Electroencephalography Signatures for Conditioned Pain Modulation and Pain Perception in Non-Specific Chronic Low Back Pain-an Exploratory Study

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients

Introduction

Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known.

Methods

We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data.

Results

As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia.

Discussion

These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.

Functional and Neural Correlates Associated with Conditioned Pain Modulation in Patients with Chronic Knee Osteoarthritis Pain: A Cross-Sectional Study

Background: In this study, we aimed to assess the factors that predict a dysfunctional conditioned pain modulation (CPM) in chronic knee OA. Methods: This is a cross-sectional analysis of patients with chronic knee OA from a prospective cohort study in Brazil (n = 85). We performed linear and logistic multivariate regression models using the purposeful selection approach to test the relationship between the CPM in both knees (average) as a dependent variable and demographics, clinical, and neurophysiological as independent variables. Results: A significant negative association between WOMAC pain scores and CPM (β: -0.13) was found. This association was modified by the subjects' race, being stronger in the non-white subjects. In our logistic regression models, pain intensity indexed with the WOMAC pain scale remained a significant association with dichotomized CPM. Furthermore, a significant CPM association with balance, indexed with the Berg Balance score, was evidenced (β: 0.04). Neurophysiological variables showed a significant negative relationship with CPM, such as the relative power of delta oscillations in the frontal area (β: -3.11) and central area (β: -3.23). There was no significant relationship between CPM and the following domains: cognitive, emotion, sleep, opioid receptor polymorphisms, and intrinsic variables of OA disease. There was no association of CPM with TMS-indexed inhibitory markers. Conclusions: These results may indicate that less function of the pain descending inhibitory system in patients with OA is correlated with higher activity-related pain (WOMAC), less balance, and cortical plasticity especially with increased low-frequency (delta) brain oscillations. These associations seem modified by race.

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.

Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review

ABSTRACT

Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.

Temporal Summation in Fibromyalgia Patients: Comparing Phasic and Tonic Paradigms

Introduction

Fibromyalgia (FM) is associated with dysfunctional pain modulation mechanisms, including central sensitization. Experimental pain measurements, such as temporal summation (TS), could serve as markers of central sensitization and have been previously studied in these patients, with conflicting results. Our objective in this study was to explore the relationships between two different protocols of TS (phasic and tonic) and test the associations between these measures and other clinical variables.

Materials and Methods

In this cross-sectional analysis of a randomized clinical trial, patients were instructed to determine their pain-60 test temperature, then received one train of 15 repetitive heat stimuli and rated their pain after the 1st and 15th stimuli: TSPS-phasic was calculated as the difference between those. We also administered a tonic heat test stimulus at the same temperature continuously for 30 s and asked them to rate their pain levels after 10 s and 30 s, calculating TSPS-tonic as the difference between them. We also collected baseline demographic data and behavioral questionnaires assessing pain, depression, fatigue, anxiety, sleepiness, and quality of life. We performed univariable analyses of the relationship between TSPS-phasic and TSPS-tonic, and between each of those measures and the demographic and clinical variables collected at baseline. We then built multivariable linear regression models to find predictors for TSPS-phasic and TSPS-tonic, while including potential confounders and avoiding collinearity.

Results

Fifty-two FM patients were analyzed. 28.85% developed summation during the TSPS-phasic protocol while 21.15% developed summation during the TSPS-tonic protocol. There were no variables associated TSPS phasic or tonic in the univariable analyses and both measures were not correlated. On the multivariate model for the TSPS-phasic protocol, we found a weak association with pain variables. BPI-pain subscale was associated with more temporal summation in the phasic protocol (ß = 0.38, p = 0.029), while VAS for pain was associated with less summation in the TSPS-tonic protocol (ß = −0.5, p = 0.009).

Conclusion

Our results suggest that, using heat stimuli with pain-60 temperatures, a TSPS-phasic protocol and a TSPS-tonic protocol are not correlated and could index different neural responses in FM subjects. Further studies with larger sample sizes would be needed to elucidate whether such responses could help differentiating subjects with FM into specific phenotypes.