Disrupted Resting State Network of Fibromyalgia in Theta frequency

Persistent homology-based functional connectivity and its association with cognitive ability: Life-span study

Brain-segregation attributes in resting-state functional networks have been widely investigated to understand cognition and cognitive aging using various approaches [e.g., average connectivity within/between networks and brain system segregation (BSS)]. While these approaches have assumed that resting-state functional networks operate in a modular structure, a complementary perspective assumes that a core-periphery or rich club structure accounts for brain functions where the hubs are tightly interconnected to each other to allow for integrated processing. In this article, we apply a novel method, persistent homology (PH), to develop an alternative to standard functional connectivity by quantifying the pattern of information during the integrated processing. We also investigate whether PH-based functional connectivity explains cognitive performance and compare the amount of variability in explaining cognitive performance for three sets of independent variables: (1) PH-based functional connectivity, (2) graph theory-based measures, and (3) BSS. Resting-state functional connectivity data were extracted from 279 healthy participants, and cognitive ability scores were generated in four domains (fluid reasoning, episodic memory, vocabulary, and processing speed). The results first highlight the pattern of brain-information flow over whole brain regions (i.e., integrated processing) accounts for more variance of cognitive abilities than other methods. The results also show that fluid reasoning and vocabulary performance significantly decrease as the strength of the additional information flow on functional connectivity with the shortest path increases. While PH has been applied to functional connectivity analysis in recent studies, our results demonstrate potential utility of PH-based functional connectivity in understanding cognitive function.

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.

Brain structure and cortical activity changes of new daily persistent headache: multimodal evidence from MEG/sMRI

BACKGROUND

New daily persistent headache (NDPH) is a rare but debilitating primary headache disorder that poses a significant burden on individuals and society. Despite its clinical importance, the underlying pathophysiological mechanisms of NDPH remain unclear. In this study, we aimed to investigate the brain structural changes and neural activity patterns in patients with NDPH using multimodal brain imaging analysis of structural magnetic resonance imaging (sMRI) combined with magnetoencephalography (MEG).

METHODS

Twenty-eight patients with NDPH and 37 healthy controls (HCs) were recruited for this study, and their structural and resting-state data were collected by 3.0 Tesla MRI and MEG. We analyzed the brain morphology using voxel-based morphometry and source-based morphometry. In each brain region, MEG sensor signals from 1 to 200 Hz were analyzed using an adapted version of Welch's method. MEG source localization was conducted using the dynamic statistical parametric mapping, and the difference of source distribution between patients with NDPH and HCs was examined.

RESULTS

Our results revealed significant differences in the regional grey matter volume, cortical thickness, and cortical surface area between the two groups. Specifically, compared with HCs, patients with NDPH showed a significant decrease in cortical thickness of the left rostral cortex in the middle frontal gyrus, decreased cortical surface area of the left fusiform gyrus, decreased grey matter volume of the left superior frontal gyrus and the left middle frontal gyrus, and increased grey matter volume of the left calcarine. Furthermore, the power of the whole brain, bilateral frontal lobes, and right temporal lobe in the NDPH group were higher than that in HCs in the ripple frequency band (80-200 Hz). Functional and structural analysis suggested that there were structural changes and abnormal high frequency cortical activity in both frontal and temporal lobes in patients with NDPH.

CONCLUSION

Our findings indicated that patients with NDPH have abnormalities in brain morphology, such as cortical area, cortical thickness, and grey matter volume, accompanied by abnormal cortical neural activity. Brain structural changes in the frontotemporal cortex and abnormalities in cortical ripple activity may be involved in the pathogenesis of NDPH.

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.

Neuroimaging Assessment of Pain

Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.

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

ABSTRACT

Chronic pain is a major healthcare issue posing a large burden on individuals and society. Converging lines of evidence indicate that chronic pain is associated with substantial changes of brain structure and function. However, it remains unclear which neuronal measures relate to changes of clinical parameters over time and could thus monitor chronic pain and treatment responses. We therefore performed a longitudinal study in which we assessed clinical characteristics and resting-state electroencephalography data of 41 patients with chronic pain before and 6 months after interdisciplinary multimodal pain therapy. We specifically assessed electroencephalography measures that have previously been shown to differ between patients with chronic pain and healthy people. These included the dominant peak frequency; the amplitudes of neuronal oscillations at theta, alpha, beta, and gamma frequencies; as well as graph theory-based measures of brain network organization. The results show that pain intensity, pain-related disability, and depression were significantly improved after interdisciplinary multimodal pain therapy. Bayesian hypothesis testing indicated that these clinical changes were not related to changes of the dominant peak frequency or amplitudes of oscillations at any frequency band. Clinical changes were, however, associated with an increase in global network efficiency at theta frequencies. Thus, changes in chronic pain might be reflected by global network changes in the theta band. These longitudinal insights further the understanding of the brain mechanisms of chronic pain. Beyond, they might help to identify biomarkers for the monitoring of chronic pain.

Increased gray matter following mindfulness-based stress reduction in breast cancer survivors with chronic neuropathic pain: preliminary evidence using voxel-based morphometry

PURPOSE

To investigate the impact of Mindfulness-Based Stress Reduction (MBSR) on gray matter volume (GMV) in female breast cancer survivors who suffer from chronic neuropathic pain (CNP).

METHODS

Voxel-based morphometry (VBM) was used to explore differences in GMV in 13 MBSR trainees and 10 waitlisted controls, with MRI scans and self-report measures completed pre- and post-8 weeks of training.

RESULTS

Compared to controls, the MBSR group had greater GMV in the angular gyrus and middle frontal gyrus post-training. The MBSR group's right parahippocampal gyrus GMV increased from pre- to post-training, whereas the control group's left parahippocampal gyrus, precuneus, middle temporal gyrus, and right cuneus GMV decreased over the same time period. Pain interference was significantly reduced and mindfulness was significantly increased following MBSR for the intervention group only.

CONCLUSIONS

MBSR was associated with increased GMV in regions where GMV is known to (1) increase with mindfulness and reorientation of attention and (2) decrease with the experience of chronic neuropathic pain. By contrast, the control group's decreases in GMV may be due to the negative effects of CNP which potentially may be reduced with MBSR, though further research is needed.

IMPLICATIONS FOR CANCER SURVIVORS

Given the poor efficiency of pharmacotherapies in a high percentage of women with neuropathic pain following breast cancer treatment, adjunct methods are required. MBSR may affect the brain to help alter attention and perception of pain, thus playing a potentially important role in the path to wellness for breast cancer survivors.

Topological data analysis in biomedicine: A review

Significant technological advances made in recent years have shepherded a dramatic increase in utilization of digital technologies for biomedicine- everything from the widespread use of electronic health records to improved medical imaging capabilities and the rising ubiquity of genomic sequencing contribute to a "digitization" of biomedical research and clinical care. With this shift toward computerized tools comes a dramatic increase in the amount of available data, and current tools for data analysis capable of extracting meaningful knowledge from this wealth of information have yet to catch up. This article seeks to provide an overview of emerging mathematical methods with the potential to improve the abilities of clinicians and researchers to analyze biomedical data, but may be hindered from doing so by a lack of conceptual accessibility and awareness in the life sciences research community. In particular, we focus on topological data analysis (TDA), a set of methods grounded in the mathematical field of algebraic topology that seeks to describe and harness features related to the "shape" of data. We aim to make such techniques more approachable to non-mathematicians by providing a conceptual discussion of their theoretical foundations followed by a survey of their published applications to scientific research. Finally, we discuss the limitations of these methods and suggest potential avenues for future work integrating mathematical tools into clinical care and biomedical informatics.

CNS imaging characteristics in fibromyalgia patients with and without peripheral nerve involvement

We tested the hypothesis that reduced skin innervation in fibromyalgia syndrome is associated with specific CNS changes. This prospective case–control study included 43 women diagnosed with fibromyalgia syndrome and 40 healthy controls. We further compared the fibromyalgia subgroups with reduced (n = 21) and normal (n = 22) skin innervation. Brains were analysed for cortical volume, for white matter integrity, and for functional connectivity. Compared to controls, cortical thickness was decreased in regions of the frontal, temporal and parietal cortex in the fibromyalgia group as a whole, and decreased in the bilateral pericalcarine cortices in the fibromyalgia subgroup with reduced skin innervation. Diffusion tensor imaging revealed a significant increase in fractional anisotropy in the corona radiata, the corpus callosum, cingulum and fornix in patients with fibromyalgia compared to healthy controls and decreased FA in parts of the internal capsule and thalamic radiation in the subgroup with reduced skin innervation. Using resting-state fMRI, the fibromyalgia group as a whole showed functional hypoconnectivity between the right midfrontal gyrus and the posterior cerebellum and the right crus cerebellum, respectively. The subgroup with reduced skin innervation showed hyperconnectivity between the inferior frontal gyrus, the angular gyrus and the posterior parietal gyrus. Our results suggest that the subgroup of fibromyalgia patients with pronounced pathology in the peripheral nervous system shows alterations in morphology, structural and functional connectivity also at the level of the encephalon. We propose considering these subgroups when conducting clinical trials.

The puzzle of fibromyalgia between central sensitization syndrome and small fiber neuropathy: a narrative review on neurophysiological and morphological evidence

Fibromyalgia (FM) is a condition characterized by chronic widespread pain whose pathogenesis is still not fully defined. Evidence based on structural and functional neuroimaging methods, electrophysiological, and morphological - skin biopsy - features demonstrated a central and peripheral nervous system involvement. A dysfunction in nociceptive inputs processing at the central level was highlighted as the primary cause of FM, but other data coming from different laboratories contributed to emphasize again the peripheral origin of FM. In fact, small fibers neuropathy (SFN) was observed in a large number of patients submitted to skin biopsy. The complex interaction between central and peripheral factors is opening a new scenario about the management of this neurological disorder. Whether proximal SFN is an initiating event leading to FM or is the consequence of stress-related insular hyper excitability remains unclear. Mild sufferance of peripheral afferents could function as a trigger for an exaggerated response of the so-called "salience matrix" in predisposed individuals. On the other side, the intriguing hypothesis rising from animal models could indicate that the cortical hyper function could cause peripheral small afferent damage. The research should go on the genetic origin of such peripheral and central abnormalities, the acquired facilitating factors, and the presence of different phenotypes in order to search for efficacious treatments, which are still lacking.

Structural and functional thalamocortical connectivity study in female fibromyalgia

Dysfunctional thalamocortical interactions have been suggested as putative mechanisms of ineffective pain modulation and also suggested as possible pathophysiology of fibromyalgia (FM). However, it remains unclear which specific thalamocortical networks are altered and whether it is related to abnormal pain perception in people with FM. Here, we conducted combined vertex-wise subcortical shape, cortical thickness, structural covariance, and resting-state functional connectivity analyses to address these questions. FM group exhibited a regional shape deflation of the left posterior thalamus encompassing the ventral posterior lateral and pulvinar nuclei. The structural covariance analysis showed that the extent of regional deflation of the left posterior thalamus was negatively covaried with the left inferior parietal cortical thickness in the FM group, whereas those two regions were positively covaried in the healthy controls. In functional connectivity analysis with the left posterior thalamus as a seed, FM group had less connectivity with the periaqueductal gray compared with healthy controls, but enhanced connectivity between the posterior thalamus and bilateral inferior parietal regions, associated with a lower electrical pain threshold at the hand dorsum (pain-free point). Overall, our findings showed the structural thalamic alteration interacts with the cortical regions in a functionally maladaptive direction, leading the FM brain more responsive to external stimuli and potentially contributing to pain amplification.

Functional Magnetic Resonance Imaging Signal Variability Is Associated With Neuromodulation in Fibromyalgia

OBJECTIVES

Although primary motor cortex (M1) transcranial direct current stimulation (tDCS) has an analgesic effect in fibromyalgia (FM), its neural mechanism remains elusive. We investigated whether M1-tDCS modulates a regional temporal variability of blood-oxygenation-level-dependent (BOLD) signals, an indicator of the brain's flexibility and efficiency and if this change is associated with pain improvement.

MATERIALS AND METHODS

In a within-subjects cross-over design, 12 female FM patients underwent sham and active tDCS on five consecutive days, respectively. Each session was performed with an anode placed on the left M1 and a cathode on the contralateral supraorbital region. The subjects also participated in resting-state functional magnetic resonance imaging (fMRI) at baseline and after sham and active tDCS. We compared the BOLD signal variability (SD_BOLD ), defined as the standard deviation of the BOLD time-series, between the tDCS conditions. Baseline SD_BOLD was compared to 15 healthy female controls.

RESULTS

At baseline, FM patients showed reduced SD_BOLD in the ventromedial prefrontal cortex (vmPFC), lateral PFC, and anterior insula and increased SD_BOLD in the posterior insula compared to healthy controls. After active tDCS, compared to sham, we found an increased SD_BOLD in the left rostral anterior cingulate cortex (rACC), lateral PFC, and thalamus. After sham tDCS, compared to baseline, we found a decreased SD_BOLD in the dorsomedial PFC and posterior cingulate cortex/precuneus. Interestingly, after active tDCS compared to sham, pain reduction was correlated with an increased SD_BOLD in the rACC/vmPFC but with a decreased SD_BOLD in the posterior insula.

CONCLUSION

Our findings suggest that M1-tDCS might revert temporal variability of fMRI signals in the rACC/vmPFC and posterior insula linked to FM pain. Changes in neural variability would be part of the mechanisms underlying repetitive M1-tDCS analgesia in FM.

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.

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.

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.

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.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

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.

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.

Neurochemical Correlates of Brain Atrophy in Fibromyalgia Syndrome: A Magnetic Resonance Spectroscopy and Cortical Thickness Study

(1) Background: Recently, a series of clinical neuroimaging studies on fibromyalgia (FM) have shown a reduction in cortical volume and abnormally high glutamate (Glu) and glutamate + glutamine (Glx) levels in regions associated with pain modulation. However, it remains unclear whether the volumetric decreases and increased Glu levels in FM are related each other. We hypothesized that higher Glu levels are related to decreases in cortical thickness (CT) and volume in FM patients. (2) Methods: Twelve females with FM and 12 matched healthy controls participated in a session of combined 3.0 Tesla structural magnetic resonance imaging (MRI) and single-voxel MR spectroscopy focused on the thalami and ventrolateral prefrontal cortices (VLPFC). The thickness of the cortical and subcortical gray matter structures and the Glu/Cr and Glx/Cr ratios were estimated. Statistics included an independent t-test and Spearman’s test. (3) Results: The Glu/Cr ratio of the left VLPFC was negatively related to the CT of the left inferior frontal gyrus (pars opercularis (p = 0.01; r = −0.75) and triangularis (p = 0.01; r = −0.70)). Moreover, the Glx/Cr ratio of the left VLPFC was negatively related to the CT of the left middle anterior cingulate gyrus (p = 0.003; r = −0.81). Significantly lower CTs in FM were detected in subparts of the cingulate gyrus on both sides and in the right inferior occipital gyrus (p < 0.001). (4) Conclusions: Our findings are in line with previous observations that high glutamate levels can be related, in a concentration-dependent manner, to the morphological atrophy described in FM patients.

Duration of the Symptoms and Brain Aging in Women with Fibromyalgia: A Cross-Sectional Study

Fibromyalgia is a chronic syndrome that is characterized by widespread pain and an altered brain dynamic. The aim of this study was to analyze the effect of the duration of the symptoms on the cortical activity of women with fibromyalgia using electroencephalogram power spectrum analyses in an eye-closed resting state. Twenty-nine women participated in this cross-sectional study (N: 29; age: 55.59 [9.50]). Theta, alpha, beta-1, beta-2, and beta-3 frequency bands were analyzed using EEGLAB. Theta power significantly correlated with the duration of the symptoms, but not with age. In addition, participants were divided into two groups according to number the years for which they were suffering from fibromyalgia. Participants who had a longer duration of symptoms obtained higher theta power in the frontal (Fp1, F4, F7, F8, and Fz), central (C3, C4, and Cz), and parietal (P3 and Pz) areas than those who had a shorter duration of symptoms, which may be related to brain aging. This exploratory study demonstrates for the first time that the frontal, central, and parietal areas may be influenced by the years in which they were suffering from the symptoms of fibromyalgia. This might indicate that the duration of these symptoms may have a higher impact on brain aging than the actual age of the patient.