Electroencephalographic Patterns in Chronic Pain: A Systematic Review of the Literature

Diagnostic Biomarkers for Upper Extremity Chronic Pain Conditions

Hand surgery patients often experience chronic pain conditions. However, there are few reliable ways to measure pain, making diagnosis and subsequent management of these conditions notably challenging for the hand surgeon. Various diagnostic biomarkers have been actively studied in the chronic pain management field with promising results. This review discusses the development of diagnostic biomarkers for chronic pain conditions of the upper extremity, including complex regional pain syndrome, osteoarthritis, and neuropathic pain. Techniques involving the measurements of heart rate variability, molecular biomarkers including inflammatory and noninflammatory molecules, metabolites, and exosomes, magnetic resonance imagining and electroencephalography, as well as skin biopsy, are discussed. Future potential applications are proposed.

EEG Beta-Band Spectral Entropy Can Predict the Effect of Drug Treatment on Pain in Patients With Herpes Zoster

BACKGROUND

Medication is the main approach for early treatment of herpes zoster, but it could be ineffective in some patients. It is highly desired to predict the medication responses to control the degree of pain for herpes zoster patients. The present study is aimed to elucidate the relationship between medication outcome and neural activity using EEG and to establish a machine learning model for early prediction of the medication responses from EEG.

METHODS

The authors acquired and analyzed eye-closed resting-state EEG data 1 to 2 days after medication from 70 herpes zoster patients with different drug treatment outcomes (measured 5-6 days after medication): 45 medication-sensitive pain patients and 25 medication-resistant pain patients. EEG power spectral entropy of each frequency band was compared at each channel between medication-sensitive pain and medication-resistant pain patients, and those features showing significant difference between two groups were used to predict medication outcome with different machine learning methods.

RESULTS

Medication-sensitive pain patients showed significantly weaker beta-band power spectral entropy in the central-parietal regions than medication-resistant pain patients. Based on these EEG power spectral entropy features and a k-nearest neighbors classifier, the medication outcome can be predicted with 80% ± 11.7% accuracy, 82.5% ± 14.7% sensitivity, 77.7% ± 27.3% specificity, and an area under the receiver operating characteristic curve of 0.85.

CONCLUSIONS

EEG beta-band power spectral entropy in the central-parietal region is predictive of the effectiveness of drug treatment on herpes zoster patients, and it could potentially be used for early pain management and therapeutic prognosis.

Scalp EEG-based Pain Detection using Convolutional Neural Network

Pain is an integrative phenomenon coupled with dynamic interactions between sensory and contextual processes in the brain, often associated with detectable neurophysiological changes. Recent advances in brain activity recording tools and machine learning technologies have intrigued research and development of neurocomputing techniques for objective and neurophysiology-based pain detection. This paper proposes a pain detection framework based on Electroencephalogram (EEG) and deep convolutional neural networks (CNN). The feasibility of CNN is investigated for distinguishing induced pain state from resting state in the recruitment of 10 chronic back pain patients. The experimental study recorded EEG signals in two phases: 1. movement stimulation (MS), where induces back pain by executing predefined movement tasks; 2. video stimulation (VS), where induces back pain perception by watching a set of video clips. A multi-layer CNN classifies the EEG segments during the resting state and the pain state. The novel approach offers high and robust performance and hence is significant in building a powerful pain detection algorithm. The area under the receiver operating characteristic curve (AUC) of our approach is 0.83±0.09 and 0.81±0.15, in MS and VS, respectively, higher than the state-of-the-art approaches. The sub-brain-areas are also analyzed, to examine distinct brain topographies relevant for pain detection. The results indicate that MS-induced pain tends to evoke a generalized brain area, while the evoked area is relatively partial under VS-induced pain. This work may provide a new solution for researchers and clinical practitioners on pain detection.

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.

Brain Imaging Biomarkers for Chronic Pain

The prevalence of chronic pain has reached epidemic levels. In addition to personal suffering chronic pain is associated with psychiatric and medical co-morbidities, notably substance misuse, and a huge a societal cost amounting to hundreds of billions of dollars annually in medical cost, lost wages, and productivity. Chronic pain does not have a cure or quantitative diagnostic or prognostic tools. In this manuscript we provide evidence that this situation is about to change. We first start by summarizing our current understanding of the role of the brain in the pathogenesis of chronic pain. We particularly focus on the concept of learning in the emergence of chronic pain, and the implication of the limbic brain circuitry and dopaminergic signaling, which underly emotional learning and decision making, in this process. Next, we summarize data from our labs and from other groups on the latest brain imaging findings in different chronic pain conditions focusing on results with significant potential for translation into clinical applications. The gaps in the study of chronic pain and brain imaging are highlighted in throughout the overview. Finally, we conclude by discussing the costs and benefits of using brain biomarkers of chronic pain and compare to other potential markers.

Shedding light on pain for the clinic: a comprehensive review of using functional near-infrared spectroscopy to monitor its process in the brain

ABSTRACT

Pain is a complex experience that involves sensation, emotion, and cognition. The subjectivity of the traditional pain measurement tools has expedited the interest in developing neuroimaging techniques to monitor pain objectively. Among noninvasive neuroimaging techniques, functional near-infrared spectroscopy (fNIRS) has balanced spatial and temporal resolution; yet, it is portable, quiet, and cost-effective. These features enable fNIRS to image the cortical mechanisms of pain in a clinical environment. In this article, we evaluated pain neuroimaging studies that used the fNIRS technique in the past decade. Starting from the experimental design, we reviewed the regions of interest, probe localization, data processing, and primary findings of these existing fNIRS studies. We also discussed the fNIRS imaging's potential as a brain surveillance technique for pain, in combination with artificial intelligence and extended reality techniques. We concluded that fNIRS is a brain imaging technique with great potential for objective pain assessment in the clinical environment.

Altered Dynamic Brain Connectivity in Individuals With Sickle Cell Disease and Chronic Pain Secondary to Hip Osteonecrosis

Individuals with sickle cell disease (SCD) exhibit changes in static brain connectivity in rest. However, little known as chronic pain associated with hip osteonecrosis affects dynamic brain connectivity during rest and the motor imagery task. The aim of this study was to investigate the characteristics of the dynamic functional brain connectivity of individuals with SCD and chronic pain secondary to hip osteonecrosis. This is a cross-sectional study comparing the dynamic brain connectivity of healthy individuals (n = 18) with the dynamic brain connectivity of individuals with SCD and chronic pain (n = 22). Individuals with SCD and chronic pain were stratified into high- or low-intensity pain groups based on pain intensity at the time of assessment. Dynamic brain connectivity was assessed through electroencephalography in 3 stages, resting state with eyes closed, and during hip (painful for the SCD individuals) and hand (control, nonpainful) motor imagery. Average weight of the edges and full synchronization time (FST)-time required for 95% of the possible edges to appear over time during a given task-were evaluated. Regarding the average weight of the edges, individuals with SCD and high-intensity pain presented higher edge weight during hip motor imagery. The average weight of the edges correlated positively with pain intensity and depression symptoms. Individuals with SCD and chronic pain complete the cerebral network at rest more quickly (lower FST). Individuals with SCD and chronic pain/hip osteonecrosis have impaired dynamic brain network with shorter FST in rest network and more pronounced diffuse connectivity in individuals with high-intensity pain. The dynamic brain network evaluated by time-varying graphs and motif synchronization was able to identify differences between groups.

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.

Decoding pain from brain activity

Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.

Profiling Transcription Initiation in Peripheral Leukocytes Reveals Severity-Associated Cis-Regulatory Elements in Critical COVID-19

The contribution of transcription factors (TFs) and gene regulatory programs in the immune response to COVID-19 and their relationship to disease outcome is not fully understood. Analysis of genome-wide changes in transcription at both promoter-proximal and distal cis-regulatory DNA elements, collectively termed the 'active cistrome,' offers an unbiased assessment of TF activity identifying key pathways regulated in homeostasis or disease. Here, we profiled the active cistrome from peripheral leukocytes of critically ill COVID-19 patients to identify major regulatory programs and their dynamics during SARS-CoV-2 associated acute respiratory distress syndrome (ARDS). We identified TF motifs that track the severity of COVID- 19 lung injury, disease resolution, and outcome. We used unbiased clustering to reveal distinct cistrome subsets delineating the regulation of pathways, cell types, and the combinatorial activity of TFs. We found critical roles for regulatory networks driven by stimulus and lineage determining TFs, showing that STAT and E2F/MYB regulatory programs targeting myeloid cells are activated in patients with poor disease outcomes and associated with single nucleotide genetic variants implicated in COVID-19 susceptibility. Integration with single-cell RNA-seq found that STAT and E2F/MYB activation converged in specific neutrophils subset found in patients with severe disease. Collectively we demonstrate that cistrome analysis facilitates insight into disease mechanisms and provides an unbiased approach to evaluate global changes in transcription factor activity and stratify patient disease severity.

Change in Brain Oscillations as a Mechanism of Mindfulness-Meditation, Cognitive Therapy, and Mindfulness-Based Cognitive Therapy for Chronic Low Back Pain

OBJECTIVE

Psychological treatments for chronic low back pain (CLBP) are effective. However, limited research has investigated their neurophysiological mechanisms. This study examined electroencephalography- (EEG-) assessed brain oscillation changes as potential mechanisms of cognitive therapy (CT), mindfulness-meditation (MM), and mindfulness-based cognitive therapy (MBCT) for CLBP. The a priori bandwidths of interest were changes in theta, alpha and beta power, measured at pre- and post-treatment.

DESIGN

A secondary analysis of a clinical trial.

SETTING

University of Queensland Psychology Clinic.

SUBJECTS

Adults (N = 57) with CLBP who completed pre- and post-treatment EEG and pain outcome assessments.

METHODS

EEG data were examined for five regions of interest (ROIs); the primary outcome was pain intensity.

RESULTS

A significant reduction in theta (P=.015) and alpha (P=.006) power in the left frontal ROI across all treatments was found, although change in theta and alpha power in this region was not differentially associated with outcome across treatments. There were significant reductions in beta power in all five ROIs across all treatments (P≤.013). Beta power reduction in the central ROI showed a significant association with reduced pain intensity in MBCT only (P=.028). Changes in other regions were not statistically significant.

CONCLUSIONS

These findings provide support for the capacity of psychological CLBP treatments to induce changes in brain activity. The reduced beta power in all five ROIs indicated that all three treatments engendered a state of lowered cortical arousal. The growing body of research in this area could potentially inform novel directions towards remedying central nervous system abnormalities associated with CLBP.

Fibromyalgia Detection Based on EEG Connectivity Patterns

Objective: The identification of a complementary test to confirm the diagnosis of FM. The diagnosis of fibromyalgia (FM) is based on clinical features, but there is still no consensus, so patients and clinicians might benefit from such a test. Recent findings showed that pain lies in neuronal bases (pain matrices) and, in the long term, chronic pain modifies the activity and dynamics of brain structures. Our hypothesis is that patients with FM present lower levels of brain activity and therefore less connectivity than controls. Methods: We registered the resting state EEG of 23 patients with FM and compared them with 23 control subjects’ resting state recordings from the PhysioBank database. We measured frequency, amplitude, and functional connectivity, and conducted source localization (sLORETA). ROC analysis was performed on the resulting data. Results: We found significant differences in brain bioelectrical activity at rest in all analyzed bands between patients and controls, except for Delta. Subsequent source analysis provided connectivity values that depicted a distinct profile, with high discriminative capacity (between 91.3–100%) between the two groups. Conclusions: Patients with FM show a distinct neurophysiological pattern that fits with the clinical features of the disease.

Low Back Pain Assessment Based on Alpha Oscillation Changes in Spontaneous Electroencephalogram (EEG)

Objectively and accurately assessing pain in clinical settings is challenging. Previous studies showed that alpha oscillations of electroencephalogram data are correlated with subjective perceived pain. Based on this finding, this study is aimed at assessing chronic low back pain based on alpha oscillations. Multichannel electroencephalogram data were recorded from 27 subjects with chronic low back pain under the simple conditions of closing eyes or opening eyes. Spectral analyses were conducted to extract the alpha band responses, and the alpha powers were calculated for the two conditions, respectively. Normalized alpha power was calculated by subtracting the alpha power in the eyes-open condition from that in the eyes-closed condition. The correlation between the alpha power and the subjective pain intensity was evaluated in frontal, central, and posterior regions. The normalized alpha power in the central region was negatively correlated with the subjective pain intensity (R = -0.50, P = 0.01), with the strongest correlation occurring at the Cz electrode (R = -0.59, P = 0.04). The correlation analysis results demonstrated the possibility of using the differences of alpha spectral power between eyes-closed and eyes-open conditions as a measure for assessing chronic low back pain. The findings suggest that the normalized alpha power in the central region may be used as a measurable and quantitative indicator of chronic pain for clinical applications.

The breathing brain: The potential of neural oscillations for the understanding of respiratory perception in health and disease

Dyspnea or breathlessness is a symptom occurring in multiple acute and chronic illnesses, however, the understanding of the neural mechanisms underlying its subjective experience is limited. In this topical review, we propose neural oscillatory dynamics and cross-frequency coupling as viable candidates for a neural mechanism underlying respiratory perception, and a technique warranting more attention in respiration research. With the evidence for the potential of neural oscillations in the study of normal and disordered breathing coming from disparate research fields with a limited history of interdisciplinary collaboration, the main objective of the review was to converge the existing research and suggest future directions. The existing findings show that distinct limbic and cortical activations, as measured by hemodynamic responses, underlie dyspnea, however, the time-scale of these activations is not well understood. The recent findings of oscillatory neural activity coupled with the respiratory rhythm could provide the solution to this problem, however, more research with a focus on dyspnea is needed. We also touch on the findings of distinct spectral patterns underlying the changes in breathing due to experimental manipulations, meditation and disease. Subsequently, we suggest general research directions and specific research designs to supplement the current knowledge using neural oscillation techniques. We argue for the benefits of interdisciplinary collaboration and the converging of neuroimaging and behavioral methods to best explain the emergence of the subjective and aversive individual experience of dyspnea.

Electroencephalography During Nociceptive Stimulation in Chronic Pain Patients: A Systematic Review

BACKGROUND

With its high temporal resolution, electroencephalography (EEG), a technique that records electrical activity of cortical neuronal cells, is a potentially suitable technique to investigate human somatosensory processing. By using EEG, the processing of (nociceptive) stimuli can be investigated, along with the functionality of the nociceptive pathway. Therefore, it can be applied in chronic pain patients to objectify whether changes have occurred in nociceptive processing. Typically, so-called event-related potential (ERP) recordings are used, where EEG signals are recorded in response to specific stimuli and characterized by latency and amplitude.

OBJECTIVE

To summarize whether differences in somatosensory processing occur between chronic pain patients and healthy controls, measured with ERPs, and determine whether this response is related to the subjective pain intensity.

DESIGN

Systematic review.

SETTING AND METHODS

PubMed, Web of Science, and Embase were consulted, and 18 case-control studies were finally included.

SUBJECTS

The chronic pain patients suffered from tension-type headache, back pain, migraine, fibromyalgia, carpal tunnel syndrome, prostatitis, or complex regional pain syndrome.

RESULTS

Chronic neuropathic pain patients showed increased latencies of the N2 and P2 components, along with a decreased amplitude of the N2-P2 complex, which was also obtained in FM patients with small fiber dysfunction. The latter also showed a decreased amplitude of the N2-P3 and N1-P1 complex. For the other chronic pain patients, the latencies and the amplitudes of the ERP components did not seem to differ from healthy controls. One paper indicated that the N2-P3 peak-to-peak amplitude correlates with the subjective experience of the stimulus.

CONCLUSIONS

Differences in ERPs with healthy controls can mostly be found in chronic pain populations that suffer from neuropathic pain or where fiber dysfunction is present. In chronic pain populations with other etiological mechanisms, limited differences were found or agreed upon across studies.

Supraspinal Effects of Dorsal Root Ganglion Stimulation in Chronic Pain Patients

OBJECTIVES

Dorsal root ganglion stimulation (DRGS) has become a popular neuromodulatory treatment for neuropathic pain. We used magnetoencephalography (MEG) to investigate potential biomarkers of pain and pain relief, based on the differences in power spectral density (PSD) during varying degrees of pain and how these oscillations change during DRGS-mediated pain relief.

MATERIALS AND METHODS

Thirteen chronic pain patients with implanted dorsal root ganglion stimulators were included in the MEG analysis. MEG Recordings were performed at rest while the stimulator was turned ON or OFF. Numerical rating scale (NRS) scores were also recorded before and after DRGS was turned OFF and ON. Power spectral and source localization analyses were then performed on preprocessed MEG recordings.

RESULTS

With DRGS-OFF, patients in severe pain had significantly increased cortical theta (4-7 Hz) power and decreased cortical alpha (7-13 Hz) power compared to patients reporting less pain. This shift in power toward lower frequencies was contrasted by a shift toward the higher frequency power spectrum (low beta 13-20 Hz activity) during DRGS-mediated pain relief. A significant correlation was found between the increase in low beta activity and the degree of reported pain relief.

CONCLUSION

Our results demonstrate increased low-frequency power spectral activity in chronic pain patients in the absence of stimulation which shifts toward higher frequency power spectrum activity in response to therapeutic DRGS. These cortical changes in response to DRGS provide support for the use of neuroimaging in the search for potential biomarkers of pain.

Temporal structure of brain oscillations predicts learned nocebo responses to pain

This study aimed to identify electrophysiological correlates of nocebo-augmented pain. Nocebo hyperalgesia (i.e., increases in perceived pain resulting from negative expectations) has been found to impact how healthy and patient populations experience pain and is a phenomenon that could be better understood in terms of its neurophysiological underpinnings. In this study, nocebo hyperalgesia was induced in 36 healthy participants through classical conditioning and negative suggestions. Electroencephalography was recorded during rest (pre- and post-acquisition) and during pain stimulation (baseline, acquisition, evocation) First, participants received baseline high thermal pain stimulations. During nocebo acquisition, participants learned to associate an inert gel applied to their forearm with administered high pain stimuli, relative to moderate intensity control stimuli administered without gel. During evocation, all stimuli were accompanied by moderate pain, to measure nocebo responses to the inert gel. Pre- to post-acquisition beta-band alterations in long-range temporal correlations (LRTC) were negatively associated with nocebo magnitudes. Individuals with strong resting LRTC showed larger nocebo responses than those with weaker LRTC. Nocebo acquisition trials showed reduced alpha power. Alpha power was higher while LRTC were lower during nocebo-augmented pain, compared to baseline. These findings support nocebo learning theories and highlight a role of nocebo-induced cognitive processing.

Elevated and Slowed EEG Oscillations in Patients with Post-Concussive Syndrome and Chronic Pain Following a Motor Vehicle Collision

(1) Background: Mild traumatic brain injury produces significant changes in neurotransmission including brain oscillations. We investigated potential quantitative electroencephalography biomarkers in 57 patients with post-concussive syndrome and chronic pain following motor vehicle collision, and 54 healthy nearly age- and sex-matched controls. (2) Methods: Electroencephalography processing was completed in MATLAB, statistical modeling in SPSS, and machine learning modeling in Rapid Miner. Group differences were calculated using current-source density estimation, yielding whole-brain topographical distributions of absolute power, relative power and phase-locking functional connectivity. Groups were compared using independent sample Mann–Whitney U tests. Effect sizes and Pearson correlations were also computed. Machine learning analysis leveraged a post hoc supervised learning support vector non-probabilistic binary linear kernel classification to generate predictive models from the derived EEG signatures. (3) Results: Patients displayed significantly elevated and slowed power compared to controls: delta (p = 0.000000, r = 0.6) and theta power (p < 0.0001, r = 0.4), and relative delta power (p < 0.00001) and decreased relative alpha power (p < 0.001). Absolute delta and theta power together yielded the strongest machine learning classification accuracy (87.6%). Changes in absolute power were moderately correlated with duration and persistence of symptoms in the slow wave frequency spectrum (<15 Hz). (4) Conclusions: Distributed increases in slow wave oscillatory power are concurrent with post-concussive syndrome and chronic pain.

Peripheral Electrical Stimulation Modulates Cortical Beta-Band Activity

Low-frequency peripheral electrical stimulation using a matrix electrode (PEMS) modulates spinal nociceptive pathways. However, the effects of this intervention on cortical oscillatory activity have not been assessed yet. The aim of this study was to investigate the effects of low-frequency PEMS (4 Hz) on cortical oscillatory activity in different brain states in healthy pain-free participants. In experiment 1, PEMS was compared to sham stimulation. In experiment 2, motor imagery (MI) was used to modulate the sensorimotor brain state. PEMS was applied either during MI-induced oscillatory desynchronization (concurrent PEMS) or after MI (delayed PEMS) in a cross-over design. For both experiments, PEMS was applied on the left forearm and resting-state electroencephalography (EEG) was recording before and after each stimulation condition. Experiment 1 showed a significant decrease of global resting-state beta power after PEMS compared to sham (p = 0.016), with a median change from baseline of −16% for PEMS and −0.54% for sham. A cluster-based permutation test showed a significant difference in resting-state beta power comparing pre- and post-PEMS (p = 0.018) that was most pronounced over bilateral central and left frontal sensors. Experiment 2 did not identify a significant difference in the change from baseline of global EEG power for concurrent PEMS compared to delayed PEMS. Two cluster-based permutation tests suggested that frontal beta power may be increased following both concurrent and delayed PEMS. This study provides novel evidence for supraspinal effects of low-frequency PEMS and an initial indication that the presence of a cognitive task such as MI may influence the effects of PEMS on beta activity. Chronic pain has been associated with changes in beta activity, in particular an increase of beta power in frontal regions. Thus, brain state-dependent PEMS may offer a novel approach to the treatment of chronic pain. However, further studies are warranted to investigate optimal stimulation conditions to achieve a reduction of pain.

How Negative Experience Influences the Brain: A Comprehensive Review of the Neurobiological Underpinnings of Nocebo Hyperalgesia

This comprehensive review summarizes and interprets the neurobiological correlates of nocebo hyperalgesia in healthy humans. Nocebo hyperalgesia refers to increased pain sensitivity resulting from negative experiences and is thought to be an important variable influencing the experience of pain in healthy and patient populations. The young nocebo field has employed various methods to unravel the complex neurobiology of this phenomenon and has yielded diverse results. To comprehend and utilize current knowledge, an up-to-date, complete review of this literature is necessary. PubMed and PsychInfo databases were searched to identify studies examining nocebo hyperalgesia while utilizing neurobiological measures. The final selection included 22 articles. Electrophysiological findings pointed toward the involvement of cognitive-affective processes, e.g., modulation of alpha and gamma oscillatory activity and P2 component. Findings were not consistent on whether anxiety-related biochemicals such as cortisol plays a role in nocebo hyperalgesia but showed an involvement of the cyclooxygenase-prostaglandin pathway, endogenous opioids, and dopamine. Structural and functional neuroimaging findings demonstrated that nocebo hyperalgesia amplified pain signals in the spinal cord and brain regions involved in sensory and cognitive-affective processing including the prefrontal cortex, insula, amygdala, and hippocampus. These findings are an important step toward identifying the neurobiological mechanisms through which nocebo effects may exacerbate pain. Results from the studies reviewed are discussed in relation to cognitive-affective and physiological processes involved in nocebo and pain. One major limitation arising from this review is the inconsistency in methods and results in the nocebo field. Yet, while current findings are diverse and lack replication, methodological differences are able to inform our understanding of the results. We provide insights into the complexities and involvement of neurobiological processes in nocebo hyperalgesia and call for more consistency and replication studies. By summarizing and interpreting the challenging and complex neurobiological nocebo studies this review contributes, not only to our understanding of the mechanisms through which nocebo effects exacerbate pain, but also to our understanding of current shortcomings in this field of neurobiological research.

Neuronal Effects of Listening to Entrainment Music Versus Preferred Music in Patients With Chronic Cancer Pain as Measured via EEG and LORETA Imaging

Previous studies examining EEG and LORETA in patients with chronic pain discovered an overactivation of high theta (6–9 Hz) and low beta (12–16 Hz) power in central regions. MEG studies with healthy subjects correlating evoked nociception ratings and source localization described delta and gamma changes according to two music interventions. Using similar music conditions with chronic pain patients, we examined EEG in response to two different music interventions for pain. To study this process in-depth we conducted a mixed-methods case study approach, based on three clinical cases. Effectiveness of personalized music therapy improvisations (entrainment music – EM) versus preferred music on chronic pain was examined with 16 participants. Three patients were randomly selected for follow-up EEG sessions three months post-intervention, where they listened to recordings of the music from the interventions provided during the research. To test the difference of EM versus preferred music, recordings were presented in a block design: silence, their own composed EM (depicting both “pain” and “healing”), preferred (commercially available) music, and a non-participant’s EM as a control. Participants rated their pain before and after the EEG on a 1–10 scale. We conducted a detailed single case analysis to compare all conditions, as well as a group comparison of entrainment-healing condition versus preferred music condition. Power spectrum and according LORETA distributions focused on expected changes in delta, theta, beta, and gamma frequencies, particularly in sensory-motor and central regions. Intentional moment-by-moment attention on the sounds/music rather than on pain and decreased awareness of pain was experienced from one participant. Corresponding EEG analysis showed accompanying power changes in sensory-motor regions and LORETA projection pointed to insula-related changes during entrainment-pain music. LORETA also indicated involvement of visual-spatial, motor, and language/music improvisation processing in response to his personalized EM which may reflect active recollection of creating the EM. Group-wide analysis showed common brain responses to personalized entrainment-healing music in theta and low beta range in right pre- and post-central gyrus. We observed somatosensory changes consistent with processing pain during entrainment-healing music that were not seen during preferred music. These results may depict top–down neural processes associated with active coping for pain.

Beta Electroencephalographic Oscillation Is a Potential GABAergic Biomarker of Chronic Peripheral Neuropathic Pain

This preliminary investigation aimed to assess beta (β) oscillation, a marker of the brain GABAergic signaling, as a potential objective pain marker, hence contributing at the same time to the mechanistic approach of pain management. This case–control observational study measured β electroencephalographic (EEG) oscillation in 12 right-handed adult male with chronic neuropathic pain and 10 matched controls (∼55 years). Participants were submitted to clinical evaluation (pain visual analog scale, Hospital Anxiety, and Depression scale) and a 24-min high-density EEG recording (BIOSEMI). Data were analyzed using the EEGlab toolbox (MATLAB), SPSS, and R. The global power spectrum computed within the low (Lβ, 13–20 Hz) and the high (Hβ, 20–30 Hz) β frequency sub-bands was significantly lower in patients than in controls, and accordingly, Lβ was negatively correlated to the pain visual analog scale (R = −0.931, p = 0.007), whereas Hβ correlation was at the edge of significance (R = −0.805; p = 0.053). Patients’ anxiety was correlated to pain intensity (R = 0.755; p = 0.003). Normalization of the low and high β global power spectrum (GPS) to the GPS of the full frequency range, while confirming the significant Lβ power decrease in chronic neuropathic pain patients, vanished the significance of the Hβ decrease, as well as the correlation between Lβ power and pain intensity. Our results suggest that the GABAergic Lβ EEG oscillation is affected by chronic neuropathic pain. Confirming the Lβ GPS decrease and the correlation with pain intensity in larger studies would open new opportunities for the clinical application of gamma-aminobutyric acid-modifying therapies.

Objective characterization of hip pain levels during walking by combining quantitative electroencephalography with machine learning

Pain is an undesirable sensory experience that can induce depression and limit individuals' activities of daily living, in turn negatively impacting the labor force. Affected people frequently feel pain during activity; however, pain is subjective and difficult to judge objectively, particularly during activity. Here, we developed a system to objectively judge pain levels in walking subjects by recording their quantitative electroencephalography (qEEG) and analyzing data by machine learning. To do so, we enrolled 23 patients who had undergone total hip replacement for pain, and recorded their qEEG during a five-minute walk via a wearable device with a single electrode placed over the Fp1 region, based on the 10-20 Electrode Placement System, before and three months after surgery. We also assessed subject hip pain using a numerical rating scale. Brain wave amplitude differed significantly among subjects with different levels of hip pain at frequencies ranging from 1 to 35 Hz. qEEG data were also analyzed by a support vector machine using the Radial Basis Functional Kernel, a function used in machine learning. That approach showed that an individual's hip pain during walking can be recognized and subdivided into pain quartiles with 79.6% recognition Accuracy. Overall, we have devised an objective and non-invasive tool to monitor an individual's pain during walking.

Portable EEG monitoring for older adults with dementia and chronic pain - A feasibility study

Given the reduced ability of people with dementia to self-report pain, this study examined the feasibility of using a portable electroencephalography (EEG) headband (MUSE 2) as a pain measurement tool for long-term care residents with dementia. Ten minutes of resting-state EEG was acquired by MUSE 2 from people with dementia experiencing ongoing pain (n = 3) and without current pain (n = 1) over three days. The MUSE 2 was acceptable and feasible for use in people with dementia while challenges regarding software, data collection and analysis in using this device are reported. Compared to the resident not experiencing pain, EEG signals of residents with ongoing pain showed different EEG patterns, and this could be a potential biomarker to support pain measurement in people with dementia. Further research with larger sample size is warranted to verify study results.

Chronic jaw pain attenuates neural oscillations during motor-evoked pain

Motor- and pain-related processes separately induce a reduction in alpha and beta power. When movement and pain occur simultaneously but are independent of each other, the effects on alpha and beta power are additive. It is not clear whether this additive effect is evident during motor-evoked pain in individuals with chronic pain. We combined highdensity electroencephalography (EEG) with a paradigm in which motor-evoked pain was induced during a jaw force task. Participants with chronic jaw pain and pain-free controls produced jaw force at 2% and 15% of their maximum voluntary contraction. The chronic jaw pain group showed exacerbated motor-evoked pain as force amplitude increased and showed increased motor variability and motor error irrespective of force amplitude. The chronic jaw pain group had an attenuated decrease in power in alpha and lower-beta frequencies in the occipital cortex during the anticipation and experience of motor-evoked pain. Rather than being additive, motor-evoked pain attenuated the modulation of alpha and beta power, and this was most evident in occipital cortex. Our findings provide the first evidence of changes in neural oscillations in the cortex during motor-evoked jaw pain.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

Hyperalgesia and Central Sensitization in Subjects With Chronic Orofacial Pain: Analysis of Pain Thresholds and EEG Biomarkers

Introduction: The presence of a temporomandibular disorder is one of the most frequent causes of orofacial pain (OFP). When pain continues beyond tissue healing time, it becomes chronic and may be caused, among other factors, by the sensitization of higher-order neurons. The aim of this study is to describe psychological characteristics of patients with chronic OFP, their peripheral pain threshold, and electroencephalography (EEG) recording, looking for possible signs of central sensitization (CS). Materials and methods: Twenty-four subjects with chronic OFP caused by temporomandibular disorder were evaluated using the Research Diagnostic Criteria for Temporomandibular Disorders Axis I and Axis II. Pain intensity, catastrophizing, and presence of CS were assessed through self-reported questionnaires. Pressure pain threshold (PPT) was recorded in facial and peripheral sites; EEG activity was recorded during open and closed eyes resting state and also during the pain threshold assessment. Pain thresholds and EEG recordings were compared with a cohort of pain-free age- and sex-matched healthy subjects. Results: Patients with chronic OFP showed a significant reduction in their pain threshold compared to healthy subjects in all sites assessed. Greater reduction in pain threshold was recorded in patients with more severe psychological symptoms. Decreased alpha and increased gamma activity was recorded in central and frontal regions of all subjects, although no significant differences were observed between groups. Discussion: A general reduction in PPT was recorded in people who suffer from chronic OFP. This result may be explained by sensitization of the central nervous system due to chronic pain conditions. Abnormal EEG activity was recorded during painful stimulation compared to the relaxed condition in both chronic OFP subjects and healthy controls.

NIRS measures in pain and analgesia: Fundamentals, features, and function

Current pain assessment techniques based only on clinical evaluation and self-reports are not objective and may lead to inadequate treatment. Having a functional biomarker will add to the clinical fidelity, diagnosis, and perhaps improve treatment efficacy in patients. While many approaches have been deployed in pain biomarker discovery, functional near-infrared spectroscopy (fNIRS) is a technology that allows for non-invasive measurement of cortical hemodynamics. The utility of fNIRS is especially attractive given its ability to detect specific changes in the somatosensory and high-order cortices as well as its ability to measure (1) brain function similar to functional magnetic resonance imaging, (2) graded responses to noxious and innocuous stimuli, (3) analgesia, and (4) nociception under anesthesia. In this review, we evaluate the utility of fNIRS in nociception/pain with particular focus on its sensitivity and specificity, methodological advantages and limitations, and the current and potential applications in various pain conditions. Everything considered, fNIRS technology could enhance our ability to evaluate evoked and persistent pain across different age groups and clinical populations.

Comparison of two tDCS protocols on pain and EEG alpha-2 oscillations in women with fibromyalgia

Transcranial Direct Current Stimulation (tDCS) has been used as an alternative treatment for pain reduction in fibromyalgia. In this study, in addition to behavioral measures, we analyzed oscillations in alpha 2 frequency band in the frontal, occipital, and parietal regions, in response to the application of two neuromodulation protocols in fibromyalgia. The study was a randomized, double-blind, placebo-controlled clinical trial with 31 women diagnosed with fibromyalgia. The participants were allocated to three groups with the anodic stimulation applied on the left motor cortex: Group 1, for five consecutive days; Group 2, for 10 consecutive days; and Group 3, sham stimulation for five consecutive days. Statistical analysis showed a reduction in pain intensity after treatment for groups in general [F (1.28) = 8.02; p = 0.008; η2 = 0.223], in addition to a reduction in alpha 2 in the frontal (p = 0.039; d = 0.384) and parietal (p = 0.021; d = 0.520) regions after the treatment on five consecutive days. We conclude that neuromodulation protocols produced similar effects on pain reduction, but differed with respect to the changes in the alpha 2 frequency band in the frontal and parietal regions.

Re-test reliability and internal consistency of EEG alpha-band oscillations in older adults with chronic knee pain

OBJECTIVE

Chronic pain studies investigating the ability to detect sensory processing differences related to thalamic gating using electroencephalographic (EEG) alpha have yielded conflicting results. Alpha's basic psychometric properties in pain populations requires further study. The present study reports on the test-retest reliability and internal consistency of EEG alpha power in older adults with chronic knee pain.

METHODS

Repeated EEG alpha power measurements were taken of older adults (N = 31) with chronic knee pain across two sessions separated by a ten-day period associated with a pilot clinical trial study. Recordings included resting periods (eyes open and eyes closed) as well as periods involving a pain management activity.

RESULTS

Most single alpha-power measures and all within-participant averages of alpha obtained within a session showed high internal consistency (Cronbach's α > 0.7) and satisfactory-to-excellent re-test reliability (Pearson's rs > 0.6) of both alpha power and alpha blocking (eyes closed minus eyes open) across repeated conditions.

CONCLUSIONS

EEG alpha power seems mostly reliable and consistent, particularly when participants' eyes are closed, after a period of habituation, and when alpha measures are averaged as within-participant estimates.

SIGNIFICANCE

This analysis suggests that within-subject averages of EEG alpha are the most reliable for developing indices of chronic knee pain.

Individual variation in alpha neurofeedback training efficacy predicts pain modulation

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Sensorimotor alpha neurofeedback training effect on pain perception was assessed.

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Neurofeedback training decreased the sensory-discriminative aspect of pain.

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Neurofeedback training increased the affective-motivational aspect of pain.

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Pain modulation by neurofeedback training was dependent upon the training efficacy.

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Neurofeedback training efficacy predicted sensory-discriminative pain modulation.

Studies have shown an association between sensorimotor α-oscillation and pain perception. It suggests the potential use of neurofeedback (NFB) training for pain modulation through modifying sensorimotor α-oscillation. Here, a single-session NFB training protocol targeted on increasing sensorimotor α-oscillations was applied to forty-five healthy participants. Pain thresholds to nociceptive laser stimulations and pain ratings (intensity and unpleasantness) to identical laser painful stimulations were assessed immediately before and after NFB training. Participants had larger pain thresholds, but rated the identical painful laser stimulation as more unpleasant after NFB training. These pain measurements were further compared between participants with high or low NFB training efficacy that was quantified as the regression slope of α-oscillation throughout the ten training blocks. A significant increase in pain thresholds was observed among participants with high-efficacy; whereas a significant increase in pain ratings was observed among participants with low-efficacy. These results suggested that NFB training decreased the sensory-discriminative aspect of pain, but increased the affective-motivational aspect of pain, whereas both pain modulations were dependent upon the NFB training efficacy. Importantly, correlation analysis across all participants revealed that a greater NFB training efficacy predicted a greater increase in pain thresholds particularly at hand contralateral to NFB target site, but no significant correlation was observed between NFB training efficacy and modulation on pain ratings. It thus provided causal evidence for a link between sensorimotor α-oscillation and the sensory-discriminative aspect of pain, and highlighted the need for personalized neurofeedback for the benefits on pain modulation at the individual level. Future studies can adopt a double-blind sham-controlled protocol to validate NFB training induced pain modulation.

Pain phenotypes classified by machine learning using electroencephalography features

Pain is a multidimensional experience mediated by distributed neural networks in the brain. To study this phenomenon, EEGs were collected from 20 subjects with chronic lumbar radiculopathy, 20 age and gender matched healthy subjects, and 17 subjects with chronic lumbar pain scheduled to receive an implanted spinal cord stimulator. Analysis of power spectral density, coherence, and phase-amplitude coupling using conventional statistics showed that there were no significant differences between the radiculopathy and control groups after correcting for multiple comparisons. However, analysis of transient spectral events showed that there were differences between these two groups in terms of the number, power, and frequency-span of events in a low gamma band. Finally, we trained a binary support vector machine to classify radiculopathy versus healthy subjects, as well as a 3-way classifier for subjects in the 3 groups. Both classifiers performed significantly better than chance, indicating that EEG features contain relevant information pertaining to sensory states, and may be used to help distinguish between pain states when other clinical signs are inconclusive.

Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography

Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically exploited the potential of electroencephalography to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity, and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4-8 Hz) and gamma (>60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results suggest that increased theta and gamma synchrony in frontal brain areas are involved in the pathophysiology of chronic pain. Although substantial challenges concerning the reproducibility of the findings and the accuracy, specificity, and validity of potential electroencephalography-based disease markers remain to be overcome, our study indicates that abnormal frontal synchrony at theta and gamma frequencies might be promising targets for noninvasive brain stimulation and/or neurofeedback approaches.

Electrophysiological correlates of focused attention on low- and high-distressed tinnitus

OBJECTIVES

The study aimed at determining the EEG correlates of concentration on either low or high-distressed tinnitus.

METHODS

Sixty-seven patients (36 women, mean age = 50.34 ± 12.94 years) with chronic tinnitus were assigned to either a high (HD) or low (LD) tinnitus-related distress group based on THI results. All participants took part in the EEG study comprising two 3-4 min blocks of focusing on either tinnitus (Tinnitus Focus Condition, TFC) or the sensations from one's own body (Body Focus Condition, BFC). The absolute power and current density of 8 frequency bands in 7 clusters were compared between conditions and groups.

RESULTS

The most pronounced differences were found in the HD patients in the TFC, relative to the BFC, i.e. reduced power of frontally distributed low alpha (8-10 Hz) and posterior high alpha (10-12 Hz) as well as lower current density of 8-10 Hz rhythm over the right frontal/anterior cingulate cortex and higher middle beta (15-18 Hz) density in the precuneus. The HD, relative to LD patients, in both conditions, exhibited increased low beta (12-15 Hz) power over the left middle area and greater higher beta (15-25 Hz) power in the left posterior region.

CONCLUSIONS

The present study contrasted bioelectrical activity, acquired when concentrating on tinnitus with EEG data collected whilst patients focused on their body. Decreased alpha power and current density in the frontal/cingulate cortex when listening to bothersome tinnitus might reflect greater cortical arousal whereas increased beta power and density in the precuneus/posterior cingulate activity in this condition could be indicative for elevated tension or augmented cognitive/emotional processing of tinnitus sound. Enhanced beta rhythm in patients with high versus low tinnitus distress, observed independently of the study condition, may be due to greater self-focused attention or more active processing of sensations derived from the own body.

Neurofeedback for Pain Management: A Systematic Review

Background: Chronic pain is a significant global health issue. For most individuals with chronic pain, biomedical treatments do not provide adequate relief. Given the evidence that neurophysiological abnormalities are associated with pain, it is reasonable to consider treatments that target these factors, such as neurofeedback (NF). The primary objectives of this review were to summarize the current state of knowledge regarding: (1) the different types of NF and NF protocols that have been evaluated for pain management; (2) the evidence supporting each NF type and protocol; (3) if targeted brain activity changes occur with NF training; and (4) if such brain activity change is associated with improvements on treatment outcomes. Methods: Inclusion criteria were intentionally broad to encompass every empirical study using NF in relation to pain. We considered all kinds of NF, including both electroencephalogram- (EEG-) and functional magnetic resonance imagining- (fMRI-) based. We searched the following databases from inception through September 2019: Pubmed, Ovid, Embase, Web of Science, PsycINFO. The search strategy consisted of a combination of key terms referring to all NF types and pain conditions (e.g., neurofeedback, rt-fMRI-NF, BOLD, pain, migraine). Results: A total of 6,552 citations were retrieved; 24 of these that were included in the review. Most of the studies were of moderate quality, included a control condition and but did not include a follow-up. They focused on studying pain intensity (83%), pain frequency, and other variables (fatigue, sleep, depression) in samples of adults (n = 7-71) with headaches, fibromyalgia and other pain conditions. Most studies (79%) used EEG-based NF. A wide variety of NF types and protocols have been used for pain management aiming to either increase, decrease or regulate brain activity in certain areas theoretically associated with pain. Conclusions: Given the generally positive results in the studies reviewed, the findings indicate that NF procedures have the potential for reducing pain and improving other related outcomes in individuals with chronic pain. However, the current evidence does not provide definitive conclusions or allow for reliable recommendations on which protocols or methods of administration may be the most effective. These findings support the need for continued - but higher quality - research in this area.

Decreased neural inhibitory state in fibromyalgia pain: A cross-sectional study

OBJECTIVES

Chronic pain is one of the most common and challenging symptoms in fibromyalgia (FM). Currently, self-reported pain is the main criterion used by clinicians assessing patients with pain. However, it is subjective, and multiple factors can affect pain levels. In this study, we investigated the neural correlates of FM pain using conditioned pain modulation (CPM), electroencephalography (EEG), and transcranial magnetic stimulation (TMS).

METHODS

In this cross-sectional neurophysiological analysis of a randomized, double-blind controlled trial, 36 patients with fibromyalgia were included. We analyzed CPM, EEG variables and TMS measures and their correlation with pain levels as measured by a visual analog scale. Univariate and multivariate linear regression analyses were performed to identify the predictors of pain severity.

RESULTS

We found: (1) no association between pain levels and CPM; (2) an association between reduced alpha and beta power over the central region in resting-EEG and higher pain levels; (3) an association between smaller event-related desynchronization (ERD) responses in theta and delta bands over the central region and higher pain levels; (4) an association between smaller ERD responses in theta and delta bands and smaller intracortical inhibition and higher intracortical facilitation ratios; (5) an association between smaller ERD responses in delta band and reduced CPM.

CONCLUSIONS

Our results do not support CPM as a biomarker for pain intensity in FM. However, our specific EEG findings showing the relationship between pain, CPM and TMS measures suggest that FM leads to a disruption of inhibitory neural modulators and thus support CPM as a likely predictive marker of disrupted pain modulation system. These neurophysiological markers need to be further explored in potential future trials as to find novel targets for the treatment of FM.

Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

Reduced pain and analgesic use after acoustic binaural beats therapy in chronic pain - A double-blind randomized control cross-over trial

BACKGROUND

Binaural Beats (BB) consist of two artificial acoustic stimuli with different frequency, presented simultaneously but independently to each ear. The human brain perceives and synchronizes to this frequency difference (entrainment). Aim of this study was to test the hypothesis that brain entrainment to a lower function rhythm, with BB application, can decrease pain perception and analgesic medication use, in chronic pain patients.

METHODS

In a double blind, randomized, cross-over trial, BB at 5Hz (theta rhythm) were applied for 30 minutes, under simultaneous electroencephalogram recordings, followed by liberal, on demand use by chronic pain patients for a week, compared to sham stimulation (SS). Pain as the main outcome (numeric scale, NRS), stress (STAI) and medication usage (defined daily doses, DDD) were assessed at baseline, 30 minutes and week's end.

RESULTS

Perceived pain (NRS) was significantly reduced in BB intervention (5.6±2.3 to 3.4±2.6, p<0.001), compared to SS (5.2±2.1 to 4.8±2.3, p=0.78), during the first 30-minute phase, as well as at the week's end (to 3.9±2.5 compared to 5.5±2.6 respectively, p<0.001). The mean EEG theta power at 5Hz was significantly increased only during BB application. Stress was significantly reduced at 30 minutes in both interventions but remained reduced only in the BB group at the week's end. Analgesic medication consumption (DDD, g) during the week was significantly less in the BB intervention (3.9±3.7 vs. 4.6±4.1, p<0.05), while reporting equal to SS mean levels of pain.

CONCLUSIONS

Acoustic BB reduced pain intensity, stress and analgesic use, compared to SS, in chronic pain patients.

SIGNIFICANCE

This study provides evidence that theta rhythm binaural beats can alleviate pain intensity, both after a brief 30 minute and a longer one week on-demand intervention. The subsequent significant reduction in analgesic medication consumption in chronic pain patients' daily living could offer a valuable tool, augmenting the effect of existing pain therapies.

The Cerebral Localization of Pain: Anatomical and Functional Considerations for Targeted Electrical Therapies

Millions of people in the United States are affected by chronic pain, and the financial cost of pain treatment is weighing on the healthcare system. In some cases, current pharmacological treatments may do more harm than good, as with the United States opioid crisis. Direct electrical stimulation of the brain is one potential non-pharmacological treatment with a long history of investigation. Yet brain stimulation has been far less successful than peripheral or spinal cord stimulation, perhaps because of our limited understanding of the neural circuits involved in pain perception. In this paper, we review the history of using electrical stimulation of the brain to treat pain, as well as contemporary studies identifying the structures involved in pain networks, such as the thalamus, insula, and anterior cingulate. We propose that the thermal grill illusion, an experimental pain model, can facilitate further investigation of these structures. Pairing this model with intracranial recording will provide insight toward disentangling the neural correlates from the described anatomic areas. Finally, the possibility of altering pain perception with brain stimulation in these regions could be highly informative for the development of novel brain stimulation therapies for chronic pain.

Differences in EEG patterns between tonic and high frequency spinal cord stimulation in chronic pain patients

OBJECTIVE

To investigate the differences in neural patterns between spinal cord stimulation (SCS) waveforms (60-Hz tonic vs 10-KHz high frequency stimulation, HFS) and their correlation to stimulation-induced pain relief.

METHODS

We recorded 10-channel electroencephalogram (EEG) in response to stimulation ON and OFF in 9 chronic pain patients (4 women, 5 men) during SCS surgery and examined the intraoperative spatio-spectral EEG features.

RESULTS

We discovered stronger relative alpha power in the somatosensory region and higher trend in alpha/theta peak power ratio in frontal cortex with HFS. We also observed a shift in peak frequency from theta to alpha rhythms in HFS as compared to baseline and tonic stimulation, where slower theta activity was maintained. Further, a positive correlation was found between changes in Oswestry disability index (ODI) scores (from preoperative to postoperative) and HFS-induced alpha/theta peak power ratio in frontal and somatosensory regions.

CONCLUSIONS

Altogether, our findings suggest that dynamic spectral interactions in theta-alpha band and their spatial distributions might be the first intraoperative neural signatures of pain relief induced by HFS in chronic pain.

SIGNIFICANCE

Examining electrophysiological changes intraoperatively has a potential to elucidate response to SCS therapy prior to device selection, reducing the healthcare expenditures associated with failed implants.

Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component

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High theta and low gamma activity in the dynamic pain connectome is linked to chronic pain.

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High alpha-band activity is present when neuropathic pain is likely.

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Spectral frequency band strength distinguish neuropathic from non-neuropathic pain.

We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.

Granger causality analysis of rat cortical functional connectivity in pain

OBJECTIVE

The primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) are two of the most important cortical brain regions encoding the sensory-discriminative and affective-emotional aspects of pain, respectively. However, the functional connectivity of these two areas during pain processing remains unclear. Developing methods to dissect the functional connectivity and directed information flow between cortical pain circuits can reveal insight into neural mechanisms of pain perception.

APPROACH

We recorded multichannel local field potentials (LFPs) from the S1 and ACC in freely behaving rats under various conditions of pain stimulus (thermal versus mechanical) and pain state (naive versus chronic pain). We applied Granger causality (GC) analysis to the LFP recordings and inferred frequency-dependent GC statistics between the S1 and ACC.

MAIN RESULTS

We found an increased information flow during noxious pain stimulus presentation in both S1[Formula: see text]ACC and ACC[Formula: see text]S1 directions, especially at theta and gamma frequency bands. Similar results were found for thermal and mechanical pain stimuli. The chronic pain state shares common observations, except for further elevated GC measures especially in the gamma band. Furthermore, time-varying GC analysis revealed a negative correlation between the direction-specific and frequency-dependent GC and animal's paw withdrawal latency. In addition, we used computer simulations to investigate the impact of model mismatch, noise, missing variables, and common input on the conditional GC estimate. We also compared the GC results with the transfer entropy (TE) estimates.

SIGNIFICANCE

Our results reveal functional connectivity and directed information flow between the S1 and ACC during various pain conditions. The dynamic GC analysis support the hypothesis of cortico-cortical information loop in pain perception, consistent with the computational predictive coding paradigm.

The association between visual impairment and fatigue: a systematic review and meta-analysis of observational studies

PURPOSE

The aim was to compare fatigue levels between patients with visual impairment and controls with normal sight and to examine the association between fatigue and vision loss severity.

METHODS

A systematic literature search was performed using databases of PubMed, Embase, PsycINFO and Cochrane to identify observational studies with outcomes related to fatigue (e.g. vitality subscale of the Short-Form 36, Fatigue Assessment Scale). A meta-analysis was performed using standardised mean differences (SMDs) and odds ratios (OR) to quantitatively summarise the association between visual impairment and fatigue. Sources of heterogeneity were explored by subgroup and sensitivity analyses. Study quality was assessed with the Newcastle-Ottawa scale.

RESULTS

After reviewing 4477 studies, 22 studies with a total of 40 004 participants were included, of which 18 contributed to meta-analysis. Among these, eight were assessed as moderate quality studies and 10 as high quality studies. Pooled analysis involving 2500 patients and 8395 controls showed higher fatigue severity levels (S.M.D. = -0.36, 95% CI -0.50 to -0.22, 14 studies) among visually impaired patients compared to normally sighted controls. This effect size was small and persisted in sensitivity analyses that involved study quality, fatigue assessment tools and visual acuity data. Furthermore, pooled analysis of four studies including 2615 patients and 5438 controls showed a significant association between visual impairment and fatigue (OR = 2.61, 95% CI 1.69 to 4.04). Secondary meta-analysis of four studies showed no significant difference in fatigue severity (S.M.D. = 0.01, 95% CI -0.37 to 0.39) between patients with moderate visual impairment and patients with severe visual impairment or blindness.

CONCLUSIONS

Current moderate to high quality evidence suggest that patients with visual impairment experience more severe fatigue symptoms than persons with normal sight. However, a limited number of available studies indicates that fatigue is not associated with severity of vision loss. Future studies are required to determine which factors and underlying mechanisms may explain the association between visual impairment and fatigue. Discussing fatigue at an early stage and developing intervention options for vision-related fatigue should be considered within the field of low vision rehabilitation.

Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions

Chronic pain is known as a complex disease due to its comorbidities with other symptoms and the lack of effective treatments. As a consequence, chronic pain seems to be under-diagnosed in more than 75% of patients. At the same time, the advance in brain imaging, the popularization of machine learning techniques and the development of new diagnostic tools based on these technologies have shown that these tools could be an option in supporting decision-making of healthcare professionals. In this study, we computed functional brain connectivity using resting-state fMRI data from one hundred and fifty participants to assess the performance of different machine learning models, including deep learning (DL) neural networks in classifying chronic pain patients and pain-free controls. The best result was obtained by training a convolutional neural network fed with data preprocessed using the MSDL probabilistic atlas and using the dynamic time warping (DTW) as connectivity measure. DL models had a better performance compared to other less costly models such as support vector machine (SVM) and RFC, with balanced accuracy ranged from 69 to 86%, while the area under the curve (ROC) ranged from 0.84 to 0.93. Also, DTW overperformed correlation as connectivity measure. These findings support the notion that resting-state fMRI data could be used as a potential biomarker of chronic pain conditions.

End points for sickle cell disease clinical trials: patient-reported outcomes, pain, and the brain

To address the global burden of sickle cell disease (SCD) and the need for novel therapies, the American Society of Hematology partnered with the US Food and Drug Administration to engage the work of 7 panels of clinicians, investigators, and patients to develop consensus recommendations for clinical trial end points. The panels conducted their work through literature reviews, assessment of available evidence, and expert judgment focusing on end points related to: patient-reported outcomes (PROs), pain (non-PROs), the brain, end-organ considerations, biomarkers, measurement of cure, and low-resource settings. This article presents the findings and recommendations of the PROs, pain, and brain panels, as well as relevant findings and recommendations from the biomarkers panel. The panels identify end points, where there were supporting data, to use in clinical trials of SCD. In addition, the panels discuss where further research is needed to support the development and validation of additional clinical trial end points.

Peripheral Nerve Ligation Elicits Widespread Alterations in Cortical Sensory Evoked and Spontaneous Activity

Peripheral neuropathies result in adaptation in primary sensory and other regions of cortex, and provide a framework for understanding the localized and widespread adaptations that arise from altered sensation. Mesoscale cortical imaging achieves high temporal resolution of activity using optical sensors of neuronal activity to simultaneously image across a wide expanse of cortex and capture this adaptation using sensory-evoked and spontaneous cortical activity. Saphenous nerve ligation in mouse is an animal model of peripheral neuropathy that produces hyperalgesia circumscribed to the hindlimb. We performed saphenous nerve ligation or sham, followed by mesoscale cortical imaging using voltage sensitive dye (VSD) after ten days. We utilized subcutaneous electrical stimulation at multiple stimulus intensities to characterize sensory responses after ligation or sham, and acquired spontaneous activity to characterize functional connectivity and large scale cortical network reorganization. Relative to sham animals, the primary sensory-evoked response to hindlimb stimulation in ligated animals was unaffected in magnitude at all stimulus intensities. However, we observed a diminished propagating wave of cortical activity at lower stimulus intensities in ligated animals after hindlimb, but not forelimb, sensory stimulation. We simultaneously observed a widespread decrease in cortical functional connectivity, where midline association regions appeared most affected. These results are consistent with localized and broad alterations in intracortical connections in response to a peripheral insult, with implications for novel circuit level understanding and intervention for peripheral neuropathies and other conditions affecting sensation.

Functional dynamics of thalamic local field potentials correlate with modulation of neuropathic pain

Understanding the functional dynamics of neural oscillations in the sensory thalamus is essential for elucidating the perception and modulation of neuropathic pain. Local field potentials were recorded from the sensory thalamus of twelve neuropathic pain patients. Single and combinational neural states were defined by the activity state of a single or paired oscillations. Relationships between the duration or occurrence rate of neural state and pre-operative pain level or pain relief induced by deep brain stimulation were evaluated. Results showed that the occurrence rate of the single neural state of low-beta oscillation was significantly correlated with pain relief. The duration and occurrence rate of combinational neural states of the paired low-beta with delta, theta, alpha, high-beta or low-gamma oscillations were more significantly correlated with pain relief than the single neural states. Moreover, these significant combinational neural states formed a local oscillatory network with low-beta oscillation as a key node. The results also showed correlations between measures of combinational neural states and subjective pain level as well. The duration of combinational neural states of paired alpha with delta or theta oscillations and the occurrence rate of neural states of the paired delta with low-beta or low-gamma oscillations were significantly correlated with pre-operative pain level. In conclusion, this study revealed that the integration of oscillations and the functional dynamics of neural states were differentially involved in modulation and perception of neuropathic pain. The functional dynamics could be biomarkers for developing neural state-dependent deep brain stimulation for neuropathic pain.