3.1. Time Course of Experimental Pain Ratings
Participants showed systematic changes in their pain ratings over the course of a run (). In most cases (74% of all runs), pain ratings declined during the first few trials, indicating adaptation to the thermal stimulus. After this initial phase, there was considerable diversity among individuals in the trend(s) shown in later trials; on average, subjects reported a gradual increase in pain. The trials are too widely spaced for this increase to be the result of wind-up, and we therefore refer to it as sensitization.
Figure 2 Time course of changes in responsiveness within a control (i.e., no-vibration) run consisting of 32 trials spaced at 15-s intervals. Each point is the pain intensity rating for one trial, averaged across all participants; error bars show ± 1 S.E.M. (more ...)
We consider first the adaptation phase, then the sensitization phase. Finally, we examine the effect of vibration on pain intensity.
3.2. Short-term and Long-term Adaptation
To quantify the adaptation that occurred at the beginning of a run, we made use of the fact that it appeared to be a negative exponential process, with pain intensity dropping rapidly at first and then more slowly (see ). If the function asymptotically approached zero, and its parameters remained constant across individuals, then pain intensity would always drop by the same fraction in the first (e.g.) 2 minutes of the run, regardless of the level at which it began. Neither of these conditions was met: In particular, pain for most subjects approached an asymptote substantially greater than zero. Nevertheless, the absolute decline in pain during adaptation (i.e. the mean of ratings 7 and 8 subtracted from the mean of the first two ratings) was closely related to the initial level of pain [r=.63, p<.001], implying that the use of relative decline (absolute decline divided by the mean of the first two ratings) as a measure of short-term adaptation would factor out much of the between-subject variance attributable to differences in initial pain ratings, and thus provide a more stable measure.
In addition to this short-term adaptation that occurred within a run, a longer-term adaptation manifested itself when a participant’s three runs were examined together (). Pain intensity, averaged over all trials within a run, declined markedly as the session proceeded. A 3×3 mixed model ANOVA examining the effects of run and clinical group showed that average pain intensity dropped significantly [F(2,144)=7.12, p=.001], but that this drop did not differ across groups (interaction: F(4,144)=.61, p=.66). The main effect of clinical group on pain intensity was also not significant [F(2,72)=.002, p=.998], as is to be expected from the fact that temperature was adjusted for individual subjects to produce comparable levels of initial pain.
Fig. 3 Pain ratings for the three runs constituting the experimental session, averaged across all participants (FM, TMD, and HC). Breaks of 10 min separated consecutive runs. The order of the three types of runs (33Hz, 100Hz, and control) varied randomly across (more ...)
The drop in average pain ratings from one run to the next occurred despite the fact that the initial pain ratings (average of trials 1 and 2) for each run did not change significantly between Runs 1 (35.0; SD=18.0), 2 (36.0; 18.0) and 3 (38; 18.3), F(2,144)=1.90, p=.15. The overall decline in pain across runs was the result of a gradual increase in the magnitude of short-term adaptation: Pain decreased an average of 16% during the first 8 trials of Run 1, as compared with 25% in Run 2 and 38% in Run 3. This pattern was present in the data of all three groups of participants. A 3×3 mixed model ANOVA, with the relative drop in pain during the first 8 trials of a run as the dependent variable, and run and group as the factors, showed that the effect of run was highly significant [F(2,144)=10.1, p<.001], but neither the effect of group [F(2,72)=.75, p=.47] nor the interaction of run and group [F(4,144)=.23, p=.92] was significant. Thus both the fast component of adaptation (the decline in pain within the first few trials of a run), and its slow component (the fact that the fast component increased from one run to the next) were comparable in FM, TMD, and HC participants.
To quantify sensitization, we fit a regression equation to the ratings for trials 10–32 for each subject (resembling the regression line fit to the mean data in ), and determined its slope, in terms of units on the 0–100 pain intensity scale per trial.
The temperatures used for each subject were chosen, on the basis of preliminary trials, to elicit ratings within (or as close as possible to) the 30–40 range on the pain intensity scale, without exceeding 51°C. The selected temperatures varied widely (see ). Interestingly, there was a significant positive relationship between a participant’s rate of sensitization and the temperature used in her runs (r=.48, p<.001).
Fig. 4 The rate of sensitization is plotted as a function of stimulus temperature. Rate is expressed in units of change (on the 0–100 pain intensity scale) per trial. Different symbols show the results for subjects with FM (squares), TMD (triangles), (more ...)
In a given subject, pain intensity generally increases with temperature, and the data in might therefore be taken to suggest that sensitization magnitude depended on the intensity of pain being experienced at the beginning of the summation process. To test this possibility, we compared sensitization slope with pain intensity at the start of sensitization; no relationship was found between these variables, r= −.05, p=.70 (see ). The fact that the magnitude of sensitization was related to stimulus temperature, but not to the level of pain that temperature evoked, suggests that the underlying mechanism is an early one, prior to the locus (or series of loci) in the nociceptive pathway at which pain signals come to reflect subjective intensity.
Fig. 5 The rate of sensitization is plotted as a function of pain intensity rating on the first trial of the series over which this rate was calculated. Different symbols show the results for subjects with FM (squares), TMD (triangles), and for healthy controls (more ...)
Given the association reported in some earlier studies between the speed or magnitude of temporal summation and clinical status, we examined the possibility that the rate of sensitization would be generally higher in the TMD and especially the FM patients than in the healthy controls. In fact, this was not the case: The rate of sensitization did not vary significantly as a function of group, F(2,72)=1.42, p=.25. This result is consistent with the view that sensitization and temporal summation are separate processes.
If the sensitization documented in the present study reflects an early stage of pain processing, we would expect it to be impervious to cognitive influences such as hypervigilance, which has been shown—in many of these same subjects [8
]—to be a powerful agent of late perceptual amplification. To test this prediction, we compared sensitization scores with scores on the Pennebaker Inventory of Limbic Languidness (PILL) [22
], the measure of hypervigilance used in our earlier study. Most of these PILL scores, obtained in a separate session, have been reported previously [8
], but the two samples do not exactly correspond, mainly because additional subjects were enrolled after the earlier study was published. ANOVA revealed a highly significant difference in hypervigilance between the clinical groups, F(2,70)=30.33, p<.001, consistent with our earlier report [8
]. Nevertheless, PILL scores did not significantly correlate with sensitization, r=−.09, p=.45, implying that sensitization occurs below the reach of this cognitive influence.
3.4. Modulation of Experimental Pain by Vibration
For a period of 10 trials (trials 13–22) in the middle of some runs, a vibratory stimulus was applied to the thenar eminence. This vibration began immediately after the subject’s rating of the thermal stimulus on trial 12, and continued without interruption until she had rated the thermal stimulus on trial 22. Each subject participated in one run with 33 Hz vibration and another with 100 Hz vibration, in both cases at an intensity of 40 dB SL. Evidence of pain modulation consisted of a deviation of pain ratings above or below the trend line formed by trials preceding and following the vibration period.
In many subjects, there was a small deviation (positive or negative) of pain ratings during the vibration period. To determine whether this represented genuine modulation of pain by vibration, or merely trial-to-trial variability, we derived quantitative modulation scores that could be subjected to statistical analysis. A modulation score was obtained for each run by (a) calculating the mean pain rating during the 10-trial vibration period; and (b) subtracting from this the combined mean of the seven trials immediately preceding, and the seven trials immediately following, the vibration period. Mean modulation scores suggested a slight reduction of pain during 33 Hz (−1.1; SD=3.7) and 100 Hz (−0.4; 5.4) vibration periods, but not during the corresponding 10-trial period in control runs (0.5; 2.5).
A repeated-measures ANOVA comparing modulation scores from the three types of runs (33Hz vibration, 100Hz vibration, and control) found a significant effect of condition, F(2,148)=3.71, p=.027. Post-hoc comparisons of modulation scores from vibration runs with those from control runs showed the difference to be significant at 33Hz, t(74)=3.00, p=.004, but not at 100Hz, t(74)=1.35, p=.18. Subsequent analysis was therefore confined to the effect of 33Hz vibration, although results at the two frequencies were qualitatively similar. The shaded area in shows that pain gating was a modest effect that lingered into the post-vibration period.
Fig. 6 Pain intensity ratings over the course of control runs (circles), and runs in which 33Hz vibration was present during trials 13–22 (triangles). Data are averaged across all participants (FM, TMD, and HC). The order of the two types of runs was (more ...)
Pain modulation scores were marginally correlated with temperature [r=.22, p=.057], meaning that there was a tendency for pain elicited by low temperatures to be more effectively suppressed than pain elicited by higher temperatures. Modulation scores were not, however, related to pain intensity on the trial (#12) immediately preceding the onset of vibration [r= −.15, p=.21] and they did not differ by participant group, F(2,72)=.58, p=.56. This pattern of statistical outcomes, similar to that obtained for sensitization slope, implies that pain gating is likewise a relatively low-level process.
Finally, there was a small but significant correlation between pain modulation score in the 33 Hz run, and the slope of sensitization in the same participant’s control run [r=.23, p=.046]. Vibration tended to increase pain in individuals with high sensitization slope, but to decrease pain in subjects with lower values of this continuous variable.