Longitudinal resting-state electroencephalography in patients with chronic pain undergoing interdisciplinary multimodal pain therapy

Multimodal hypersensitivity and somatic symptoms predict adolescent postmenarchal widespread pain

ABSTRACT

Widespread pain in adolescence is linked with poor mental health, pain, and somatic symptoms in childhood. This prospective study in 207 premenarchal adolescents used quantitative sensory testing (QST) and multimodal hypersensitivity (MMH) measures to assess somatosensory system function and identify predictors for widespread pain (≥3/7 sites). We hypothesized that premenarchal pain, somatic symptoms, psychological factors, and somatosensory system function would predict postmenarchal widespread pain, which would be associated with greater menstrual pain intensity. At premenarchal and postmenarchal study visits, participants completed measures of somatic symptoms, a pain body map, psychosocial questionnaires, QST, and experimental MMH measures including auditory, visual, and visceral stimulation. Electroencephalography (EEG) was collected during auditory and visual tasks to identify neural correlates of MMH. Premenarchal widespread pain was reported by 25% of participants, whereas 29% developed new incident widespread pain postmenarche. Adolescents with postmenarchal widespread pain reported greater menstrual pain intensity (median [interquartile range] 47 [28-61]; 0-100 visual analog scale) than those without (24 [8-50], P = 0.001). Elevated somatic symptoms (P = 0.012), stress (P = 0.015), and sensitivity to visceral (bladder filling) (P = 0.046) and unpleasant visual stimuli (P = 0.043) were significant predictors of postmenarche widespread pain. A multivariable regression model found premenarchal body map score (OR = 1.75, 95% CI [1.20, 2.55]), somatic symptoms (OR = 1.47, 95% CI [1.03, 2.11]), and visual hypersensitivity (OR = 1.62, 95% CI [1.12, 2.33]) predicted postmenarchal widespread pain. No EEG differences in early cortical sensory processing were found. Our results suggest that increased sensitivity to multimodal unpleasant and painful stimuli represents a novel risk factor for postmenarche widespread pain.

Pain and the Brain: A Systematic Review of Methods, EEG Biomarkers, Limitations, and Future Directions

Background: Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. Objectives: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain's electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. Methods: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle-Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. Results: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. Conclusions: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040).

Effects of centrally acting analgesics on resting-state electroencephalography biomarker candidates of chronic pain

Resting-state electroencephalography (rsEEG) holds promise as a biomarker of chronic pain. However, the impact of centrally acting analgesics like opioids, antiepileptics, and antidepressants on rsEEG remains unclear. This confounds and limits the interpretability of previous studies and questions the specificity of rsEEG biomarker candidates of chronic pain, especially for potential diagnostic biomarkers. We, therefore, aimed to elucidate the effects of opioids, antiepileptics, and antidepressants on common rsEEG biomarker candidates of chronic pain. To this end, we analyzed two large, independent rsEEG datasets, including 217 people with chronic pain. We performed preregistered multivariate Bayesian analyses to allow for the quantification and interpretation of evidence in favor of as well as against medication effects on EEG. We specifically evaluated the effects of different centrally acting analgesics on rsEEG features and controlled for the potential confounds of age, pain intensity, and depression. Results predominantly provided evidence against effects of centrally acting analgesics on peak alpha frequency, oscillatory power in different frequency bands, and connectivity-based network measures. Although these findings do not rule out any effects of analgesics on rsEEG, they argue against medium to large effects of centrally acting analgesics on rsEEG. These results help to interpret previous and future rsEEG findings in people with chronic pain and strengthen the validity of rsEEG biomarker candidates of chronic pain. Thus, the present findings can help to develop clinically valuable biomarkers of chronic pain. PERSPECTIVE: This study investigated the effects of centrally acting analgesics on brain-based biomarker candidates of chronic pain, as assessed by electroencephalography. The results predominantly provided evidence against effects on peak alpha frequency, oscillatory power, and connectivity-based network measures. This might help to develop clinically useful biomarkers of chronic pain. DATA AVAILABILITY: Datasets are available at https://osf.io/mj9xr/.

Assessing the balance between excitation and inhibition in chronic pain through the aperiodic component of EEG

Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a non-invasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond.

Imbalance in positive and negative acceleration ratio of alpha oscillation in patients with complex regional pain syndrome

Objectives

To elucidate the functional characteristics of the brain in the presence of chronic pain using electroencephalography (EEG), with a focus on the dynamics of neural excitation and inhibition.

Methods

Resting-state EEG was performed in: 17 patients with complex regional pain syndrome (CRPS) who exhibited chronic pain higher than 20 on the visual analogue scale (VAS), 6 patients with reduced CRPS symptoms and chronic pain less than 20 on VAS, and healthy age-matched controls. For the analysis, 50 s of electroencephalogram (EEG) signals were extracted from EEG recordings during wakefulness and rest with eyes closed. The envelope of the alpha frequency band was calculated by examining the positive and negative accelerations of the envelope oscillation, ratio of positive (Ap) to negative (An) accelerations (Ap-An ratio), and mean amplitude of the envelope. Comparisons were made between patients and controls, and correlations between these EEG measures and the subjective pain VAS were evaluated.Significant differences in the value of Ap, An and Ap-An ratio were observed at temporal and central electrodes between patients with pain symptoms and controls. Those with reduced CRPS symptoms exhibited a distinct Ap-An ratio at the majority of electrodes when compared with those exhibiting chronic pain.

Conclusions

Distinct patterns in alpha wave envelope dynamics, reflecting excitatory and inhibitory activities, were associated with chronic pain in patients with CRPS. The pain-relieved state of CRPS suggested that a new balance of activities was established. This relationship indicated a potential association between altered alpha oscillation characteristics and the subjective experience of pain.

Significance

This study introduces a novel method for analyzing alpha oscillation envelopes, providing new insights into the neural pathophysiology of chronic pain in CRPS patients. This approach has the potential to enhance our understanding of the alterations in brain function that occur under chronic pain conditions.

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

Introduction

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

Methods

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

Results

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

Discussion

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

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

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

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

ABSTRACT

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

Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

Pain control based on oscillatory brain activity using transcranial alternating current stimulation: An integrative review

Developing effective tools and strategies to relieve chronic pain is a high-priority scientific and clinical goal. In particular, the brain regions related to pain processing have been investigated as potential targets to relieve pain by non-invasive brain stimulation (NIBS). In addition to elucidating the relationship between pain and oscillatory brain activity, transcranial alternating current stimulation (tACS), which can non-invasively entrain oscillatory brain activity and modulate oscillatory brain communication, has attracted scientific attention as a possible technique to control pain. This review focuses on the use of tACS to relieve pain through the manipulation of oscillatory brain activity and its potential clinical applications. Several studies have reported that tACS on a single brain reduces pain by normalizing abnormal oscillatory brain activity in patients with chronic pain. Interpersonal tACS approaches based on inter-brain synchrony to manipulate inter-brain communication may result in pain relief via prosocial effects. Pain is encoded by the spatiotemporal neural communication that represents the integration of cognitive, emotional-affective, and sensorimotor aspects of pain. Therefore, future studies should seek to identify the pathological oscillatory brain communication in chronic pain as a therapeutic target for tACS. In conclusion, tACS could be effective for re-establishing oscillatory brain activity and assisting social interaction, and it might help develop novel approaches for pain control.

Exercise training augments brain function and reduces pain perception in adults with chronic pain: A systematic review of intervention studies

Introduction

Chronic pain (CP) is a leading cause of disability worldwide. Pain may be measured using subjective questionnaires, but understanding the underlying physiology, such as brain function, could improve prognosis. Further, there has been a shift towards cost-effective lifestyle modification for the management of CP.

Methods

We conducted a systematic review (Registration: #CRD42022331870) using articles retrieved from four databases (Pubmed, EMBASE, AMED, and CINAHL) to assess the effect of exercise on brain function and pain perception/quality of life in adults with CP.

Results

Our search yielded 1879 articles; after exclusion, ten were included in the final review. Study participants were diagnosed with either osteoarthritis or fibromyalgia. However, two studies included "fibromyalgia and low back pain" or "fibromyalgia, back, and complex regional pain." Exercise interventions that were 12 weeks or longer (n = 8/10) altered brain function and improved pain and/or quality of life outcomes. The cortico-limbic pathway, default-mode network, and dorsolateral prefrontal cortex were key regions that experienced alterations post-intervention. All studies that reported an improvement in brain function also demonstrated an improvement in pain perception and/or quality of life.

Discussion

Our review suggests that alterations in brain function, notably the cortico-limbic, default-mode and dorsolateral prefrontal cortex, may be responsible for the downstream improvements in the subjective experience of CP. Through appropriate programming (i.e., length of intervention), exercise may represent a viable option to manage CP via its positive influence on brain health.