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Systematic Review and Meta-Analysis

Noninvasive motor cortex stimulation effects on quantitative sensory testing in healthy and chronic pain subjects: a systematic review and meta-analysis

Giannoni-Luza, Stefanoa; Pacheco-Barrios, Kevina,b; Cardenas-Rojas, Alejandraa; Mejia-Pando, Piero F.a; Luna-Cuadros, Maria A.a; Barouh, Judah L.a; Gnoatto-Medeiros, Marinaa; Candido-Santos, Ludmillaa; Barra, Alicec,d,e; Caumo, Wolneif; Fregni, Felipea,*

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doi: 10.1097/j.pain.0000000000001893
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Abstract

1. Introduction

Pain perception is a complex process influenced by sensory, cognitive, and emotional dimensions72; the multidimensional nature of pain requires different measurement approaches to understand the pathophysiology underlying pain syndromes.44 Quantitative sensory testing (QST) assessments have been used to objectively measure pain in both healthy and pain populations.44 Static QST—measured by pain threshold (PT)—assesses the basal state of the nociceptive system, whereas dynamic QST evaluates the pain processing system: (1) pain facilitation—measured by temporal summation (TS)—and pain inhibitory systems (the endogenous pain inhibitory system)—assessed by conditioned pain modulation (CPM) protocols.5,51 This later evaluates the phenomenon known as “pain inhibits pain” by testing the functioning and integrity of the endogenous descending inhibitory pathways.7 The changes in QST measurements are useful to understand pain processes in healthy subjects, and they could be applied in pain populations as diagnostic biomarkers and as a predictor of responsiveness to analgesic treatments.68

Noninvasive motor cortex stimulation has shown an effect on pain facilitatory and inhibitory systems because of the activation of subcortical structures related to the endogenous pain modulation system such as thalamus, cingulate gyrus, periaqueductal gray, and subnucleus reticularis dorsalis (SRD), among others.30,31 Transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) might restore the balance in the endogenous pain pathways as a top-down regulation, through subcortical nuclei (such as thalamic nuclei and SRD) while preventing or reversing maladaptive plasticity leading to a decrease in pain perception.16 Transcranial direct current stimulation delivers a subthreshold current from anode to cathode by 2 electrodes over the scalp, whereas rTMS uses magnetic fields to induce electrical changes in the brain activity.16 Both of them are noninvasive brain stimulation (NIBS) techniques that have shown some efficacy in healthy subjects and pain-related syndromes.45,46,61 Hence, these tools are appropriate options to modulate the pain perception processes reflected on QST changes. The NIBS effects on CPM can be related to endogenous pain pathway modulation,24 which can be used to understand this system disruption on different chronic pain conditions better and clarify the NIBS mechanism of action. Moreover, their effects on PT and TS can give us a better understanding of its impact on peripheral and central sensitization.70

Although the utility that would have to understand the NIBS effects on pain processes indexed by QST and that noninvasive motor cortex stimulation has been extensively studied in chronic pain,2,27,61 the knowledge on their effects on QST is still limited, especially the pooled effect of 2 commonly used techniques for motor cortex stimulation (tDCS and rTMS) in healthy subjects and in subjects with pain. Thus, with this systematic review and meta-analysis, we aim to evaluate the effects that previous studies have shown of motor cortex stimulation on pain perception processes indexed by changes in static and dynamic QST outcomes, including PT, TS, and CPM.

2. Methods

A systematic review of the literature and meta-analysis were conducted following the recommendation of the Cochrane Handbook,33 including the PRISMA guidelines (online supplementary material 1).54

2.1. Literature search and study selection

We searched in MEDLINE, EMBASE, Web of Science, LILACS, and Cochrane Central until July 31, 2019, using a search strategy with the following search terms: “noninvasive brain stimulation” OR “transcranial magnetic stimulation” OR “transcranial direct current stimulation” AND “Diffuse Noxious Inhibitory Control” OR “Pain Threshold.” The full research strategy is shown in online supplementary material 2. Duplicates were eliminated before selection. Before the title and abstract selection, 2 experienced reviewers (K.P.B. and A.C.-R.) agreed on a standard approach. Two random samples of 50 search results were preselected for the training and standardization process. After preselecting the articles based on the title and abstract, 4 reviewers (L.C., M.L., P.M., and S.G.-L.) selected the same articles for calibration purposes. Subsequently, we calculated the interrater agreement and kappa estimator, aiming for an interrater agreement of at least 90% (online supplementary material 3). Afterward, the citations were independently screened by the 4 reviewers (L.C., M.L., P.M., and S.G.-L.) in terms of titles and abstracts. Discrepancies between reviewers were resolved by a fifth reviewer (A.C.-R.). Then, the 4 main reviewers independently assessed the full text of selected studies, and again, the fifth reviewer resolved discrepancies.

2.2. Eligibility criteria

We searched for full-text articles restricted to English. Included articles had to have (1) enrolled either healthy subjects and/or subjects with a pain condition; (2) performed NIBS such as tDCS or rTMS on the motor cortex compared with their respective sham; (3) assessed the QST including pressure PT, heat PT, cold PT, or electrical PT, CPM, and TS; and (4) designed as randomized controlled trials (RCTs), included parallel group, crossover designs, and pilot studies.

2.3. Data extraction

In total, 8 reviewers participated in the extraction process. Two of them (A.C.-R. and S.G.-L.) developed the extraction matrix. The extraction was performed in pairs (P.M. and M.L.; J.B. and S.G.-L.; and M.G. and L.C.) that extracted the same articles independently. All discrepancies between reviewers were solved by a seventh reviewer (K.P.-B.). For each study, we extracted in a standardized spreadsheet the following: (1) participant characteristics (sample size, condition, age, sex, and drop-outs), (2) NIBS intervention protocol characteristics (stimulated area, electrode size, current intensity, pulse frequency, number of sessions, and session duration), and (3) outcomes of interest (PT, CPM, and/or TS). In case of missing or unclear information, we requested by email the values from the authors. We used WebPlotDigitizer v.3.1166 to extract data from relevant graphs, and if a study only reported postintervention data, we determined whether to include the data in the analysis by studying baseline comparability on the graphs. If we were unable to contact the authors or extract the data graphically, we excluded the study from the quantitative analysis. Some of the included studies measured multiple variables to assess the QST outcome within subjects (more than 1 body location for PT assessments—eg, left arm, right arm, and left leg). We were aware that computing different effect sizes for the same sample or overlapping sets of participants and treating them as completely unrelated effect sizes violate the basic assumptions of the traditional meta-analytic method. In those cases, we calculated a weight mean of the multiple variables to compute a unique measurement of the outcome of interest, in order not to lose relevant information.

2.4. Static quantitative sensory testing outcomes

(1). Pain threshold: Corresponded to the smallest stimulus that was reported by subjects as painful. This could be measured by the different stimuli such as pressure with an algometer, heat, cold, or electrical stimulus. It was reported a lower PT in different chronic pain conditions.44,68 We extracted and analyzed changes in stimulus units (eg, kPA and centigrade degrees) and SD as a measurement of PT changes.59,60

2.5. Dynamic quantitative sensory testing outcomes

(1). Temporal summation: This protocol measured pain facilitation and was calculated as the difference between the pain rating after a series of stimuli and the rating after a single stimulus after the series, expecting more pain after the application of stimuli in series.44,68 We extracted and analyzed changes in pain ratings and SD as a measurement of TS effect.59,60

(2). Conditioned pain modulation: This protocol involved 2 conditions, the test stimulus (painful sensation) and the conditioned stimulus (cold water sensation). This protocol could be measured by the difference between PT or pain rating after the test stimulus and after the conditioned stimulus. In healthy patients, we expected a decrease in the pain score after the conditioned stimulus; however, in pain conditions, as the endogenous pain modulation system was impaired, higher pain scores would be perceived after the conditioned stimulus.58 We extracted and analyzed changes in pain ratings and SD as a measurement of CPM effect.59,60

2.6. Risk of bias assessment

The risk of bias of the selected studies was evaluated by 2 reviewers (A.C.-R. and S.G.-L.) using the Cochrane Risk of Bias Scale for RCTs.33 To classify the low, high, and unclear risk of bias, we followed the instructions stated in the Cochrane Handbook for Systematic Reviews of Interventions for RCTs.33 In the event of any discrepancies between the 2 reviewers, a consensus was attempted to be reached by discussion. If a full consensus could not be reached between the 2 reviewers after an exhaustive discussion, the opinion of a third reviewer was obtained (K.P.-B.), and the proceeding majority consensus was taken.

2.7. Data synthesis

The RCTs were presented separately according to the condition (healthy vs pain population), given the differences in the pain perception processes between these 2 groups. The QST outcomes were categorized according to the type of stimulation (tDCS or rTMS). Then, the effect sizes of QST outcomes and their 95% confidence intervals (95% CIs) were calculated, and an exploratory meta-analysis was performed. Although within the treatment categories were interventions with different parameters, we decided to do an exploratory synthesis to compare across the spectrum of the available noninvasive motor cortex stimulation techniques. We adjusted Cohen's d to Hedge's g by applying a correction factor because Cohen's d has a slight bias to overestimate in small sample sizes. We assessed heterogeneity using an I2 statistical, and we considered low heterogeneity when I2 <40%.33 We considered it appropriate to use random-effects models because of the overall heterogeneity evaluation (in population and intervention).23 Moreover, we performed subgroup analysis, sensitivity analysis, and meta-regression as further evaluations of sources of heterogeneity. The publication bias was evaluated by visual assessment (funnel plot) and by the Egger test. The data were analyzed using Stata v15.1 software (StataCorp LLC).

3. Results

3.1. Overview

The search retrieved 5656 results; after removing duplicates, 4032 titles and abstracts were screened, and of these, 3877 were excluded. One hundred fifty-five studies were evaluated in full text, and of which, 117 studies were excluded (online supplementary material 4). And finally, 38 studies were included,1,6,8–12,14,15,18,20–22,25,26,32,34,36–38,40,41,43,49,52,53,55–57,62,64,65,69,73,74,76,78 reporting 71 comparisons (1178 participants). A flow diagram of the search process is presented in Figure 1.

Figure 1.
Figure 1.:
Flow diagram of the search and selection process. QST, quantitative sensory testing; RCT, randomized controlled trial.

Regarding NIBS, 28 studies evaluated the effects of tDCS and 10 of rTMS. From them, 9 studies (23.7%) assessed other interventions together with NIBS. Three evaluated the effects of exercise (7.6%), whereas the other 6 evaluated melatonin, intramuscular electrical stimulation, naloxone, ketamine, and remifentanil (2.6% each). In terms of QST outcomes data, 33 studies reported PT: 20 in the healthy population (35 comparisons, 629 subjects) and 13 in pain conditions (17 comparisons, 462 patients); 2 reported TS (3 comparisons, 38 patients); 13 reported CPM outcomes: 7 in the healthy population (10 comparisons, 169 subjects) and 6 in pain conditions (8 comparisons, 239 patients); and 11 reported more than 1 outcome. Besides, 23 (60.5%) performed the QST protocols in upper limbs, 7 (18.4%) in lower limbs, 2 (5.3%) in both upper and lower limbs, and 6 (15.8%) in other body areas. The included pain populations1,6,12,15,20,22,37,40,41,49,52,53,62,65,69,76 were heterogeneous, including fibromyalgia: 4 (25%), knee osteoarthritis: 3 (18.8%), peripheral neuropathy: 2 (12.5%), temporomandibular disorder: 1 (6.3%), poststroke pain: 1 (6.3%), myofascial pain: 1 (6.3%), postoperative pain: 1 (6.3%), and others: 3 (18.8%) studies. Only 7 (43.8%) reported pain duration and 2 (12.5%) sensory profile. A qualitative summary of included articles is provided in Tables 1 and 2.

Table 1
Table 1:
General information from the tDCS studies included in the meta-analysis.
Table 1-A
Table 1-A:
General information from the tDCS studies included in the meta-analysis.
Table 1-B
Table 1-B:
General information from the tDCS studies included in the meta-analysis.
Table 1-C
Table 1-C:
General information from the tDCS studies included in the meta-analysis.
Table 1-D
Table 1-D:
General information from the tDCS studies included in the meta-analysis.
Table 1-E
Table 1-E:
General information from the tDCS studies included in the meta-analysis.
Table 1-F
Table 1-F:
General information from the tDCS studies included in the meta-analysis.
Table 1-G
Table 1-G:
General information from the tDCS studies included in the meta-analysis.
Table 2
Table 2:
General information from the rTMS studies included in the meta-analysis.
Table 2-A
Table 2-A:
General information from the rTMS studies included in the meta-analysis.
Table 2-B
Table 2-B:
General information from the rTMS studies included in the meta-analysis.

3.2. Effect on outcomes

3.2.1. Pain threshold

We analyzed 20 RCTs8–11,14,17,18,21,22,25,26,32,34,36,38,43,55–57,64,73,74,78 (35 comparisons) with the healthy population (n = 629) (Fig. 2A) to evaluate the NIBS effects on PT. We found a significant and homogenous PT increase (ES: 0.16, 95% CI: 0.02-0.31; I2 = 22.2%) in favor of NIBS intervention compared with sham. When analyzing techniques separately, results were not significant; the 12 tDCS studies result in an effect size of 0.14 (95% CI: −0.03 to 0.31), whereas for the 8 rTMS studies, the pooled effect size was 0.24 (95% CI: −0.03 to 0.50), and the combination of both (tDCS + rTMS) effects was −0.09 (95% CI: −0.55 to 0.38). No significant difference was found in the heterogeneity test between subgroups (P = 0.426).

Figure 2.
Figure 2.:
Forest plot of pain threshold in (A) healthy populations and (B) pain conditions. rTMS, repetitive transcranial magnetic stimulation; SMD, standardized mean difference; tDCS, transcranial direct current stimulation.

Besides, we evaluated the PT changes due to NIBS interventions in the pain population (n = 492) from 14 RCTs1,6,12,15,20,37,40,41,49,52,53,62,69,76 (18 comparisons) (Fig. 2B). We found a significant PT increase in favor of NIBS (ES: 0.48, 95% CI: 0.15-0.89; I2 = 68.8%). However, we did not found differences (P = 0.790) among tDCS (ES: 0.47, 95% CI: 0.13-0.82) and rTMS (ES: 0.57, 95% CI: −0.12 to 1.25) effects.

3.2.2. Conditioned pain modulation

We analyzed 7 RCTs11,14,21,25,26,55,64 (10 comparisons) with the healthy population (n = 303) (Fig. 3A) that evaluate the NIBS effects on CPM effect (pain ratings reduction). We found a significant and homogenous higher CPM effect (ES: −0.39, 95% CI: −0.64 to −0.14; I2 = 17%) in favor of NIBS intervention compared with sham. The tDCS effect size was significant (ES: −0.50, 95% CI: −0.85 to −0.15), whereas the rTMS was not (ES: −0.20, 95% CI: −0.57 to 0.17). No significant difference was found in the heterogeneity test between subgroups (P = 0.195). Besides, we evaluated the CPM effects due to NIBS interventions in the pain population (n = 184) from 6 RCTs1,15,20,22,65,76 (8 comparisons) (Fig. 3B) compared with healthy subjects, and we found a significant and homogeneous CPM effect in favor of NIBS (ES: −0.35, 95% CI: −0.60 to −0.11; I2 = 0%). We did not found differences (P = 0.266) among tDCS (ES: −0.33, 95% CI: −0.58 to −0.07) and rTMS (ES: −0.35, 95% CI: −0.60 to −0.11) effects.

Figure 3.
Figure 3.:
Forest plot of conditioned pain modulation in (A) healthy populations and (B) pain conditions. SMD, standardized mean difference; tDCS, transcranial direct current stimulation; TMS, transcranial magnetic stimulation.

3.2.3. Temporal summation

We could not perform a meta-analysis because of lack of combinable data from the 2 included studies,34,49 1 included a healthy population34 and the other patients with chronic pain.49

3.3. Risk of bias assessment

Most of the selected articles (44.74%) had low risks of bias in several categories. However, most of them (60.53%) had problems when reporting randomization sequence generation and allocation concealment; although they specified the allocation of the subjects was done by a random method, they did not specify how the randomization sequence was generated. Besides, most of them (73.68%) did not specify how they achieved the allocation concealment; therefore, they were classified as unclear regarding this item. Furthermore, more than half of the selected articles (55.26%) presented a high risk of bias in the blinding component, as most of them did not blind the researcher performing the intervention. See Figure 4.

Figure 4.
Figure 4.:
Risk of bias.

3.4. Subgroup, sensitivity, and meta-regression analysis

The sensitivity analysis showed that results did not change even if the study with the largest effect was removed from the analysis and also when we excluded 1 study at a time. Moreover, after subgroup analysis and meta-regression, the risk of bias level, the combination with other interventions, the number of sessions (less or more than 1 session), stimulation polarity (excitatory vs inhibitory), and the type of stimulus (pressure, heat, cold, or electrical stimulus) were not important sources of heterogeneity in the CPM analysis (online supplementary material 5). However, we identified substantial sources of heterogeneity (I2 > 60%) in the PT analysis (the use of NIBS combined with other interventions, the stimulation polarity [excitatory vs inhibitory stimulation], and the type of stimulus [pressure, cold, or heat stimulus]). We evaluated the PT location (upper and lower limb) as a source of heterogeneity; we found, in the healthy population, a higher pooled effect size from studies with a lower limb as a location for the PT assessment compared with the upper limb location; however, we did not find this difference among the studies with the pain population (online supplementary 5).

Also, we performed a subgroup analysis by disease with 2 or more included studies (knee OA and fibromyalgia), we did not find any significant difference between conditions (online supplementary 5). Finally, we performed a subgroup analysis by conditions categorized by the underlying mechanisms: neuropathic pain states (peripheral neuropathy and poststroke pain), nociceptive states (osteoarthritis and low back pain), and nociplastic states (fibromyalgia); we found no difference in the CPM response between nociceptive and nociplastic states, but the PT increase was stronger in the nociplastic states (ES: 0.81, 95% CI: −0.01 to 1.63) than that in the neuropathic and nociceptive (ES: 0.15, 95% CI: −0.24 to 0.54; ES: 0.38, 95% CI: −0.01 to 0.78, respectively) states (online supplementary 5).

3.5. Publication bias

We did not find publication bias in the PT and CPM meta-analysis as indexed by symmetrical funnel plots and nonsignificant Egger test analysis (online supplementary material 6).

4. Discussion

4.1. Summary of results

We included 38 RCTs that have evaluated the effects of noninvasive motor cortex stimulation on QST outcomes in healthy and pain subjects. The included studies were heterogeneous, had small sample sizes, and presented a low to moderate risk of bias with no publication bias. We found a significant increase in PT and homogenous higher CPM effect (small to moderate effect size) in healthy subjects and pain disorders, in favor of the NIBS group compared with sham. These effects seem robust and consistent because all sensitivity analyses, subgroup analyses, and meta-regression could not identify any critical between-studies source of heterogeneity.

4.2. Motor cortex stimulation effects on pain threshold

Our meta-analysis found a small to moderate pooled effect of motor cortex stimulation by tDCS and rTMS on PTs; these results are consistent with one of the postulated mechanisms of action of NIBS: modulation of pain by the activation of subcortical structures related to the endogenous pain modulation system such as the thalamus, cingulate gyrus, periaqueductal gray, and SRD, among others.30,31 This endogenous pain modulation system could also affect the PT perception.

Regarding the type of stimuli to evaluate the PT changes, we included all the reported categories such as heat, cold, electrical, and mechanical pain stimulus. We did not find significant differences among the type of stimuli, which are consistent with the previous literature48; this would be useful for future design experiments and to increase the comparability of different PT protocols.

Previous systematic reviews and meta-analysis75 evaluated the effect of anodal tDCS on PT in healthy subjects compared with sham intervention. Similar to our results, they found a significant increase in PT (MD 12.57, 95% CI: 6.29-18.85); however, they did not report the results using a standardized effect size, which hinders the comparison with our findings.

Our findings by population show that both healthy and pain populations increased their PT values; however, we found higher increases in the pain population; these results could be explained due to a ceiling effect. In other words, pain neurocircuitry dysfunction provides a more extensive range of modulation of this system because there is a limit for the enhancement of the endogenous inhibitory pain system. This supports that noninvasive motor cortex stimulation is a brain state–dependent technique35 with a high potential to modulate pain, especially in dysfunctional and maladaptive pain networks in patients with chronic pain. However, owing to the heterogeneous included pain populations, further studies are needed to elucidate the effects in specific pain conditions.

4.3. Motor cortex stimulation effects on conditioned pain modulation

In this meta-analysis, both techniques (tDCS and rTMS) showed a similar direction in CPM effects in both healthy and pain populations, although they have different mechanisms of action. In contrast to the PT results by population, the CPM effect was similar in both, suggesting a higher neuroplasticity potential of the descending inhibitory pathways related to CPM effects and potentially less ceiling effect. It may also indicate that CPM is a better marker to address, understand, and measure the mechanistic effects of motor cortex stimulation.

We hypothesize that noninvasive motor cortex stimulation could have modulated motor cortex excitability restoring the inhibitory effects on pain circuits, as seen in neuropathic pain and other types of pain.3,47 In fact, lack of inhibition by the motor cortex leads to decreased endogenous pain inhibitory pathways.13,60 This fact is supported by some studies that showed CPM as a possible predictor of chronic pain development.39,60 Moreover, studies advocate that CPM could be used as a possible prognosis factor for pain-sensitized patients and, therefore, could be used as a predictor of higher pain level experience. One idea is also to explore CPM as a possible prognostic variable for tDCS and rTMS, as recently proposed in another trial.71 In addition, one possibility is to use motor cortex stimulation to enhance the endogenous pain inhibitory system as to “prevent” pain in a healthy population exposed to a nociceptive stimulus.4,28

More well-powered studies are needed to validate the CPM biomarker as a predictor of motor cortex stimulation effects in pain populations and to elucidate the relationship of CPM effect and pain levels in specific chronic pain populations.

4.4. Heterogeneity of methods of quantitative sensory testing and noninvasive brain stimulation protocols

The behavioral protocols change across the studies, measuring different variables of pain processing with different QST protocols; almost half of the studies used pressure PT, whereas others used heat, cold, or electrical stimuli. On the other hand, cold water stimuli were the most frequently used as the conditioning stimulus in CPM. We found that the type stimulus in the PT protocols is an important source of heterogeneity in the meta-analysis of pain populations; however, the pooled effect sizes are similar among those subgroups (online supplementary 5). In this context, the different QST protocols should not be a source of heterogeneity. In addition, different anatomical parts such as the forearm, hand, feet, and knee, among others, were used for the QST assessment. Although the healthy population should not be affected in different pain conditions, these different locations would be related to peripheral and central sensitization. Therefore, the information of these results might contribute to the heterogeneity and accuracy of our findings.

Another factor of heterogeneity of significant value is the difference in the stimulation parameters. Although we selected studies that had investigated the effects of the stimulation on the same cortical area, there are known differences between the underlying mechanisms of tDCS and rTMS and the number of sessions. However, we decided to do an exploratory pooled analysis42–44,49,50,52 because most of the included studies used an excitatory protocol over the motor cortex.

In addition, the statistical approach to analyze the QST outcomes (eg, proportion vs absolute number changes), the presence or not of follow-up, and quantity and duration variation of QST assessments across all the included studies (Table 1) highlight the need of acquiring more standardized data for a more precise QST outcome changes evaluation.

4.5. Transcranial direct current stimulation and repetitive transcranial magnetic stimulation mechanisms to modulate quantitative sensory testing

The QST is a more objective measurement of pain perception processes.67 It includes different tasks such as sensory pain testing, PT, CPM, and TS. These different measurements assess peripheral and central sensitization. The pain signal arrives in the dorsal horn and then crosses the midline just in front of the anterior commissure and sent the signal up by the spinothalamic tract to the thalamus and then to the sensory cortex.77 Once pain signals arrive in the sensory area, it is processed and interpreted as a PT.77 Then, the signal sends feedback through supraspinal structures such as the primary motor cortex, sensory cortex, thalamus, and other structures such as the cingulate gyrus, periaqueductal gyrus, rostral ventromedial medulla, SRD, and spinal cord, in order to enhance the endogenous pain modulation system decreasing the pain perception. In a healthy population, this mechanism is believed to contrast the pain stimulus.77 However, in chronic pain, there is a disruption in this communication, decreasing the PT and increasing pain perception.63 This effect disrupts the endogenous pain pathway that can be measured with the CPM.58

It is still unclear whether the differential mechanism of rTMS compared with tDCS on the motor cortex would represent a different mechanism of endogenous pain inhibitory system modulation, although the final effect is similar. Transcranial direct current stimulation delivers a continuous transcranial subthreshold current inducing long-lasting modulation of the neuronal activity by mechanisms of long-term potentiation and long-term depression and therefore changing synaptic plasticity mechanisms.19,29 On the other hand, rTMS induces an action potential and thus a response of the neuronal membrane and thereby, different frequencies of pulses can enhance or inhibit excitability in the targeted region,29 although some differences in the mechanisms, both of them have shown capability of inducing long-term effects related to neuroplastic mechanisms of pain.29 The rationale behind using motor cortex stimulation relies on the ability to potentiate the endogenous pain modulation system. Motor cortex stimulation ultimately modulates other circuits such as the thalamus and other structures such as the sensory cortex, cingulate gyrus, periaqueductal gyrus, and SRD. These structures control the inhibition/facilitation of pain perception and, ultimately, the PT and CPM effects. Hence, these techniques have the capacity to modulate these structures by a top-down modulation in healthy and pain conditions indexed by QST outcome changes.

The potential therapeutic implications of NIBS are plausible, especially using motor cortex stimulation; however, these results seem brain state–dependent35 and possibly disease-related, although we reported here a possible larger modulation of PT in nociplastic pain syndromes, such as fibromyalgia, the small sample size, and higher heterogeneity among the current evidence difficult to draw a definitive conclusion.

4.6. Limitations

Some factors may limit these results and thus should be interpreted with caution. One crucial factor, as mentioned, is the heterogeneity of the QST measurement and the NIBS protocols. Patients with chronic pain presented different syndromes across the studies that result in different mechanisms of pain and differential responsiveness to the stimulation. To address this problem, we decided to divide the results in healthy and pain conditions because combining the pain population with healthy subjects could bias the results. Another limitation is the inclusion of pilot studies and not adequately justified sample size calculation by a statistical power analysis. Finally, as shown by Cochrane risk bias indexes, some of the studies included did not describe the randomization accurately and/or blinding procedures, thus leading to potentially lower quality of the data included in the analysis. However, the comprehensive and systematic methodology used in this study assures the high-quality summary of all the studies to date in the field and motivates the conduct of future research with improved designs.

5. Conclusion

This meta-analysis suggests a significant small to moderate effect of noninvasive motor cortex stimulation on PT and CPM in healthy and pain populations. This supports the idea of top-down modulation of endogenous pain pathways by motor cortex stimulation as one of their primary mechanism of action on pain. These biomarkers could be useful in the treatment follow-up of patients with chronic pain. However, validation requires further investigation under strict methodological settings and with an evaluation of specific chronic pain populations.

Conflict of interest statement

The authors have no conflicts of interest to declare.

Acknowledgments

This study was funded by NIH grant R01 AT009491-01A1.

Author Contributions: All authors designed the study. S. Giannoni-Luza, J.L. Barouh, M. Gnoatto-Medeiros, L. Candido-Santos, P.F. Mejia-Pando, M.A. Luna-Cuadros, A. Barra, and K. Pacheco-Barrios collected the data. K. Pacheco-Barrios and A. Cardenas-Rojas performed statistical analyses. All authors participated in the interpretation of the results and the writing of the manuscript, and approved of its final version.

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Keywords:

Noninvasive brain stimulation; Transcranial magnetic stimulation; Transcranial direct current stimulation; Quantitative sensory testing

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