Specific Electroencephalographic Signatures for Pain and Descending Pain Inhibitory System in Spinal Cord Injury

Modulations in high-density EEG during the suppression of phantom-limb pain with neurostimulation in upper limb amputees

Phantom limb pain (PLP) is a distressing and persistent sensation that occurs after the amputation of a limb. While medication-based treatments have limitations and adverse effects, neurostimulation is a promising alternative approach whose mechanism of action needs research, including electroencephalographic (EEG) recordings for the assessment of cortical manifestation of PLP relieving effects. Here we collected and analyzed high-density EEG data in 3 patients (P01, P02, and P03). Peripheral nerve stimulation suppressed PLP in P01 but was ineffective in P02. In contrast, transcutaneous electrical nerve stimulation was effective in P02. In P03, spinal cord stimulation was used to suppress PLP. Changes in EEG oscillatory components were analyzed using spectral analysis and Petrosian fractal dimension. With these methods, changes in EEG spatio-spectral components were found in the theta, alpha, and beta bands in all patients, with these effects being specific to each individual. The changes in the EEG patterns were found for both the periods when PLP level was stationary and the periods when PLP was gradually changing after neurostimulation was turned on or off. Overall, our findings align with the proposed roles of brain rhythms in thalamocortical dysrhythmia or disruption of cortical excitation and inhibition which has been linked to neuropathic pain. The individual differences in the observed effects could be related to the specifics of each patient's treatment and the unique spectral characteristics in each of them. These findings pave the way to the closed-loop systems for PLP management where neurostimulation parameters are adjusted based on EEG-derived markers.

Sleep disturbance correlated with severity of neuropathic pain in sciatic nerve crush injury model

The association between sleep and pain has been investigated widely. However, inconsistent results from animal studies compared with human data show the need for a validated animal model in the sleep-pain association field. Our study aims to validate common neuropathic pain models as a tool for evaluating the sleep-pain association. Electrodes electroencephalogram (EEG) and electromyogram (EMG) were surgically implanted to measure sleep. The von Frey test was used to measure pain sensitivity. Following the baseline data acquisition, two pain-modelling procedures were performed: sciatic nerve crush injury (SCI) and common peroneal nerve ligation (CPL). Post-injury measurements were performed on days 1, 5, 10, and 15 post-surgery. The results presented decreased paw withdrawal thresholds and reduced NREM sleep duration in both models on the first post-surgery day. In the SCI model, NREM sleep duration was negatively correlated with paw withdrawal thresholds (p = 0.0466), but not in the CPL model. Wake alpha and theta EEG powers were also correlated with the pain threshold. The results confirm that the SCI model shows disturbed sleep patterns associated with increased pain sensitivity, suggesting it is a reliable tool for investigating sleep disturbances associated with neuropathic pain.

OPRM1 and BDNF polymorphisms associated with a compensatory neurophysiologic signature in knee osteoarthritis patients

OBJECTIVE

The present study investigated the relationship between three genetic polymorphisms of OPRM1 (rs1799971 - A118G and rs1799972 - C17T) and BDNF (rs6265 - C196T) and EEG-measured brain oscillations in Knee Osteoarthritis (KOA) patients.

MATERIALS AND METHODS

We performed a cross-sectional analysis of a cohort study (DEFINE cohort), KOA arm, with 66 patients, considering demographic (age, sex, and education), clinical (pain intensity and duration), OPRM1 (rs1799971 - A118G and rs1799972 - C17T) and BDNF (rs6265 - C196T) genotypes, and electrophysiological measures. Brain oscillations relative power from Delta, Theta, Alpha, Low Alpha, High Alpha, Beta, Low Beta and High Beta oscillations were measured during resting state EEG. Multivariate regression models were used to explore the main brain oscillation predictors of the three genetic polymorphisms.

RESULTS

Our findings demonstrate that Theta and Low Beta oscillations are associated with the variant allele of OPRM1-rs1799971 (A118G) on left frontal and left central regions, respectively, while Alpha brain oscillation is associated with variant genotypes (CT/TT) of BDNF-rs6265 on frontal (decrease of oscillation power) and left central (increase of oscillation power) regions. No significant model was found for OPRM1-rs1799972 (C17T) in addition to the inclusion of pain intensity as a significant predictor of this last model.

CONCLUSION

One potential interpretation for these findings is that polymorphisms of OPRM1 - that is involved with endogenous pain control - lead to increased compensatory oscillatory mechanisms, characterized by increased theta oscillations. Along the same line, polymorphisms of the BDNF lead to decreased alpha oscillations in the frontal area, likely also reflecting the disruption of resting states to also compensate for the increased injury associated with knee OA. It is possible that these polymorphisms require additional brain adaption to the knee OA related injury.

Electroacupuncture alleviates postoperative pain through inhibiting neuroinflammation via stimulator of interferon genes/type-1 interferon pathway

OBJECTIVE

This work explores the impact of electroacupuncture (EA) on acute postoperative pain (APP) and the role of stimulator of interferon genes/type-1 interferon (STING/IFN-1) signaling pathway modulation in the analgesic effect of EA in APP rats.

METHODS

The APP rat model was initiated through abdominal surgery and the animals received two 30 min sessions of EA at bilateral ST36 (Zusanli) and SP6 (Sanyinjiao) acupoints. Mechanical, thermal and cold sensitivity tests were performed to measure the pain threshold, and electroencephalograms were recorded in the primary somatosensory cortex to identify the effects of EA treatment on APP. Western blotting and immunofluorescence were used to examine the expression and distribution of proteins in the STING/IFN-1 pathway as well as neuroinflammation. A STING inhibitor (C-176) was administered intrathecally to verify its role in EA.

RESULTS

APP rats displayed mechanical and thermal hypersensitivities compared to the control group (P < 0.05). APP significantly reduced the amplitude of θ, α and γ oscillations compared to their baseline values (P < 0.05). Interestingly, expression levels of proteins in the STING/IFN-1 pathway were downregulated after inducing APP (P < 0.05). Further, APP increased pro-inflammatory factors, including interleukin-6, tumor necrosis factor-α and inducible nitric oxide synthase, and downregulated anti-inflammatory factors, including interleukin-10 and arginase-1 (P < 0.05). EA effectively attenuated APP-induced painful hypersensitivities (P < 0.05) and restored the θ, α and γ power in APP rats (P < 0.05). Meanwhile, EA distinctly activated the STING/IFN-1 pathway and mitigated the neuroinflammatory response (P < 0.05). Furthermore, STING/IFN-1 was predominantly expressed in isolectin-B4- or calcitonin-gene-related-peptide-labeled dorsal root ganglion neurons and superficial laminae of the spinal dorsal horn. Inhibition of the STING/IFN-1 pathway by intrathecal injection of C-176 weakened the analgesic and anti-inflammatory effects of EA on APP (P < 0.05).

CONCLUSION

EA can generate robust analgesic and anti-inflammatory effects on APP, and these effects may be linked to activating the STING/IFN-1 pathway, suggesting that STING/IFN-1 may be a target for relieving APP. Please cite this article as: Ding YY, Xu F, Wang YF, Han LL, Huang SQ, Zhao S, Ma LL, Zhang TH, Zhao WJ, Chen XD. Electroacupuncture alleviates postoperative pain through inhibiting neuroinflammation via stimulator of interferon genes/type-1 interferon pathway. J Integr Med. 2023; 21(5): 496-508.

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

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.

Functional Changes in Cortical Activity of Patients Submitted to Knee Osteoarthritis Treatment: An Exploratory Pilot Study

INTRODUCTION

There is evidence that brain plasticity is the central mechanism involved in the functional recovery process of patients with knee osteoarthritis. Studies involving the analysis of central nervous system mechanisms of pain control and recovery could provide more data on future therapeutic approaches.

OBJECTIVE

The aim of the study was to explore possible functional changes in cortical activity of patients submitted to knee osteoarthritis standardized pain treatment using electroencephalography.

METHODOLOGY

Ten patients with clinical and radiological diagnosis of painful knee unilateral or bilateral osteoarthritis were recruited to participate in clinical (Pain's Visual Analog Scale), radiological (Kellgren-Lawrence Scale), and neurophysiological (electroencephalography) assessments to evaluate cortical activity during cortical pain modulation activity. The clinical and neurophysiological analyses were performed before and after standardized pain treatment.

RESULTS

Eight patients participated in this study. A significant improvement in pain perception and relative increase in interhemispheric connectivity after therapies was observed. In electroencephalography analysis, tests with real movement showed a relative increase in density directed at Graph's analysis.

CONCLUSIONS

Relative increase density directed measures at connectivity analysis in electroencephalography after pain treatment can be possible parameters to be explored in future research with a larger number of patients.

Analytic consistency and neural correlates of peak alpha frequency in the study of pain

BACKGROUND

Several studies have found evidence of reduced resting-state peak alpha frequency (PAF) in populations with pain. However, the stability of PAF from different analytic pipelines used to study pain has not been determined and underlying neural correlates of PAF have not been validated in humans.

NEW METHOD

For the first time we compare analytic pipelines and the relationship of PAF to activity in the whole brain and thalamus, a hypothesized generator of PAF. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data and subsequently 64 channel resting-state electroencephalographic (EEG) from 47 healthy men, controls from an ongoing study of chronic prostatitis (a pain condition affecting men). We identified important variations in EEG processing for PAF from a review of 17 papers investigating the relationship between pain and PAF. We tested three progressively complex pre-processing pipelines and varied four postprocessing variables (epoch length, alpha band, calculation method, and region-of-interest [ROI]) that were inconsistent across the literature.

RESULTS

We found a single principal component, well-represented by the average PAF across all electrodes (grand-average PAF), explained > 95% of the variance across participants. We also found the grand-average PAF was highly correlated among the pre-processing pipelines and primarily impacted by calculation method and ROI. Across methods, interindividual differences in PAF were correlated with rs-fMRI-estimated activity in the thalamus, insula, cingulate, and sensory cortices.

CONCLUSIONS

These results suggest PAF is a relatively stable marker with respect to common pre and post-processing methods used in pain research and reflects interindividual differences in thalamic and salience network function.

EEG theta and beta bands as brain oscillations for different knee osteoarthritis phenotypes according to disease severity

This study aims to investigate the multivariate relationship between different sociodemographic, clinical, and neurophysiological variables with resting-state, high-definition, EEG spectral power in subjects with chronic knee osteoarthritis (OA) pain. This was a cross-sectional study. Sociodemographic and clinical data were collected from 66 knee OA subjects. To identify associated factors, we performed independent univariate and multivariate regression models by frequency bands (delta, theta, alpha, beta, low-beta, and high-beta) and by pre-defined regions (frontal, central, and parietal). From adjusted multivariate models, we found that: (1) increased frontocentral high-beta power and reduced central theta activity are positively correlated with pain intensity (β = 0.012, 95% CI 0.004-0.020; and β = - 0.008; 95% CI 0.014 to - 0.003; respectively); (2) delta and alpha oscillations have a direct relationship with higher cortical inhibition; (3) diffuse increased power at low frequencies (delta and theta) are associated with poor cognition, aging, and depressive symptoms; and (4) higher alpha and beta power over sensorimotor areas seem to be a maladaptive compensatory mechanism to poor motor function and severe joint degeneration. Subjects with higher pain intensity and higher OA severity (likely subjects with maladaptive compensatory mechanisms to severe OA) have higher frontocentral beta power and lower theta activity. On the other hand, subjects with less OA severity and less pain have higher theta oscillations power. These associations showed the potential role of brain oscillations as a marker of pain intensity and clinical phenotypes in chronic knee OA patients. Besides, they suggest a potential compensatory mechanism of these two brain oscillators according to OA severity.

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

 

Conditioned pain modulation (CPM) can discriminate between healthy and chronic pain patients. However, its relationship with neurophysiological pain mechanisms is poorly understood. Brain oscillations measured by electroencephalography (EEG) might help gain insight into this complex relationship.

OBJECTIVE

To investigate the relationship between CPM response and self-reported pain intensity in non-specific chronic low back pain (NSCLBP) and explore respective EEG signatures associated to these mechanisms.

DESIGN

Cross-sectional analysis. Participants: Thirty NSCLBP patients participated.

METHODS

Self-reported low back pain, questionnaires, mood scales, CPM (static and dynamic quantitative sensory tests), and resting surface EEG data were collected and analyzed. Linear regression models were used for statistical analysis.

RESULTS

CPM was not significantly correlated with self-reported pain intensity scores. Relative power of EEG in the beta and high beta bands as recorded from the frontal, central, and parietal cortical areas were significantly associated with CPM. EEG relative power at delta and theta bands as recorded from the central area were significantly correlated with self-reported pain intensity scores while controlling for self-reported depression.

CONCLUSIONS

Faster EEG frequencies recorded from pain perception areas may provide a signature of a potential cortical compensation caused by chronic pain states. Slower EEG frequencies may have a critical role in abnormal pain processing.

EEG Signal Complexity Is Reduced During Resting-State in Fragile X Syndrome

Introduction: Fragile X syndrome (FXS) is a genetic disorder caused by a mutation of the fragile X mental retardation 1 gene (FMR1). FXS is associated with neurophysiological abnormalities, including cortical hyperexcitability. Alterations in electroencephalogram (EEG) resting-state power spectral density (PSD) are well-defined in FXS and were found to be linked to neurodevelopmental delays. Whether non-linear dynamics of the brain signal are also altered remains to be studied. Methods: In this study, resting-state EEG power, including alpha peak frequency (APF) and theta/beta ratio (TBR), as well as signal complexity using multi-scale entropy (MSE) were compared between 26 FXS participants (ages 5-28 years), and 7 neurotypical (NT) controls with a similar age distribution. Subsequently a replication study was carried out, comparing our cohort to 19 FXS participants independently recorded at a different site. Results: PSD results confirmed the increased gamma, decreased alpha power and APF in FXS participants compared to NT controls. No alterations in TBR were found. Importantly, results revealed reduced signal complexity in FXS participants, specifically in higher scales, suggesting that altered signal complexity is sensitive to brain alterations in this population. The replication study mostly confirmed these results and suggested critical points of stagnation in the neurodevelopmental curve of FXS. Conclusion: Signal complexity is a powerful feature that can be added to the electrophysiological biomarkers of brain maturation in FXS.