Altered insula-default mode network connectivity in fibromyalgia: a resting-state magnetoencephalographic study

Pathology of pain and its implications for therapeutic interventions

Pain is estimated to affect more than 20% of the global population, imposing incalculable health and economic burdens. Effective pain management is crucial for individuals suffering from pain. However, the current methods for pain assessment and treatment fall short of clinical needs. Benefiting from advances in neuroscience and biotechnology, the neuronal circuits and molecular mechanisms critically involved in pain modulation have been elucidated. These research achievements have incited progress in identifying new diagnostic and therapeutic targets. In this review, we first introduce fundamental knowledge about pain, setting the stage for the subsequent contents. The review next delves into the molecular mechanisms underlying pain disorders, including gene mutation, epigenetic modification, posttranslational modification, inflammasome, signaling pathways and microbiota. To better present a comprehensive view of pain research, two prominent issues, sexual dimorphism and pain comorbidities, are discussed in detail based on current findings. The status quo of pain evaluation and manipulation is summarized. A series of improved and innovative pain management strategies, such as gene therapy, monoclonal antibody, brain-computer interface and microbial intervention, are making strides towards clinical application. We highlight existing limitations and future directions for enhancing the quality of preclinical and clinical research. Efforts to decipher the complexities of pain pathology will be instrumental in translating scientific discoveries into clinical practice, thereby improving pain management from bench to bedside.

Salivary Testosterone Levels and Pain Perception Exhibit Sex-Specific Association in Healthy Adults But Not in Patients With Migraine

This study investigated the sex-specific associations between pain perception and testosterone levels in healthy controls (HCs) and patients with migraine. Male and female HCs and migraine patients were recruited. A series of questionnaires were completed by the participants to evaluate their psychosocial profiles, which included data on mood, stress, and sleep quality. Heat pain thresholds and suprathreshold pain ratings at 45 °C (referred to as the pain perception score [PPS]) were assessed using the Thermode system. Salivary testosterone levels were analyzed using a commercial enzyme-linked immunosorbent assay kit. A total of 88 HCs (men/women: 41/47, age: 29.9 ± 7.7 years) and 75 migraine patients (men/women: 30/45, age: 31.1 ± 7.7 years) completed all assessments. No significant differences were observed in either the psychosocial profiles or heat pain thresholds and PPSs between the sexes in the control and migraine groups. A positive correlation between testosterone levels and PPSs was identified in the male controls (r = .341, P = .029), whereas a negative correlation was identified in the female controls (r = -.407, P = .005). No such correlations were identified in the migraine group. This study confirms that a negative association is present between PPSs and testosterone levels in female controls, which is in line with the findings that testosterone is associated with reduced pain perception. Our study is the first to demonstrate a sex-specific association between PPSs and testosterone levels in HCs. Moreover, this study also revealed that the presence of migraine appears to disrupt this association. PERSPECTIVE: This study revealed that testosterone levels demonstrate opposite associations with pain perception in healthy men and women. However, the presence of migraine appears to disrupt this sex-specific association.

Characteristic oscillatory brain networks for predicting patients with chronic migraine

To determine specific resting-state network patterns underlying alterations in chronic migraine, we employed oscillatory connectivity and machine learning techniques to distinguish patients with chronic migraine from healthy controls and patients with other pain disorders. This cross-sectional study included 350 participants (70 healthy controls, 100 patients with chronic migraine, 40 patients with chronic migraine with comorbid fibromyalgia, 35 patients with fibromyalgia, 30 patients with chronic tension-type headache, and 75 patients with episodic migraine). We collected resting-state magnetoencephalographic data for analysis. Source-based oscillatory connectivity within each network, including the pain-related network, default mode network, sensorimotor network, visual network, and insula to default mode network, was examined to determine intrinsic connectivity across a frequency range of 1-40 Hz. Features were extracted to establish and validate classification models constructed using machine learning algorithms. The findings indicated that oscillatory connectivity revealed brain network abnormalities in patients with chronic migraine compared with healthy controls, and that oscillatory connectivity exhibited distinct patterns between various pain disorders. After the incorporation of network features, the best classification model demonstrated excellent performance in distinguishing patients with chronic migraine from healthy controls, achieving high accuracy on both training and testing datasets (accuracy > 92.6% and area under the curve > 0.93). Moreover, in validation tests, classification models exhibited high accuracy in discriminating patients with chronic migraine from all other groups of patients (accuracy > 75.7% and area under the curve > 0.8). In conclusion, oscillatory synchrony within the pain-related network and default mode network corresponded to altered neurophysiological processes in patients with chronic migraine. Thus, these networks can serve as pivotal signatures in the model for identifying patients with chronic migraine, providing reliable and generalisable results. This approach may facilitate the objective and individualised diagnosis of migraine.

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.

Disturbed insular functional connectivity and its clinical implication in patients with complex regional pain syndrome

BACKGROUND

Complex regional pain syndrome (CRPS) is characterized by continued amplification of pain intensity. Given the pivotal roles of the insula in the perception and interpretation of pain, we examined insular functional connectivity and its associations with clinical characteristics in patients with CRPS.

METHODS

Twenty-one patients with CRPS and 49 healthy controls underwent resting-state functional magnetic resonance imaging. The seed-to-seed functional connectivity analysis was performed for the bilateral insulae and cognitive control regions including the dorsal anterior cingulate cortex (dACC) and bilateral dorsolateral prefrontal cortex (DLPFC) between the two groups. Correlations between altered functional connectivity and clinical characteristics were assessed in CRPS patients.

RESULTS

CRPS patients exhibited lower functional connectivity within the bilateral anterior insulae, between the insular and cognitive control regions (the bilateral anterior/posterior insulae-dACC; the right posterior insula-left DLPFC), as compared with healthy controls at false discovery rate-corrected p < 0.05. In CRPS patients, pain severity was associated negatively with the left-right anterior insular functional connectivity (r = -0.49, p = 0.03), yet positively with the left anterior insula-dACC functional connectivity (r = 0.51, p = 0.02).

CONCLUSIONS

CRPS patients showed lower functional connectivity both within the bilateral anterior insulae and between the insular and cognitive control regions. The current findings may suggest pivotal roles of the insula in dysfunctional pain processing of CRPS patients.

EEG Beta functional connectivity decrease in the left amygdala correlates with the affective pain in fibromyalgia: A pilot study

Fibromyalgia (FM) is a major chronic pain disease with prominent affective disturbances, and pain-associated changes in neurotransmitters activity and in brain connectivity. However, correlates of affective pain dimension lack. The primary goal of this correlational cross-sectional case-control pilot study was to find electrophysiological correlates of the affective pain component in FM. We examined the resting-state EEG spectral power and imaginary coherence in the beta (β) band (supposedly indexing the GABAergic neurotransmission) in 16 female patients with FM and 11 age-adjusted female controls. FM patients displayed lower functional connectivity in the High β (Hβ, 20-30 Hz) sub-band than controls (p = 0.039) in the left basolateral complex of the amygdala (p = 0.039) within the left mesiotemporal area, in particular, in correlation with a higher affective pain component level (r = 0.50, p = 0.049). Patients showed higher Low β (Lβ, 13-20 Hz) relative power than controls in the left prefrontal cortex (p = 0.001), correlated with ongoing pain intensity (r = 0.54, p = 0.032). For the first time, GABA-related connectivity changes correlated with the affective pain component are shown in the amygdala, a region highly involved in the affective regulation of pain. The β power increase in the prefrontal cortex could be compensatory to pain-related GABAergic dysfunction.

Identification of Resting-State Network Functional Connectivity and Brain Structural Signatures in Fibromyalgia Using a Machine Learning Approach

Abnormal resting-state functional connectivity (rs-FC) and brain structure have emerged as pathological hallmarks of fibromyalgia (FM). This study investigated and compared the accuracy of network rs-FC and brain structural features in identifying FM with a machine learning (ML) approach. Twenty-six FM patients and thirty healthy controls were recruited. Clinical presentation was measured by questionnaires. After MRI acquisitions, network rs-FC z-score and network-based gray matter volume matrices were exacted and preprocessed. The performance of feature selection and classification methods was measured. Correlation analyses between predictive features in final models and clinical data were performed. The combination of the recursive feature elimination (RFE) selection method and support vector machine (rs-FC data) or logistic regression (structural data), after permutation importance feature selection, showed high performance in distinguishing FM patients from pain-free controls, in which the rs-FC ML model outperformed the structural ML model (accuracy: 0.91 vs. 0.86, AUC: 0.93 vs. 0.88). The combined rs-FC and structural ML model showed the best performance (accuracy: 0.95, AUC: 0.95). Additionally, several rs-FC features in the final ML model correlated with FM's clinical data. In conclusion, ML models based on rs-FC and brain structural MRI features could effectively differentiate FM patients from pain-free subjects.

Resting-state functional connectivity predicts motor cortex stimulation-dependent pain relief in fibromyalgia syndrome patients

MRI-based resting-state functional connectivity (rsFC) has been shown to predict response to pharmacological and non-pharmacological treatments for chronic pain, but not yet for motor cortex transcranial magnetic stimulation (M1-rTMS). Twenty-seven fibromyalgia syndrome (FMS) patients participated in this double-blind, crossover, and sham-controlled study. Ten daily treatments of 10 Hz M1-rTMS were given over 2 weeks. Before treatment series, patients underwent resting-state fMRI and clinical pain evaluation. Significant pain reduction occurred following active, but not sham, M1-rTMS. The following rsFC patterns predicted reductions in clinical pain intensity after the active treatment: weaker rsFC of the default-mode network with the middle frontal gyrus (r = 0.76, p < 0.001), the executive control network with the rostro-medial prefrontal cortex (r = 0.80, p < 0.001), the thalamus with the middle frontal gyrus (r = 0.82, p < 0.001), and the pregenual anterior cingulate cortex with the inferior parietal lobule (r = 0.79, p < 0.001); and stronger rsFC of the anterior insula with the angular gyrus (r =  - 0.81, p < 0.001). The above regions process the attentional and emotional aspects of pain intensity; serve as components of the resting-state networks; are modulated by rTMS; and are altered in FMS. Therefore, we suggest that in FMS, the weaker pre-existing interplay between pain-related brain regions and networks, the larger the pain relief resulting from M1-rTMS.

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1–40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability.

Is there hemispheric specialization in the chronic pain brain?

Organismal bilateral symmetry is associated with near-identical halves of the central nervous system, with certain functions displaying specialization through one brain hemisphere. The processing of pain in the brain as well as brain plasticity in the context of painful injuries have garnered much attention in recent decades. Noninvasive brain imaging studies in pain-free human subjects have identified multiple brain regions that are linked to the sensory and affective components of pain. Longlasting adaptations in brains of chronic pain sufferers have likewise been described, suggesting a mechanism for pain chronification. Invasive molecular and biochemical studies in animal models have expanded on these findings, with added emphasis on the role of specific genes and molecules involved. To date, the extent of hemispheric asymmetry in the context of pain is not well-understood. This topical review evaluates the evidence of hemispheric specialization observed in humans and rodent models of pain and compares it to findings where such asymmetry is absent. Our review shows conflicting information regarding the existence of pain-related asymmetry, and if so, the side to which it can be localized. This could be due to the heterogeneity of pain processing pathways, heterogeneity in study parameters, as well as differences in data reporting. With the advent of progressively sophisticated non-invasive tools that can be used in human subjects, in addition to more precise methods to visualize and control specific brain regions or neuronal ensembles in animal models, we predict that the next few decades will witness a better understanding of the supraspinal control and processing of chronic pain, including the role of each of its hemispheres.

Pain, But Not Physical Activity, Is Associated with Gray Matter Volume Differences in Gulf War Veterans with Chronic Pain

Chronic musculoskeletal pain (CMP) is a significant burden for Persian Gulf War Veterans (GWVs), yet the causes are poorly understood. Brain structure abnormalities are observed in GWVs, however relationships with modifiable lifestyle factors such as physical activity (PA) are unknown. We evaluated gray matter volumes and associations with symptoms, PA, and sedentary time in GWVs with and without CMP. Ninety-eight GWVs (10 females) with CMP and 56 GWVs (7 females) controls completed T1-weighted magnetic resonance imaging, pain and fatigue symptom questionnaires, and PA measurement via actigraphy. Regional gray matter volumes were analyzed using voxel-based morphometry and were compared across groups using analysis of covariance (ANCOVA). Separate multiple linear regression models were used to test associations between PA intensities, sedentary time, symptoms, and gray matter volumes. Familywise cluster error rates were used to control for multiple comparisons (α = 0.05). GWVs with CMP reported greater pain and fatigue symptoms, worse mood, and engaged in less moderate-to-vigorous PA and more sedentary time than healthy GWVs (all p values < 0.05). GWVs with CMP had smaller gray matter volumes in the bilateral insula and larger volumes in the frontal pole (p < 0.05adjusted). Gray matter volumes in the left insula were associated with pain symptoms (r partial = 0.26, -0.29; p < 0.05adjusted). No significant associations were observed for either PA or sedentary time (p > 0.05adjusted). GWVs with CMP had smaller gray matter volumes within a critical brain region of the descending pain processing network and larger volumes within brain regions associated with pain sensation and affective processing, which may reflect pain chronification.SIGNIFICANCE STATEMENT The pathophysiology of chronic pain in Gulf War veterans is understudied and not well understood. In a large sample of Gulf War veterans, we report veterans with chronic musculoskeletal pain have smaller gray matter volumes in brain regions associated with pain regulation and larger volumes in regions associated with pain sensitivity compared with otherwise healthy Gulf War veterans. Gray matter volumes in regions of pain regulation were significantly associated with pain symptoms and encompassed the observed group brain volume differences. These results are suggestive of deficient pain modulation that may contribute to pain chronification.

Resting State Electrophysiological Cortical Activity: A Brain Signature Candidate for Patients with Migraine

PURPOSE OF REVIEW

Studies on event-related evoked potentials have indicated that altered cortical processing of sensory stimuli is associated with migraine. However, the results depend on the experimental method and patients. Electrophysiology of resting state cortical activity has revealed compelling results regarding the pathophysiology of migraine. This review summarized the available information related to patients with episodic and chronic migraine to determine whether certain features can be used as signatures for migraine.

RECENT FINDINGS

A recent study examined differences in resting state functional connectivity among the pain-related regions and revealed that beta connectivity was attenuated in migraine and that altered connectivity in the anterior cingulate cortex was linked to migraine chronification. These findings suggested that chronification leads to neuroplasticity in the pain areas of higher-level processing rather than in areas involved in basic sensory discrimination (i.e., primary and secondary somatosensory areas). Another study discovered that the betweenness centrality of delta band in right precuneus was significantly lower in those with longer history of migraine. Electroencephalogram may also predict the treatment outcomes in patients with chronic migraine that those with lower pre-treatment occipital alpha power tend to show greater reduction in headache frequency. Studies on resting state activity have yielded convincing findings regarding aberrant oscillatory power and functional connectivity in relation to migraine, thus contributing to identifying brain signatures for migraine. The role of such assessment in precision medicine should be further investigated.

Dynamic brainstem and somatosensory cortical excitability during migraine cycles

Abstract

Background

Migraine has complex pathophysiological characteristics and episodic attacks. To decipher the cyclic neurophysiological features of migraine attacks, in this study, we compared neuronal excitability in the brainstem and primary somatosensory (S1) region between migraine phases for 30 consecutive days in two patients with episodic migraine.

Methods

Both patients underwent EEG recording of event-related potentials with the somatosensory and paired-pulse paradigms for 30 consecutive days. The migraine cycle was divided into the following phases: 24–48 h before headache onset (Pre2), within 24 h before headache onset (Pre1), during the migraine attack (Ictal), within 24 h after headache offset (Post1), and the interval of ˃48 h between the last and next headache phase (Interictal). The normalised current intensity in the brainstem and S1 and gating ratio in the S1 were recorded and examined.

Results

Six migraine cycles (three for each patient) were analysed. In both patients, the somatosensory excitability in the brainstem (peaking at 12–14 ms after stimulation) and S1 (peaking at 18–19 ms after stimulation) peaked in the Pre1 phase. The S1 inhibitory capability was higher in the Ictal phase than in the Pre1 phase.

Conclusion

This study demonstrates that migraine is a cyclic excitatory disorder and that the neural substrates involved include the somatosensory system, starting in the brainstem and spanning subsequently to the S1 before the migraine occurs. Further investigations with larger sample sizes are warranted.

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.

Deep Brain Stimulation of the Posterior Insula in Chronic Pain: A Theoretical Framework

INTRODUCTION

To date, clinical trials of deep brain stimulation (DBS) for refractory chronic pain have yielded unsatisfying results. Recent evidence suggests that the posterior insula may represent a promising DBS target for this indication.

METHODS

We present a narrative review highlighting the theoretical basis of posterior insula DBS in patients with chronic pain.

RESULTS

Neuroanatomical studies identified the posterior insula as an important cortical relay center for pain and interoception. Intracranial neuronal recordings showed that the earliest response to painful laser stimulation occurs in the posterior insula. The posterior insula is one of the only regions in the brain whose low-frequency electrical stimulation can elicit painful sensations. Most chronic pain syndromes, such as fibromyalgia, had abnormal functional connectivity of the posterior insula on functional imaging. Finally, preliminary results indicated that high-frequency electrical stimulation of the posterior insula can acutely increase pain thresholds.

CONCLUSION

In light of the converging evidence from neuroanatomical, brain lesion, neuroimaging, and intracranial recording and stimulation as well as non-invasive stimulation studies, it appears that the insula is a critical hub for central integration and processing of painful stimuli, whose high-frequency electrical stimulation has the potential to relieve patients from the sensory and affective burden of chronic pain.

Abnormal subgenual anterior cingulate circuitry is unique to women but not men with chronic pain

The subgenual anterior cingulate cortex (sgACC) plays an important role in pain modulation. We previously demonstrated sex differences in sgACC functional connectivity (FC) in healthy individuals. Given that many chronic pain conditions show sex differences in prevalence, here we tested the hypothesis that people with chronic pain exhibit a sex-specific pattern of abnormal sgACC FC. We acquired resting-state functional magnetic resonance imaging data from 156 (82 W: 74 M) healthy participants and 38 (19 W: 19 M) people with chronic low back pain resulting from ankylosing spondylitis, a condition that predominantly affects men. We confirmed that there are sex differences in sgACC FC in our large cohort of healthy adults; women had greater sgACC FC with the precuneus, a key node of the default mode network, and men had greater sgACC FC with the posterior insula and the operculum. Next, we identified an interaction effect between sex and pain status (healthy/chronic pain) for sgACC FC. Within the chronic pain group, women had greater sgACC FC than men to the default mode and sensorimotor networks. Compared to healthy women, women with chronic pain also had greater sgACC FC to the precuneus and lower FC to the hippocampus and frontal regions. No differences in sgACC FC were seen in men with vs without chronic pain. Our findings indicate that abnormal sgACC circuitry is unique to women but not men with ankylosing spondylitis-related chronic pain. These sex differences may impact the benefit of therapeutics that target the sgACC for chronic pain.

Music Intervention Reduces Persistent Fibromyalgia Pain and Alters Functional Connectivity Between the Insula and Default Mode Network

OBJECTIVE

The aims of the present study were to examine the effects of short-term music interventions among patients with fibromyalgia (FM) and to clarify the alterations in functional connectivity and persistent pain.

DESIGN

Pilot study.

SETTING

All participants were evaluated at Juntendo University from November 2017 to January 2019.

SUBJECTS

We enrolled female patients who had been clinically diagnosed with FM (N = 23).

METHODS

All participants listened to Mozart's Duo for Violin and Viola No. 1, K. 423, in a quiet room for 17 minutes. We compared the degree of pain using resting-state functional magnetic resonance imaging and the numeric rating scale before and after listening to music.

RESULTS

Pain scores were significantly reduced after listening to music. Further, we observed there was a significant difference in connectivity between the right insular cortex (IC) and posterior cingulate cortex (PCC)/precuneus (PCu) before and after listening to music. We also found that the difference between the right IC-PCu connectivity and the difference in pain scores were significantly correlated.

CONCLUSIONS

We found that a short period of music intervention reduced chronic pain and altered functional IC-default mode network connectivity. Furthermore, music potentially normalized the neural network via IC-default mode network connectivity, yielding temporary pain relief in patients with FM. Further longitudinal studies with larger sample sizes are required to confirm these results.

Chronic pain-related cortical neural activity in patients with complex regional pain syndrome

Quantitative objective measurement of chronic pain is important. We elucidated chronic pain-related cortical neural activity and neural connectivity among pain-related brain regions in complex regional pain syndrome (CRPS). Resting-state magnetoencephalography recordings were performed. Cortical current density and neural connectivity, revealed by amplitude envelope correlation (AEC), were estimated on standardized brain magnetic resonance imaging. Intra-experiment pain was assessed subjectively using a visual analogue scale (VAS). The correlation between current density and VAS scores was calculated for the occipital areas and pain-related cortices. Current density in the primary (SI) and secondary (SII) somatosensory cortex and precuneus in both hemispheres was negatively correlated with the pain VAS score. The AEC and VAS values were significantly correlated for the SII and the precuneus and for the SII and insular cortex in the alpha frequency band in the right hemisphere. In the theta frequency band, the AEC and VAS values correlated for the SII and posterior cingulate cortex in the right hemisphere. Our results suggested that disruption of pain processes and functions in the default mode network occurs in CRPS. Our method targeting the neural mechanism of pain has the potential to offer a clinically objective means of evaluating it.

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Chronic pain can be objectively evaluated with magnetoencephalography.

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Neural connectivity of pain-related cortices was reduced in complex regional pain syndrome.

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Default mode network is disrupted in complex regional pain syndrome patients.

Why It Hurts: The Mechanisms of Pain in Rheumatoid Arthritis

Pain is a near-universal feature of rheumatoid arthritis, but peripheral joint inflammation may not suffice to explain the etiology of pain in all patients with rheumatoid arthritis. Inflammation in rheumatoid arthritis releases several algogens that may generate pain. Also, central nervous system processes may play a crucial role in the regulation and perpetuation of pain. Several methods for assessing pain in rheumatoid arthritis exist, and recently the role of assessing therapeutics in treating specific etiologies of pain has gained interest.

Correlating cognition and cortical excitability with pain in fibromyalgia: a case control study

BACKGROUND

Fibromyalgia is a chronic pain disorder characterized by widespread musculoskeletal symptoms, primarily attributed to sensitization of somatosensory system carrying pain. Few reports have investigated the impact of fibromyalgia symptoms on cognition, corticomotor excitability, sleepiness, and the sleep quality - all of which can deteriorate the quality of life in fibromyalgia. However, the existing reports are underpowered and have conflicting directions of findings, limiting their generalizability. Therefore, the present study was designed to compare measures of cognition, corticomotor excitability, sleepiness, and sleep quality using standardized instruments in the recruited patients of fibromyalgia with pain-free controls.

METHODS

Diagnosed cases of fibromyalgia were recruited from the Rheumatology department for the cross-sectional, case-control study. Cognition (Mini-Mental State Examination, Stroop color-word task), corticomotor excitability (Resting motor threshold, Motor evoked potential amplitude), daytime sleepiness (Epworth sleepiness scale), and sleep quality (Pittsburgh sleep quality index) were studied according to the standard procedure.

RESULTS

Thirty-four patients of fibromyalgia and 30 pain-free controls were recruited for the study. Patients of fibromyalgia showed decreased cognitive scores (p = 0.05), lowered accuracy in Stroop color-word task (for color: 0.02, for word: 0.01), and prolonged reaction time (< 0.01, < 0.01). Excessive daytime sleepiness in patients were found (< 0.01) and worsened sleep quality (< 0.01) were found. Parameters of corticomotor excitability were comparable between patients of fibromyalgia and pain-free controls.

CONCLUSIONS

Patients of fibromyalgia made more errors, had significantly increased reaction time for cognitive tasks, marked daytime sleepiness, and impaired quality of sleep. Future treatment strategies may include cognitive deficits and sleep disturbances as an integral part of fibromyalgia management.

Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences

Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.

Salivary cortisol is associated with cognitive changes in patients with fibromyalgia

Fibromyalgia (FM) is a stress-related chronic pain disorder with common cognitive complaints. This study characterized cognitive dysfunction in patients with FM and explored whether these changes are linked to altered cortisol levels. Consecutive 44 patients with FM and 48 healthy controls were enrolled for the assessments of subjective and objective cognitive functions and diurnal levels of salivary cortisol (sampled at awakening, 30 min after awakening, 3 pm, and bedtime). All measurements were compared between the groups and evaluated for clinical correlation. The FM group had more subjective cognitive complaints and performed poorer in objective cognitive testing in memory (delayed recall in Chinese Version Verbal Learning Test and Taylor Complex Figure Test), language (Boston Naming Test), and executive domains (Wisconsin Card Sorting Test) after adjustments for education. The diurnal cortisol levels of patients with FM tended to be lower, especially at 30 min after awakening and bedtime. Moreover, moderate positive correlations existed between the Chinese Version Verbal Learning Test, Boston Naming Test and the morning cortisol levels within the FM group. We suggested the altered cognitive function in FM may be linked to stress maladaptation. Future studies are warranted to elucidate whether stress management improves cognitive performance in patients with FM.

Neuromagnetic Amygdala Response to Pain-Related Fear as a Brain Signature of Fibromyalgia

INTRODUCTION

Fibromyalgia (FM) is a chronic pain condition characterized by impaired emotional regulation. This study explored the brain response to pain-related fear as a potential brain signature of FM.

METHODS

We used a conditioned fear task and magnetoencephalography to record pain-related fear responses in patients with FM. Two blocks of 30 fear responses were collected to compute the response strength in the first block and the strength difference between the first and second blocks (fear habituation). These measurements were investigated for their clinical relevance and compared with measurements obtained from healthy controls and patients with chronic migraine (CM), a different chronic pain condition often comorbid with FM.

RESULTS

Pain-related fear clearly activated the bilateral amygdala and anterior insula in patients with FM (n = 52), patients with CM (n = 50), and the controls (n = 30); the response strength in the first block was consistent across groups. However, fear habituation in the right amygdala decreased in the FM group (vs. CM and control groups, both p ≤ 0.001, no difference between CM and control groups). At the 3-month follow-up, the patients with FM reporting < 30% improvement in pain severity (n = 15) after pregabalin treatment exhibited lower fear habituation in the left amygdala at baseline (vs. ≥ 30% improvement, n = 22, p = 0.019). Receiver operating characteristic analysis confirmed that amygdala fear habituation is a suitable predictor of diagnosis and treatment outcomes of FM (area under the curve > 0.7).

CONCLUSIONS

Amygdala activation to pain-related fear is maladaptive and linked to treatment outcomes in patients with FM. Because the aberrant amygdala response was not observed in the CM group, this response is a potential brain signature of FM.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier, NCT02747940.

Individual pain sensitivity is associated with resting-state cortical activities in healthy individuals but not in patients with migraine: a magnetoencephalography study

Background

Pain sensitivity may determine the risk, severity, prognosis, and efficacy of treatment of clinical pain. Magnetic resonance imaging studies have linked thermal pain sensitivity to changes in brain structure. However, the neural correlates of mechanical pain sensitivity remain to be clarified through investigation of direct neural activities on the resting-state cortical oscillation and synchrony.

Methods

We recorded the resting-state magnetoencephalographic (MEG) activities of 27 healthy individuals and 30 patients with episodic migraine (EM) and analyzed the source-based oscillatory powers and functional connectivity at 2 to 59 Hz in pain-related cortical regions, which are the bilateral anterior cingulate cortex (ACC), medial orbitofrontal (MOF) cortex, lateral orbitofrontal (LOF) cortex, insula cortex, primary somatosensory cortex (SI), primary motor cortex (MI), and posterior cingulate cortex (PCC). The mechanical punctate pain threshold (MPPT) was obtained at the supraorbital area (the first branch of the trigeminal nerve dermatome, V1) and the forearm (the first thoracic nerve dermatome, T1) and further correlated with MEG measures.

Results

The MPPT is inversely correlated with the resting-state relative powers of gamma oscillation in healthy individuals (all corrected P < 0.05). Specifically, inverse correlation was noted between the MPPT at V1 and gamma powers in the bilateral insula (r = − 0.592 [left] and − 0.529 [right]), PCC (r = − 0.619 and − 0.541) and MI (r = − 0.497 and − 0.549) and between the MPPT at T1 and powers in the left PCC (r = − 0.561) and bilateral MI (r = − 0.509 and − 0.520). Furthermore, resting-state functional connectivity at the delta to beta bands, especially between frontal (MOF, ACC, LOF, and MI), parietal (PCC), and sensorimotor (bilateral SI and MI) regions, showed a positive correlation with the MPPT at V1 and T1 (all corrected P < 0.05). By contrast, in patients with EM, the MPPT was not associated with resting-state cortical activities.

Conclusions

Pain sensitivity in healthy individuals is associated with the resting-state gamma oscillation and functional connectivity in pain-related cortical regions. Further studies must be conducted in a large population to confirm whether resting-state cortical activities can be an objective measurement of pain sensitivity in individuals without clinical pain.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-020-01200-8.

Patients with fibromyalgia show increased beta connectivity across distant networks and microstates alterations in resting-state electroencephalogram

Fibromyalgia (FM) is a chronic condition characterized by widespread pain of unknown etiology associated with alterations in the central nervous system. Although previous studies demonstrated altered patterns of brain activity during pain processing in patients with FM, alterations in spontaneous brain oscillations, in terms of functional connectivity or microstates, have been barely explored so far. Here we recorded the EEG from 43 patients with FM and 51 healthy controls during open-eyes resting-state. We analyzed the functional connectivity between different brain networks computing the phase lag index after group Independent Component Analysis, and also performed an EEG microstates analysis. Patients with FM showed increased beta band connectivity between different brain networks and alterations in some microstates parameters (specifically lower occurrence and coverage of microstate class C). We speculate that the observed alterations in spontaneous EEG may suggest the dominance of endogenous top-down influences; this could be related to limited processing of novel external events and the deterioration of flexible behavior and cognitive control frequently reported for FM. These findings provide the first evidence of alterations in long-distance phase connectivity and microstate indices at rest, and represent progress towards the understanding of the pathophysiology of fibromyalgia and the identification of novel biomarkers for its diagnosis.

A Combination of Particle Swarm Optimization and Minkowski Weighted K-Means Clustering: Application in Lateralization of Temporal Lobe Epilepsy

K-Means is one of the most popular clustering algorithms that partitions observations into nonoverlapping subgroups based on a predefined similarity metric. Its drawbacks include a sensitivity to noisy features and a dependency of its resulting clusters upon the initial selection of cluster centroids resulting in the algorithm converging to local optima. Minkowski weighted K-Means (MWK-Means) addresses the issue of sensitivity to noisy features, but is sensitive to the initialization of clusters, and so the algorithm may similarly converge to local optima. Particle Swarm Optimization (PSO) uses a globalized search method to solve this issue. We present a hybrid Particle Swarm Optimization (PSO) + MWK-Means clustering algorithm to address all the above problems in a single framework, while maintaining benefits of PSO and MWK Means methods. This study investigated the utility of this approach in lateralizing the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Using MEG-CSI, we analyzed preoperative resting state MEG data from 17 adults TLE patients with Engel class I outcomes to determine coherence at 54 anatomical sites and compared the results with 17 age- and gender-matched controls. Fiber-tracking was performed through the same anatomical sites using DTI data. Indices of both MEG coherence and DTI nodal degree were calculated. A PSO + MWK-Means clustering algorithm was applied to identify the side of temporal lobe epileptogenicity and distinguish between normal and TLE cases. The PSO module was aimed at identifying initial cluster centroids and assigning initial feature weights to cluster centroids and, hence, transferring to the MWK-Means module for the final optimal clustering solution. We demonstrated improvements with the use of the PSO + MWK-Means clustering algorithm compared to that of K-Means and MWK-Means independently. PSO + MWK-Means was able to successfully distinguish between normal and TLE in 97.2% and 82.3% of cases for DTI and MEG data, respectively. It also lateralized left and right TLE in 82.3% and 93.6% of cases for DTI and MEG data, respectively. The proposed optimization and clustering methodology for MEG and DTI features, as they relate to focal epileptogenicity, would enhance the identification of the TLE laterality in cases of unilateral epileptogenicity.

Subjective cognitive decline detected by the oscillatory connectivity in the default mode network: a magnetoencephalographic study

Discriminating between those with and without subjective cognitive decline (SCD) in cross-sectional investigations using neuropsychological tests is challenging. The available magnetoencephalographic (MEG) studies have demonstrated altered alpha-band spectral power and functional connectivity in those with SCD. However, whether the functional connectivity in other frequencies and brain networks, particularly the default mode network (DMN), exhibits abnormalities in SCD remains poorly understood. We recruited 26 healthy controls (HC) without SCD and 27 individuals with SCD to perform resting-state MEG recordings. The power of each frequency band and functional connectivity within the DMN were compared between these two groups. Posterior cingulate cortex (PCC)-based connectivity was also used to test its diagnostic accuracy as a predictor of SCD. There were no significant between-group differences of spectral power in the regional nodes. However, compared with HC, those with SCD demonstrated increased delta-band and gamma-band functional connectivity within the DMN. Moreover, node strength in the PCC exhibited a good discrimination ability at both delta and gamma frequencies. Our data suggest that the node strength of delta and gamma frequencies in the PCC may be a good neurophysiological marker in the discrimination of individuals with SCD from those without SCD.

Chronic pain in adults with sickle cell disease is associated with alterations in functional connectivity of the brain

Chronic pain affects 50% of adults with sickle cell disease (SCD). Although central sensitization is thought to contribute to the pathogenesis of this chronic pain, no studies have examined differences in functional connectivity of the brain between patients with SCD with and without chronic pain. We performed an observational cohort study using resting-state functional MRI (rsfMRI) of the brain on adults with SCD with and without chronic pain. We tested the hypothesis that, compared to those without chronic pain, those with chronic pain would have differences in functional connectivity between the periaqueductal grey (PAG) and other regions of the brain. Twenty-two adults with SCD, 15 with chronic pain and 7 without chronic pain, as well as 10 African-American controls, underwent rsfMRI of the brain. When SCD patients with chronic pain were compared to those without chronic pain, significant differences in connectivity were noted between the PAG and 9 regions of the brain, including several in the default mode network, a network involved in introspection that has been implicated in other chronic pain syndromes. Changes in functional connectivity between patients with SCD with and without chronic pain suggest a mechanism for chronic pain that involves neuro-plastic changes to the brain.

Association between brain-derived neurotrophic factor gene polymorphisms and fibromyalgia in a Korean population: a multicenter study

Background

Several lines of evidence imply that brain-derived neurotrophic factor (BDNF) is involved in the pathophysiology of fibromyalgia (FM); in this regard, patients with FM have altered blood and cerebrospinal fluid levels of BDNF. In this study, we explored the association between BDNF gene polymorphisms and FM susceptibility and the severity of symptoms.

Methods

In total, 409 patients with FM and 423 healthy controls in 10 medical centers were enrolled from the Korean nationwide FM survey. The alleles and genotypes at 10 positions in the BDNF gene were genotyped.

Results

The allele and genotype frequencies of BDNF rs11030104 differed significantly between the patients with FM and the controls (P = 0.031). The GG genotype of rs11030104 had a protective effect against FM (P = 0.016), and the G allele of rs11030104 was negatively associated with the presence of FM compared with the A allele (P = 0.013). In comparison, although the allele and genotype frequencies of BDNF rs12273539 did not differ between the two groups, the TT genotype of BDNF rs12273539 was associated with susceptibility to FM (P = 0.038). Haplotype analyses implied that some BDNF haplotypes have a protective effect against FM. Finally, several genotypes and haplotypes of the BDNF gene contributed to specific symptoms of FM.

Conclusions

This study is the first to evaluate the associations between BDNF gene polymorphisms and FM. Our results imply that some BDNF single-nucleotide polymorphisms and haplotypes are associated with susceptibility to, and contribute to the symptoms of, FM.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.

Pain and chronic mild traumatic brain injury in the US military population: a Chronic Effects of Neurotrauma Consortium study

PRIMARY OBJECTIVES

To describe the association between mild traumatic brain injury (mTBI) and pain intensity and pain interference outcomes while accounting for potential confounders and mediators including environmental factors and comorbidities in a cohort of US Veterans of the Iraq and Afghanistan wars.

RESEARCH DESIGN

Cross-sectional snapshot of baseline data from a prospective, longitudinal study.

METHODS

Effects of mTBI on pain intensity and pain interference were compared between participants with or without mTBI exposure. Data were analysed using covariate-adjusted regression analyses as well as structural equation modelling (SEM) methods to assess the robustness of findings across different modelling assumptions. As results of the two approaches were consistent with respect to the overall association between mTBI exposure and pain, the results focus primarily on the SEM findings.

RESULTS

The mTBI exposed group reported significantly greater indices of post-traumatic stress disorder (PTSD), depression, anxiety and sleep disturbance. After accounting for other factors, mTBI exposure was significantly, but indirectly associated with the pain interference and pain intensity outcomes.

CONCLUSIONS

mTBI is strongly associated with pain intensity and pain interference in this sample. However, the effect appears to be mediated by other common mTBI comorbidities: PTSD, depression, anxiety and sleep disturbance.

Disrupted Resting State Network of Fibromyalgia in Theta frequency

Fibromyalgia (FM), chronic widespread pain, exhibits spontaneous pain without external stimuli and is associated with altered brain activities during resting state. To understand the topological features of brain network in FM, we employed persistent homology which is a multiple scale network modeling framework not requiring thresholding. Spontaneous magnetoencephalography (MEG) activity was recorded in 19 healthy controls (HCs) and 18 FM patients. Barcode, single linkage dendrogram and single linkage matrix were generated based on the proposed modeling framework. In theta band, the slope of decrease in the number of connected components in barcodes showed steeper in HC, suggesting FM patients had decreased global connectivity. FM patients had reduced connectivity within default mode network, between middle/inferior temporal gyrus and visual cortex. The longer pain duration was correlated with reduced connectivity between inferior temporal gyrus and visual cortex. Our findings demonstrated that the aberrant resting state network could be associated with dysfunction of sensory processing in chronic pain. The spontaneous nature of FM pain may accrue to disruption of resting state network.