TY - JOUR
AB - Abstract Objectives Several chronic pain syndromes are characterized by deficient endogenous pain modulation as well as elevated negative affectivity and reduced resting heart rate variability. In order to elucidate the relationships between these characteristics, we investigated whether negative affectivity and heart rate variability are associated with endogenous pain modulation in a healthy population. Design, Subjects, and Methods An offset analgesia paradigm with noxious thermal stimulation calibrated to the individual’s pain threshold was used to measure endogenous pain modulation magnitude in 63 healthy individuals. Pain ratings during constant noxious heat stimulation to the arm (15 seconds) were compared with ratings during noxious stimulation comprising a 1 °C rise and return of temperature to the initial level (offset trials, 15 seconds). Offset analgesia was defined as the reduction in pain following the 1 °C decrease relative to pain at the same time point during continuous heat stimulation. Results Evidence for an offset analgesia effect could only be found when noxious stimulation intensity (and, hence, the individual’s pain threshold) was intermediate (46 °C or 47 °C). Offset analgesia magnitude was also moderated by resting heart rate variability: a small but significant offset effect was found in participants with high but not low heart rate variability. Negative affectivity was not related to offset analgesia magnitude. Conclusions These results indicate that resting heart rate variability (HRV) is related to endogenous pain modulation (EPM) in a healthy population. Future research should focus on clarifying the causal relationship between HRV and EPM and chronic pain by using longitudinal study designs. Endogenous Pain Modulation, Offset Analgesia, Heart Rate Variability, Negative Affectivity, Chronic Pain Introduction When pain signals are transmitted through the nervous system, they are modulated to accommodate the organism’s current and future needs [1]. One important phenomenon illustrating this is endogenous pain modulation (EPM) [2], which is thought to be a relevant factor in the development and maintenance of chronic pain. In humans, EPM efficiency is often tested with conditioned pain modulation (CPM) paradigms. In these paradigms, pain elicited by a single stimulus is compared with pain elicited by the same stimulus when accompanied by a painful stimulus of another modality in a different area (“pain inhibits pain”) [3]. More recently, offset analgesia (OA) has emerged as another paradigm to investigate EPM. In the typical OA paradigm, a 1 °C drop from continuous painful heat stimulation causes disproportionate pain relief, compared with continuous stimulation with this lower temperature [4, 5]. The two paradigms investigate different aspects of EPM but are thought to have a common ground in brainstem-spinal descending pathways [6]. Research using conditioned pain modulation paradigms or offset analgesia paradigms has consistently shown that EPM is abnormal in different types of chronic pain like osteoarthritis, irritable bowel syndrome (IBS), fibromyalgia syndrome (FMS), and neuropathic pain [7–9]. Longitudinal studies investigating initially pain-free individuals before and after surgery found that EPM efficiency before surgery was inversely related to postoperative chronic pain [10,11]. Consequently, some authors have argued that individual differences in EPM efficiency might be predictive of the development and course of different pain conditions [12]. Given the relevance of EPM for chronic pain conditions, the question arises as to which individual difference variables are associated with EPM efficiency in healthy individuals. In the present study, we focus on two factors that have been shown to be relevant for pain processing and are, more broadly, vulnerability factors for different kinds of psychological and somatic pathologies: negative affectivity and heart rate variability. Negative affectivity (NA), the tendency to experience negative emotions in daily life across different situations [13], is associated with a higher incidence of (functional) somatic [14] and psychiatric [15] disorders. NA influences affective processing of pain [16] and predicts changes in pain tolerance after vaccination [17]. Although NA is often controlled for in EPM studies, it has rarely been used as a primary predictor [18]. However, specific pain-related manifestations of NA, like pain catastrophizing and fear of pain, seem to be associated with reduced EPM [19]. Resting heart rate variability (HRV) reflects the interplay between the sympathetic and parasympathetic nervous system, with higher HRV indicating more flexibility to adapt to changing demands [20]. Few studies have focused on the association between resting HRV and EPM in adults [21], despite accumulating evidence that HRV is an index of physiological adaptability and is related to inhibitory capacity in general [22,23]. Moreover, resting HRV is reduced in several chronic pain conditions [24,25]. The aim of this study was to investigate the association between the above individual difference variables reflecting psychological and physiological (in)flexibility on the one hand and EPM on the other hand, using an offset analgesia paradigm in a healthy sample. Methods Participants Sixty-three healthy individuals (15 men, 48 women) participated in the study, all psychology students participating for course credits or 12 euros (mean age = 21.49 years, SD = 3.80 years, range = 18–41 years). Exclusion criteria were any self-reported psychiatric or chronic somatic conditions, current use of antidepressants, anxiolytics, beta-blockers or any type of analgesic medication, and wearing an electronic implant. The study was approved by the Social and Societal Ethics Committee of the University of Leuven. All participants gave written informed consent before participating. Materials and Apparatuses Thermal Stimulation Heat stimulation was delivered via a 30×30 mm Peltier thermode attached to the dorsal forearm with a Velcro strap (ATS system; Medoc Advanced Medical Systems Ltd., Ramat Yishay, Israel). The rise and fall rate during the experimental trials was 4 °C/s. Innocuous stimulation was set at 35 °C. Noxious stimulation temperature was determined for every participant based on their individual pain threshold. Pain Ratings During Heat Stimulation Perceived pain intensity was measured with a numeric rating scale ranging from 0 to 100. The scale was presented vertically on the screen and participants could indicate changes in pain intensity by scrolling and clicking. Labels next to the scale were: no pain (0), very slight/barely noticeable (5), very slight (10), slight (20), moderate (30), rather strong (40), strong (50), very strong (60–80), very very strong (90), unbearable (100). Psychological Trait Variables Positive and negative affectivity, the tendency to experience positive and negative emotions in daily life [26], was measured with the trait version of the Positive and Negative Affect Schedule (PANAS) [20]. For 10 positive and 10 negative emotions, the respondent has to indicate on a five-point Likert scale how often they experience this emotion in daily life. The Dutch version has been validated [27]. For replication purposes, two psychological factors that have been shown to be associated with EPM magnitude, fear of pain and pain catastrophizing [19], were measured with self-report questionnaires. Fear of pain was measured with the Fear of Pain Questionnaire [28]. Respondents are asked to indicate on a five-point Likert scale how fearful they are to experience pain associated with 30 physically painful situations. The questionnaire assesses fear of minor pain, fear of major pain, and fear of medical pain. The Dutch version has been validated [29]. The tendency to have pain-related catastrophic cognitions was measured with the Pain Catastrophizing Scale (PCS) [30]. Respondents are asked to indicate on a scale from 0 to 4 to what extent they experience 13 thoughts and emotions when in pain. The scale has three subscales: rumination, magnification, and helplessness. The Dutch version has been validated [31]. Baseline Heart Rate Variability Baseline heart rate variability was derived from an eight-minute electrocardiogram (ECG) recording, during which the participant was instructed to sit still and relax. Three 8-mm Ag/AgCl electrodes were placed underneath the participant’s right and left clavicle and at the location of the left lower ribs. The signal was sampled at 1,000 Hz and fed into a Couldbourn V75-04 Bioamplifier (Allentown, PA, USA). The ECG recording was visually inspected and processed offline with the ECG processing software Artiifact [32], which was also used to derive R-R intervals from which the root mean square of successive differences (RMSSD) was calculated as a time-domain parameter. This parameter has been shown to be a good measure of vagally mediated HRV indexing physiological flexibility [23]. Procedure Participants were instructed not to drink alcohol the evening before the experiment, not to exercise, smoke, or consume caffeine four hours before the experiment, and not to eat two hours prior to the experiment. Upon arrival, participants filled out the informed consent form and the PANAS, FPQ, and PCS. Subsequently, participants were informed about the course of the experiment and were made aware of the emergency button, which would stop all heat stimulation in case the pain was too high. Individual pain thresholds were determined prior to the experimental trials by slowly (1 °C/s) heating the thermode placed at the left dorsal forearm starting from 35 °C. Participants were instructed to indicate with a mouse click when the thermal sensation became painful. The theoretical cutoff limit was 50 °C, but all participants indicated that the heat was painful before reaching this temperature. This procedure was repeated five times. The average temperature of the last three threshold determination trials was considered the pain threshold temperature. To ensure the experimental trials were painful, the noxious stimulation (NS) temperature was set 1 °C above this threshold temperature. In the typical offset analgesia (OA) paradigm, a 1 °C drop from continuous painful heat stimulation causes disproportionate pain relief, compared with continuous stimulation with this lower temperature [4]. After establishing the individual NS temperature, the participants went through three blocks of experimental trials. Each block consisted of the presentation of three types of experimental trials (three within-subject conditions: offset, constant, and baseline) (Figure 1) in counterbalanced order. In the offset trials, participants received five seconds of NS on the forearm. This was followed by a 1 °C rise in temperature to the extranoxious stimulation (ENS) temperature. After five seconds of ENS, the temperature dropped by 1 °C for five additional seconds of NS. Previous research has indicated that this 1 °C drop causes disproportionate decreases in perceived pain intensity [4,5]. To disentangle habituation effects and offset effects, constant trials were included, in which the participants received 15 seconds of NS. To investigate if the 1 °C drop in the offset trials caused reductions in pain perception similar to complete pain relief, the baseline trials consisted of 10 seconds of NS, after which the thermode cooled down immediately to baseline temperature (35 °C). Each trial was separated by 120 seconds of innocuous stimulation (35 °C). Participants were instructed to continuously indicate pain intensity during the blocks—the scale did not disappear in-between the trials. Figure 1 View largeDownload slide Heat stimulation trials presented as within-subject conditions during the blocks. Noxious stimulation (NS) temperature was dependent on the participant’s individual pain threshold. Extranoxious stimulation temperature was 1 °C above the NS temperature. T1, T2, and T3 mark the critical time points on which pain ratings were used for analysis. All three trials were presented in each block in random order. ENS = extranoxious stimulation; NS = noxious stimulation. Figure 1 View largeDownload slide Heat stimulation trials presented as within-subject conditions during the blocks. Noxious stimulation (NS) temperature was dependent on the participant’s individual pain threshold. Extranoxious stimulation temperature was 1 °C above the NS temperature. T1, T2, and T3 mark the critical time points on which pain ratings were used for analysis. All three trials were presented in each block in random order. ENS = extranoxious stimulation; NS = noxious stimulation. Each block was separated by a 10-minute break in which the thermode was removed from the arm. The breaks were included to minimize sensitization/habituation to the heat stimulus and to let the skin rest. To minimize interindividual variability in cognitions during the break, neutral video clips were shown during the breaks. The two video clips consisted of scenes from the bird documentary Winged Migration [33]. Statistical Analysis and Design Data from four participants who did not report pain during the experimental trials were excluded from analysis. Participants’ pain ratings at T1, T2, and T3 (Figure 1) in each condition were averaged across blocks. When an individual’s pain rating during heat stimulation did not exceed 20 (labeled very slight pain), that particular trial was not taken into account when calculating averages. Six out of 531 trials were excluded for this reason. To investigate the overall offset effect, pain ratings at T2 and T3 were used as dependent variables in a mixed model analysis, with time (T2 and T3) and condition (baseline vs offset vs constant) and their interactions as fixed effects. Follow-up comparisons were made with post hoc t tests with Tukey-Kramer correction for multiple comparisons. To investigate moderators of the offset effect, we focused on the difference in pain ratings in the offset vs constant condition at T3 (a larger difference reflects a more efficient EPM). Our main independent variables in this regard were NA and baseline RMSSD. For both these variables, two groups were made based on a median split. Pain ratings at T3 were used as dependent variables in separate mixed-model analyses, with condition (constant vs offset) as a within-subject factor and NA or RMSSD group as a between-subject factor. In the case of a significant interaction effect, the offset effect was tested in both groups separately. In addition, the linear relationship between the predictor variables and the offset effect was investigated with robust regression analyses (to minimize the influence of outliers). For this purpose, we calculated the difference score between pain ratings in the constant vs offset condition by subtracting the pain ratings in the offset condition from the pain ratings in the constant condition at T3. NA and baseline RMSSD were logarithmically transformed and used as independent variables in separate robust regressions, with the pain ratings’ difference score as the dependent variable. To control for the role of the NS temperature in the offset effect, NS temperature was also investigated as a between-subject variable in an equivalent mixed model. Because this variable was extremely negatively skewed, we decided to divide the participants into groups based on tertiles (group 1 = 42–45 °C, N = 21; group 2 = 46–47 °C, N = 21; group 3 = 48 °C, N = 17). Analyses were conducted with the Statistical Package for the Social Sciences (SPSS) 23, SAS University Edition, and JMP Pro 12. Results Descriptive Statistics Predictor Variables Descriptive statistics for the predictor variables NA, pain catastrophizing, fear of pain, baseline RMSSD, and NS temperature can be found in Table 1. NA was correlated with the rumination (r = 0.483, P < 0.001), magnification (r = 0.328, P = 0.011), and helplessness (r = 0.369, P = 0.004) scales of the PCS. NA was not correlated with any of the FPQ subscales. Resting heart rate and baseline RMSSD were strongly intercorrelated (r = –0.757, P < 0.001) but did not correlate with any of the trait questionnaires. NS temperature was unrelated to scores on the trait questionnaires and to baseline HR(V) measurements. Table 1 Descriptive statistics for the predictor variables Min Max Mean SD Negative affectivity (PANAS) 10 45 22.08 7.69 Fear of severe pain (FPQ) 17 48 32.12 5.97 Fear of minor pain (FPQ) 10 28 16.85 4.52 Fear of medical pain (FPQ) 13 40 24.78 6.92 FPQ total 51 116 76.2 13.20 Rumination (PCS) 1 16 8.39 3.33 Magnification (PCS) 0 10 3.83 2.49 Helplessness (PCS) 0 16 5.90 3.62 PCS total 1 40 17.83 8.11 Baseline HR 57.12 98.78 78.73 10.55 Baseline RMSSD 9.39 97.83 41.82 16.93 NS temperature 42 48 46 1.93 Min Max Mean SD Negative affectivity (PANAS) 10 45 22.08 7.69 Fear of severe pain (FPQ) 17 48 32.12 5.97 Fear of minor pain (FPQ) 10 28 16.85 4.52 Fear of medical pain (FPQ) 13 40 24.78 6.92 FPQ total 51 116 76.2 13.20 Rumination (PCS) 1 16 8.39 3.33 Magnification (PCS) 0 10 3.83 2.49 Helplessness (PCS) 0 16 5.90 3.62 PCS total 1 40 17.83 8.11 Baseline HR 57.12 98.78 78.73 10.55 Baseline RMSSD 9.39 97.83 41.82 16.93 NS temperature 42 48 46 1.93 FPQ = Fear of Pain Questionnaire; HR = heart rate; NS temperature = noxious stimulus temperature, defined as 1 °C above the individual heat pain threshold; PANAS = Positive and Negative Affect Schedule; PCS = Pain Catastrophizing Scale; RMSSD = root mean square of the successive differences calculated from the R - R peak interval of the heart rate. Table 1 Descriptive statistics for the predictor variables Min Max Mean SD Negative affectivity (PANAS) 10 45 22.08 7.69 Fear of severe pain (FPQ) 17 48 32.12 5.97 Fear of minor pain (FPQ) 10 28 16.85 4.52 Fear of medical pain (FPQ) 13 40 24.78 6.92 FPQ total 51 116 76.2 13.20 Rumination (PCS) 1 16 8.39 3.33 Magnification (PCS) 0 10 3.83 2.49 Helplessness (PCS) 0 16 5.90 3.62 PCS total 1 40 17.83 8.11 Baseline HR 57.12 98.78 78.73 10.55 Baseline RMSSD 9.39 97.83 41.82 16.93 NS temperature 42 48 46 1.93 Min Max Mean SD Negative affectivity (PANAS) 10 45 22.08 7.69 Fear of severe pain (FPQ) 17 48 32.12 5.97 Fear of minor pain (FPQ) 10 28 16.85 4.52 Fear of medical pain (FPQ) 13 40 24.78 6.92 FPQ total 51 116 76.2 13.20 Rumination (PCS) 1 16 8.39 3.33 Magnification (PCS) 0 10 3.83 2.49 Helplessness (PCS) 0 16 5.90 3.62 PCS total 1 40 17.83 8.11 Baseline HR 57.12 98.78 78.73 10.55 Baseline RMSSD 9.39 97.83 41.82 16.93 NS temperature 42 48 46 1.93 FPQ = Fear of Pain Questionnaire; HR = heart rate; NS temperature = noxious stimulus temperature, defined as 1 °C above the individual heat pain threshold; PANAS = Positive and Negative Affect Schedule; PCS = Pain Catastrophizing Scale; RMSSD = root mean square of the successive differences calculated from the R - R peak interval of the heart rate. Overall Offset Effect Average pain ratings at T2 and T3 by condition are displayed in Figure 2. At T2, the pain ratings in the offset condition were significantly higher compared with pain ratings in the constant (t116 = 8.05, P < 0.001) and baseline (t116 = –7.91, P < 0.001) conditions. This suggests that overall participants noticed the 1 °C rise in temperature in the offset condition. Conditions significantly differed at T3 as well, but this was solely due to pain ratings in the baseline condition being significantly lower than pain ratings in the offset (t116 = –14.11, P < 0.001) and constant (t116 = –15.63, P < 0.001) conditions. In contrast to our expectations, there was no difference between the offset and the constant conditions at T3 (t116 = –0.44, P = 0.661). Figure 2 View largeDownload slide Least square mean pain ratings at T2 and T3 by condition. Whiskers denote standard error of the mean. Figure 2 View largeDownload slide Least square mean pain ratings at T2 and T3 by condition. Whiskers denote standard error of the mean. Effect of NS Temperature When exploring the possible moderation effect of NS temperature, the overall difference between pain ratings at T3 in the offset and constant conditions remained nonsignificant (F1,56 = 0.23, P = 0.637). There was, however, a significant condition by temperature interaction (F2,56 = 4.69, P = 0.013) and a main effect of temperature on pain ratings (F2,56 = 18.04, P < 0.001), with higher temperatures being associated with higher pain ratings. Post hoc stepdown Bonferroni-corrected t tests indicated that no significant differences between the constant and offset conditions emerged in the lower (t56 = 1.51, P = 0.274) and higher (t56 = 0.31, P = 0.761) temperature groups, but pain ratings in the group that chose 46–47 °C as an NS temperature were significantly lower in the offset condition than the constant condition (t56 = 2.70, P = 0.027) (see Figure 3). Figure 3 View largeDownload slide Least square mean pain ratings at T3 by condition and temperature. Whiskers denote standard error of the mean. NS = noxious stimulation. Figure 3 View largeDownload slide Least square mean pain ratings at T3 by condition and temperature. Whiskers denote standard error of the mean. NS = noxious stimulation. Effect of NA, Fear of Pain, and Pain Catastrophizing The possible moderating role of NA on offset analgesia was explored by adding NA groups, based on a median split (cutoff = 21), as a between-subject fixed factor to a mixed model that compared pain ratings at T3 in the offset and constant conditions. When adding the NA group to the model, the difference between the conditions remained insignificant (F1,57 = 0.29, P = 0.593). No significant NA group-by-condition interaction effect was found on pain ratings at T3 (F1,57 = 1.40, P = 0.241). There was also no significant main effect of NA on pain ratings (F1,57 = 0.95, P = 0.333). In a robust regression, the logarithmically transformed NA score was not significantly associated with the difference in pain ratings between the constant and offset conditions at T3 (β1 = –15.19, P = 0.399). Similarly, no effects were found for the different subscales of the FPQ and PCS. Effect of Baseline HRV To investigate the effect of baseline HRV on the offset effect, participants were divided into a low- vs high-RMSSD group (cutoff = 38.67) by means of a median split. The main effect of RMMSD group on pain ratings was not significant (F1,57 = 0.27, P = 0.606). However, there was a significant RMSSD-by-condition interaction (F1,56 = 5.87, P = 0.019). Tests in each group separately following up on this effect indicated that in the low-RMSSD group, there was no significant difference between conditions (F1,57 = 1.73, P = 0.194), but pain ratings in the offset condition were significantly lower than pain ratings in the constant condition in the high-RMSSD group (F1,57 = 4.43, P = 0.04) (Figure 4). Robust regression analysis indicated that baseline RMSSD was significantly related to the difference in pain ratings between the constant and offset condition in T3 (β = 36.02, P = 0.03) (Figure 5), with higher RMSSD being associated with a more positive difference score, that is, a larger offset analgesia effect. Figure 4 View largeDownload slide Least square mean pain ratings at T3 by condition and root mean square of successive differences group. Whiskers denote standard error of the mean. RMSSD = root mean square of successive differences. Figure 4 View largeDownload slide Least square mean pain ratings at T3 by condition and root mean square of successive differences group. Whiskers denote standard error of the mean. RMSSD = root mean square of successive differences. Figure 5 View largeDownload slide Scatterplot of baseline root mean square of successive differences by the constant–offset difference score at T3, with a regression line fitted by the robust regression method. RMSSD = root mean square of successive differences. Figure 5 View largeDownload slide Scatterplot of baseline root mean square of successive differences by the constant–offset difference score at T3, with a regression line fitted by the robust regression method. RMSSD = root mean square of successive differences. Discussion and Conclusions The present study aimed to investigate the association between NA, HRV, and EPM in an offset analgesia paradigm. The magnitude of the offset effect was defined as the difference in pain ratings at T3 in the offset condition vs the constant condition. In contrast to our expectations, we did not find evidence for an overall difference between pain ratings in the offset and constant conditions at T3. However, the results show that offset magnitude was mediated by RMSSD at the baseline: A small but significant offset analgesia effect could be found in subjects with high baseline RMSSD, but not in subjects with low baseline RMSSD. This finding highlights the conceptual connection between HRV and EPM magnitude. Measures of vagally mediated HRV, like RMSSD, indicate how flexibly neurovisceral networks responsible for goal-directed behavior and adaptive emotional responding are recruited. Recent neuro-imaging studies have revealed that HRV can serve as an index of inhibitory processes regulating the balance between excitation and inhibition in the abovementioned neurovisceral circuits [23]. Because endogenous pain modulation is critically dependent on a subtle balance between excitation and inhibition, the finding that HRV and EPM are related is not surprising. Moreover, the offset analgesia effect is mediated by activation in the periaqueductal grey and rostroventral medulla [34], both structures involved in cortical control over heart rate. Despite the conceptual connection between HRV and EPM, studies directly investigating the association between resting HRV and EPM magnitude are rare. One study reported a significant correlation between baseline RMSSD and CPM magnitude in children and adolescents [35]. A significant association between RMSSD and both offset analgesia and CPM was also found in a recent study, but this association was only apparent for men [21]. It is possible that the relationship between HRV and EPM is stronger in men, although we were not able to test this because our sample consisted primarily of women. However, this might explain why the effect that we did find was relatively small. Interestingly, chronic pain syndromes like FMS and IBS are characterized by both reduced HRV and reduced EPM magnitude. The finding that HRV and EPM are associated even in the absence of chronic pain and previous findings that reduced EPM magnitude predicts the development of chronic pain over time [10] hint that this tonic disinhibition—indexed by reduced HRV—might be a risk factor for the development of chronic pain. However, as the current study was correlational, causal inferences cannot be made at this moment. Research on HRV training—for instance, through biofeedback or slow deep breathing—suggests that the involved neurovisceral circuits are flexible to some extent and that these inhibitory processes can be trained [36,37]. Consequently, because HRV and EPM are associated, HRV training may possibly contribute to a more efficient EPM and reduce pain in chronic pain patients. Although more longitudinal research is needed to establish the causal relationship between HRV, EPM, and chronic pain, these results are a first step in this direction. In contrast to our expectations, there was no association between NA and magnitude of the offset effect. Individuals with high NA are characterized by an over-reactive evaluative system as well as poorer emotional regulation and executive control [38,39], and NA is a risk factor for different kinds of psychopathology [15,40]. Because chronic pain is characterized by both elevated NA and reduced EPM, we wanted to investigate the relationship between NA and EPM in a healthy population. Our results do not provide any evidence for such a relationship. However, it is possible that an effect of NA on EPM is only evident with NA reaching clinical levels, such as in the case of clinical depression. For instance, fibromyalgia patients with comorbid depression performed worse on a CPM task compared with fibromyalgia patients without comorbid depression, who in turn performed worse than healthy controls [41]. Our sample consisted of healthy students with varying levels of NA; however, none of them suffered from clinical depression. There was also no relationship between offset analgesia magnitude and the included pain-specific measures that are influenced by NA, fear of pain, and pain catastrophizing. Although relationships between CPM and fear of pain and pain catastrophizing are often reported in the literature, this finding is not very robust and might be dependent on stimulus modality [18]. Furthermore, studies controlling for these factors while using an offset analgesia paradigm are scarce and do not report direct effects of fear of pain or pain catastrophizing on OA magnitude [18]. Some specific findings deserve further attention. The results from this study show that offset analgesia was only found with thermal pain stimuli of 46–47 °C. This is surprising, considering the fact that previous studies employing this paradigm have successfully used both fixed lower [34] and higher [4,42] temperatures. Other studies in which the NS temperature was dependent on the individual’s pain perception do not mention any effects—or absence of effects—of NS temperature on offset analgesia magnitude [18,5,43]. It is possible that low NS temperatures might not have elicited sufficient pain to generate an offset effect in this specific sample. It has, for instance, been shown that the threshold for the activation of Aδ fibers, needed for the experience of strong acute pain, is about 46–48 °C [44]. Conversely, administration of extremely high temperatures to the skin might have reduced the participants’ ability to distinguish between the different sensations. The main effect of stimulus temperature on pain ratings, as seen in Figure 3, suggests that although the temperature was individually calibrated to the pain threshold, pain intensity was highly affected by the temperature administered in both the offset and constant conditions. In addition to differences in temperature, differences in perceived pain in the constant condition might have moderated the offset analgesia effect. When interpreting these results, one must also take into account that differences in NS temperatures produced differences in rising times and consequently unequal total stimulation lengths, which might have contributed to differences in pain perception. Considering the fact that NS temperature was dependent on the individual’s pain threshold, another interpretation is that the offset analgesia paradigm does not appear in participants with a very low or a very high heat pain threshold. Physiological or psychological differences between individuals with different heat pain thresholds might thus account for differences in EPM efficiency. However, we did not find any differences between these pain threshold groups in the physiological and psychological measures we included in this sample. Further research is needed to determine the relationship between pain threshold, EPM efficiency, and possible mediators of this relationship. Several limitations inherent to our study design are worth mentioning, possibly explaining the lack of an overall offset analgesia effect. First, a number of variations in different aspects of the OA paradigm are found in the literature. Because methodological choices had to be made for our particular study, some of these choices might apply to features that are critical for OA to emerge. This might possibly explain the lack of an offset analgesia effect for the majority of the subjects. For instance, in the present study, participants rated their pain levels continuously, while in some other studies participants were prompted for momentary pain ratings at fixed time points [4,34]. This difference in assessment could imply a difference in attention focus. Second, the rise time in our study (at a rate of 4 °C/s) was relatively long compared with other offset analgesia studies due to a difference in equipment [5,34]. Another possible explanation for the absence of the offset effect is the large number of female compared with male participants in the current sample. There is a vast literature on the influence of gender on EPM magnitude, consistently showing that men have more efficient EPM than women [45], and this seems to be true for offset analgesia as well [21]. Future studies investigating the relationship between individual difference variables and EPM magnitude should control for this by recruiting an equal amount of men and women. However, the few men that did participate in this study did not show a larger offset effect. Another potential limitation is the fact that HRV was only measured during rest, and not during evoked pain. Monitoring changes in HR(V) during evoked pain might provide us with more insight in the relationship between HRV and EPM. Lastly, as this study was correlational (HRV or NA were not manipulated or measured at different time points), we cannot draw conclusions about causal relationships from our results. In summary, the aim of this study was to investigate the association between negative affectivity and heart rate variability—both factors associated with different chronic pain conditions—on the one hand, and endogenous pain modulation on the other, in a healthy population, with the purpose of exploring the relationships between NA, HRV, and EPM. Although there was no overall offset effect in our sample, it was observed in the group receiving heat stimulation of 46–47 °C (corresponding to pain thresholds of 45–46 °C). Our results confirmed the hypothesis that individuals with higher resting HRV have a more efficient EPM, but not that individuals with higher NA have less efficient EPM. Future research should focus on clarifying the causal relationship between HRV, NA, EPM, and chronic pain by using longitudinal study designs. Authors’ Contributions All authors contributed significantly to the conception and design of the study and to the interpretation of the data. MVDH was responsible for the data collection. MVDH and LVO performed the data analysis. All authors contributed to drafting the article and revising it critically. All authors approved the final version of the paper for submission. Acknowledgments The authors thank Sofie Thys for her help in data collection. Funding sources: This research was supported by the Center for Excellence on Generalization Research (GRIP*TT; University of Leuven grant PF/10/005) and by Asthenes, a long-term structural funding–Methusalem grant by the FWO-Vlaanderen, Flemish Government, Belgium. Conflicts of interest: The authors report no conflicts of interest. References 1 Bourne S , Machado AG , Nagel SJ. 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TI - Endogenous Pain Modulation: Association with Resting Heart Rate Variability and Negative Affectivity
JF - Pain Medicine
DO - 10.1093/pm/pnx165
DA - 2018-08-01
UR - https://www.deepdyve.com/lp/oxford-university-press/endogenous-pain-modulation-association-with-resting-heart-rate-R0qosDZpaU
SP - 1587
EP - 1596
VL - 19
IS - 8
DP - DeepDyve
ER -