increase in the percentage of mechanically insensitive neurons
among neurons with CVs ⬎5 m/s (Strassman et al. 1996). This
observation was confirmed and extended in the present study to
include differences in other mechanical response properties as
well. A number of other studies of primary afferent nociceptors
have also observed distinctive properties among the most
slowly conducting portion of the A␦ population that prompted
them to treat these neurons as a separate group from the faster
conducting A␦ fibers (Campbell and Meyer 1986; Hoheisel and
Mense 1987; Ikeda et al. 1997; Liang and Terashima 1993;
Liang et al. 1995; Lynn et al. 1995).
In previous studies (Strassman and Raymond 1999; Strassman et al. 1996), we considered the fastest dural fibers to fall
within the upper limit of the A␦ range (22–25 m/s) as commonly defined for other primary afferent populations in the rat
(e.g., Leem et al. 1993). However, some studies have found
that A␤ conduction velocities in the rat are slower than in other
species, and have demarcated the A␦/A␤ border as low as
12–15 m/s (Lynn and Carpenter 1982; Waddell et al. 1989).
Some variation between studies may be attributable to age
differences (Birren and Wall 1956) as well as differences
between distal and proximal portions of individual nerve fibers
(Harper and Lawson 1985; Waddell et al. 1989). In addition,
trigeminal primary afferents may have somewhat slower CVs
than their spinal analogs, although we know of no study that
has reported the CVs of A␤ fibers or defined the A␦/A␤ border
for the rat trigeminal system. Consequently, we have not attempted to define this border for the dural afferents and instead
simply note that the slow A group includes the slower conducting portion of the A␦ population, whereas the fast A group
contains the faster A␦ fibers as well as a number of fibers that
would be classified as A␤ according to the CV criteria of some
investigators.
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tinguished from the other C neurons by a number of properties:
more mechanically insensitive neurons, higher thresholds, and
more nonadapting neurons.
In a previous study of mechanical sensitization in dural
afferents, we found different patterns of sensitization occurring
in different neurons after application of cAMP (Levy and
Strassman 2002). Some neurons showed primarily a lowered
response threshold, whereas other neurons showed primarily
an increase in their suprathreshold responses. These two effects
appeared to be occurring in different subpopulations because
the two groups also showed some differences in baseline
mechanical response properties and CV. In the present study,
which included a much larger sample of neurons, cluster analysis was carried out to further examine the heterogeneity across
the population with respect to CV, slope, and threshold. The
two subsets of neurons that had been defined in the previous
study based on their patterns of sensitization showed a differential cluster distribution, further supporting the possibility that
they constitute different subpopulations.
3028
D. LEVY AND A. M. STRASSMAN
Comparisons with afferents from other tissues
J Neurophysiol • VOL
Mechanisms determining mechanical response properties
Mechanical response properties might be influenced by the
characteristics of the mechanical transduction process as well
as the process of impulse generation by voltage-gated currents.
There is currently no information about how the properties of
mechanical transduction elements might differ among different
groups of nociceptive or small-diameter sensory neurons.
However, a number of voltage-gated currents are differentially expressed within subpopulations of sensory neurons,
including currents that are thought to affect impulse generation
or the capacity for repetitive firing. Currents that show such
differential expression within populations of small-diameter
sensory neurons include the tetrodotoxin-resistant (TTX-R)
voltage-gated sodium currents (Akopian et al. 1996; Cardenas
et al. 1997; Gold et al. 1996a; Tate et al. 1998), the hyperpolarization-activated cation current IH (Scroggs et al. 1994;
Petruska et al. 2000), a number of transiently activated (IA) or
sustained (IK) outward voltage-gated K⫹ currents (Cardenas et
al. 1995; Gold et al. 1996b; Petruska et al. 2000), and Ca2⫹activated K⫹ currents (Christian et al. 1994).
The differential expression of IH and IA is particularly striking because these two currents are thought to have opposite
effects (enhancement and suppression, respectively) on the
capacity for repetitive firing (Ingram and Williams 1996; Rudy
1988). According to a classification system for dorsal root
ganglion cells based on membrane currents, type 4 cells have
a large IH with no IA, whereas type 2 cells have a large IA with
no IH (Cardenas et al. 1995; Petruska et al. 2000). Because
slope and adaptation both depend in part on a neuron’s ability
to fire repetitively, the segregation of these two currents in
distinct neuronal populations raises the possibility that these
populations might also differ in their sensory response properties. A similar segregation might contribute to differences in
slope and adaptation found between in different populations of
dural afferents.
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The present study found a negative correlation between
slope and threshold. This correlation has not been calculated in
previous studies of primary afferent mechanosensitivity. However, a few such studies have shown a similar trend by dividing
their neuronal sample into groups of different thresholds and
comparing the response properties of the groups. In studies of
cutaneous and mucosal mechanonociceptive afferents, it was
found that neurons with moderate thresholds had higher response rates and better encoding of stimulus intensity than
those with higher thresholds (Burgess and Perl 1967; Cooper et
al. 1991). Although not explicitly noted, a similar trend can
also be seen in the mechanical stimulus-response curves illustrated in a number of other studies of cutaneous and visceral
afferents. Garell et al. (1996) divided cutaneous nociceptors
into two groups according to threshold and plotted the groupaveraged stimulus-response curves separately. Graphical analysis of the plots shows that the low-threshold group had very
steep initial slopes (A fibers: 0.5 Hz/g, C fibers: 0.2 Hz/g), with
saturation at higher intensities (⬎20 g), while the high-threshold group had much lower slopes (0.05 and 0.04 Hz/g for A
and C fibers, respectively). A similar relationship can be seen
in the individual stimulus-response curves of pelvic nerve
afferents responding to distension of the colon or the urinary
bladder (Sengupta and Gebhart 1994a,b). These were also
divided into low- and high-threshold groups. Although the
authors found no difference in the mean slopes, graphical
analysis of the plots nonetheless reveals a striking difference
between the two groups in the distribution of slopes. The
low-threshold group contained neurons with steep initial slopes
(1–3 Hz/mmHg) that then saturated (similar to the low-threshold cutaneous afferents of Garell et al. 1996) as well as neurons
with flatter slopes. The neurons in the high-threshold group
almost all had flat slopes (⬍0.7 Hz/mmHg). Thus the relationship between slope and threshold exhibited by dural afferents
can be discerned in mechanosensitive afferents of other tissues
as well.
Although other studies of primary afferent mechanosensitivity have not subdivided the A population by CV as we have,
it is nonetheless possible to discern parallels with a number of
our findings on differences between fiber classes. A study of
pelvic nerve afferents showed differences between fiber classes
in the incidence of mechanosensitivity that are similar to our
findings in dural afferents (Sengupta and Gebhart 1994b).
Although that study did not subdivide the A population, it
showed histograms of the conduction velocities of mechanically sensitive and insensitive fibers, that allow calculation of
the incidence of mechanosensitivity in the three fiber classes
that we used in the present study. From these histograms it can
be calculated that the percentage of mechanically insensitive
neurons was ⬃15% in the slow A population and 40% in the
fast A and C populations. Thus the higher incidence of mechanosensitivity in slow A neurons is apparently not unique to the
dural afferent population. This is also true of our finding of a
higher percentage of mechanically insensitive units among the
most slowly conducting C neurons because a similar trend is
present in human cutaneous C fibers (Weidner et al. 1999).
Studies of mechanical stimulus-response functions of cutaneous nociceptors have found that A fibers have higher slopes
than C fibers (Garell et al. 1996; Slugg et al. 2000). This is only
partly true for the dural afferents in that the slow A’s have
somewhat higher slopes than C fibers, but the fast A’s have
lower slopes. Our finding of a subgroup of fast A fibers with
low mechanosensitivity does not appear to have a parallel in
studies of other primary afferent populations.
A number of previous studies have examined relationships
between mechanical stimulus-response properties (slope or
threshold) and adaptation and, in some cases, found associations that are similar to those found in the present study.
Among pulmonary mechanoreceptive afferents (Knowlton and
Larrabee 1946), as well as cutaneous mechanical nociceptors
(Burgess and Perl 1967), neurons with rapid adaptation tend to
have high thresholds as was also found for dural afferents in
the present study. In cutaneous nociceptors, neurons with an
augmenting response pattern have high thresholds (Garell et al.
1996) similar to our finding in dural afferents. Similarly, a
study of mechanosensitive colonic afferents found that nonadapting neurons have high thresholds (Blumberg et al. 1983).
That study also found that the steepest slopes were exhibited by
those neurons that had a combined dynamic and static response
pattern, which is similar to our finding of high sensitivity in
dural afferents that have combined adapting and nonadapting
response components (i.e., neurons with exponential decay to a
non-0 plateau).
MECHANICAL RESPONSE PROPERTIES OF DURAL AFFERENTS
However, slope was strongly correlated with threshold in the
dural afferents. Because threshold does not depend on the
capacity for repetitive firing, it seems unlikely that this capacity could be the predominant factor in the determination of
slope, although it might be a contributing factor in some
neurons. Possibly repetitive firing capacity becomes important
in determining slope only when that capacity reaches extremely low levels (such as might occur in neurons with very
large IA and no IH), in which case it might tend to produce both
low slopes as well as rapid adaptation. This would be consistent with the association found between these two characteristics in the present study.
3029
duces an opposite bias, is that the relatively long stimulus pulse
that is used for activating slow fibers is not optimal for the
identification of fast fibers (⬎5 m/s) because the longer stimulus artifact can partially obscure short-latency spikes. For
unbiased searching, the pulse parameters should be alternated
between those that are optimal for slow and fast fibers, but in
practice, search parameters were more often optimized for
slow fibers because of their greater likelihood of exhibiting
mechanosensitivity. An alternative approach for determining
the fiber spectrum of the dural innervation is by anatomical
measurements of axon diameter, as has been done for the
unmyelinated fibers by Messlinger et al. (1993) but has not yet
been done for the myelinated fibers.
Functional considerations
The measurement of CV in this study is subject to several
potential sources of error as a result of being determined by
stimulation of a peripheral innervation site rather than an
exposed nerve. One potential source of error is in the determination of conduction distance because the route that each axon
takes from the ganglion to the dura is not visualized but rather
is assumed to follow a direct course via the tentorial nerve as
observed in anatomical studies and by dissection. This could
result in an underestimation of the CV if a given fiber took a
more circuitous route. A second, potentially much larger
source of error can arise from the slowing of CV that typically
occurs in peripheral axonal branches within the innervated
tissue (e.g., Peng et al. 1999). Fiber classification is based on
measurement of the CV of the parent axon in its course to the
target tissue rather than the peripheral branches within the
target tissue. For this reason, electrical response latencies were
determined at multiple sites across the exposed dura for each
neuron to locate the stimulation site associated with the shortest latency, which was presumed to correspond to the position
at which the parent axon first reached the dura from its course
through the underlying tentorium (see Figs. 1 and 2 of Strassman and Raymond 1999). Failure to use the shortest-latency
site for CV calculation could result in an underestimation of
CV by as much as three- or fourfold (Peng et al. 1999;
unpublished observations).
The determination of threshold in the present study was not
done by extrapolation of the stimulus-response function to zero
(e.g., Sengupta and Gebhart 1994a,b; Sengupta et al. 1990),
which would correspond to the stimulus intensity that evokes
an infinitesimal depolarization. Instead, threshold was defined
as the stimulus intensity that evoked one to two spikes, which
is similar to the definition of threshold used in von Frey hairs
studies. The extrapolation method will result in the calculation
of lower thresholds, and the decrease in threshold will be
greater for neurons with lower slopes. This might tend to
weaken the negative correlation between slope and threshold
that was observed in the present study.
As a result of sampling bias, the distribution of conduction
velocities in the study sample, as illustrated in the histogram in
Fig. 1A, may not be an accurate representation of the true
distribution in the population of dural afferents. One major
source of bias is that slowly conducting neurons are far more
difficult to isolate in microelectrode recordings than faster
conducting neurons, owing to the smaller amplitude of their
extracellularly recorded spikes. A second factor, which pro-
As far as is known, the only function of the meningeal
sensory innervation is nociceptive. It is not known to be
involved in the mediation of any nonnociceptive reflexes or
nonpainful sensations. Neurogenic inflammation, which can be
evoked in the dura by the release of neuropeptides from sensory fibers (Moskowitz and Macfarlane 1993), has a protective
function and is presumed to be mediated by nociceptive afferents. Although the meningeal sensory fibers can evoke vasodilation through the peripheral release of neuropeptides, these
fibers do not appear to participate in the normal regulation of
cerebral blood flow, since such regulation is not altered by
trigeminal deafferentation (Branston et al. 1995; Suzuki et al.
1990). However, trigeminal deafferentation does abolish or
attenuate the increase in cerebral blood flow that is evoked by
a number of potentially harmful or pathological conditions,
including meningitis (Weber et al. 1996), transient cerebral
ischemia (Moskowitz et al. 1989), severe hypertension, and
seizures (Sakas et al. 1989). Thus currently available evidence
is consistent with the idea that the meningeal sensory innervation only becomes activated under abnormal, potentially harmful conditions.
The response thresholds of the dural afferents were mostly
above physiological levels of intracranial pressure. Only ⬃3%
of the neurons had thresholds within this range (⬍2.5 kPa),
whereas ⬃18% had thresholds within the range of intracranial
pressures reached in experimental meningitis (⬍5 kPa) (cf.
discussion in Bove and Moskowitz 1997). Transient elevations
of intracranial pressure to higher levels might occur during
actions such as coughing or sudden head movement potentially
resulting in the recruitment of a larger proportion of afferents.
Meningitis as well as other pathological conditions might also
be accompanied by decreased thresholds as a result of sensitization, which could potentially bring a larger proportion of
the response thresholds within these pressure ranges.
It should be noted that comparisons of response thresholds
with intracranial pressures are complicated by the nonphysiological nature of the experimental stimulus conditions. Response thresholds in this study were determined with a focal
indenting stimulus, whereas intracranial pressures are more
diffusely distributed, and would tend to compress the dura
against the rigid cranium. Thus our stimulus might be expected
to produce more tension and shear, but less compression, than
would occur under physiological conditions within the closed
cranial space.
Clinical observations suggest that sensory fibers involved in
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Technical considerations relating to CV measurement,
threshold determination, and sampling bias
3030
D. LEVY AND A. M. STRASSMAN
some types of headache may be particularly sensitive to mechanical force transients (see INTRODUCTION). Consistent with
this, the highest response rates evoked in the dural afferent
population occurred during and immediately after stimulus
onset in neurons that had an adapting response component.
Sustained (nonadapting) responses, which were generally of
lower discharge rate, were also observed, both in neurons with
and without an adapting response component. Such nonadapting responses might contribute to the headaches that can accompany sustained increases in intracranial pressure or maintained traction or displacement of meningeal tissues.
The authors thank G. Bove for valuable comments on the manuscript.
This work was supported by the National Headache Foundation and by the
National Institute of Neurological Disorders and Stroke Grant NS-32534.
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