Frontiers in Human Neuroscience

Part of the multifaceted pathophysiology of Complex Regional Pain syndrome (CRPS) has been ascribed to a lateralized maladaptive neuroplasticity in sensorimotor cortices, a finding that has been corroborated by behavioral studies indicating that CRPS patients indeed present difficulties in mentally representing their painful limb. Hand laterality judgment tasks (HLT) are widely used to measure such difficulties, with the laterality of hand stimuli corresponding to the affected hand judged more slowly than the one of hand stimuli corresponding to the unaffected hand. Importantly, the HLT is also regularly used in the rehabilitation of CRPS and other chronic pain disorders, with the aim to activate motor imagery and, consequently, restoring the cortical representation of the limb. The potential of these tasks to elicit motor imagery is thus critical to their use in therapy. Yet, the influence of the biomechanical constraints (BMC) on HLT reaction time, supposed to reflect the activation of motor imagery, is rarely verified. In the present study we investigated the influence of the BMC on the perception of hand postures and movements. The results of a first experiment, in which a HLT was used, showed that CRPS patients were significantly slower than controls in judging hand stimuli, whether or not the depicted hand corresponded to their affected hand, but that their performance did not differ from controls when they judged non-body stimuli. Results regarding reaction time patterns reflecting the BMC were inconclusive in CRPS and controls, questioning the validity of the task in activating motor imagery processes. In a second experiment we therefore directly investigated the influence of implicit knowledge of upper-limb BMC on perceptual judgments of hand movements with the apparent body movement perception task. Participants judge the perceived path of movement between two depicted hand positions, with only one of the two proposed paths that is biomechanically plausible. While the controls chose the biomechanically plausible path most of the time, CRPS patients did not, indicating that the perception and/or use of the BMC seems to be disturbed in CRPS. These findings show a non-lateralized body representation impairment in CRPS, which might be related to difficulties in using correct knowledge of the bodys biomechanics. Most importantly however, our results, in agreement with previous studies, indicate that it seems highly challenging to measure motor imagery and the indexes of BMC with the classical HLT task, which has important implications for the rehabilitation of chronic pain with these tasks.

Fibromyalgia is characterized by widespread musculoskeletal pain accompanied by sleep disturbances and cognitive dysfunction, among other symptoms. Patients frequently report difficulties with memory, but objective assessment of these impairments remains limited. This study aimed to evaluate working memory performance in fibromyalgia patients using two established paradigms: the change detection task, which primarily measures storage capacity, and the n-back task, which assesses both storage and manipulation of information. For the change detection task, the behavioral outcomes assessed were the hit rate, false alarm rate, capacity estimate and response times. The electrophysiological measure evaluated was the contralateral delayed activity. For the n-back, the behavioral outcomes were the same, except for the capacity estimate. Electrophysiologically, the P2 and P3 from the evoked potentials were the outcomes of the task. Behaviorally, results demonstrated that fibromyalgia patients exhibited lower memory capacity than controls (1.90 vs 2.64), in the change detection task, which involved differences in the hit rate and false alarm rate, whereas no behavioral differences were found for the n-back task. In contrast, no differences were found for any of the electrophysiological outcomes in any of the tasks. Taken together, we found evidence supporting a reduction in working memory capacity in fibromyalgia, although it is not reflected in electrophysiological measures.

Peripheral magnetic stimulation (PMS) is a noninvasive technique applicable to post-stroke rehabilitation, treatment of phantom limb pain (PLP) and generating neuroprosthetic sensations. Here we aimed to test whether PMS could be utilized to enable sensory feedback from hand prostheses and suppress PLP. Accordingly, we induced somatic sensations with PMS and conducted EEG measurements to assess sensory evoked potentials (SEPs) in 30 able-bodied participants (controls) and 11 individuals with transradial amputation. Single PMS pulses of varying amplitude were applied to the left arm locations overlying the median, radial, and ulnar nerves. Subjective accounts of sensations were collected using PerceptMapper, the University of Pittsburghs multitouch interface. After the best location for PMS was found, continuous stimulation (20 or 40 Hz, delivered in 5-min blocks with 5-7 min interblock intervals for patricipant breaks and EEG setup checks) was applied. The control participants reported experiencing sensations in their hands. The amputees felt sensations in their phantom hands. PMS evoked SEPs in both the controls and amputees. The analysis of intertrial coherence showed significant phase consistency of the stimulus-locked EEG responses across trials for the controls and amputees. The measurements of visual analogue scale (VAS) scale showed that PMS did not change PLP in 2 participants, increased it in 4, and decreased in 3. We propose that PMS could be used to assess the effects of peripheral nerve stimulation on somatic sensations, PLP and cortical activity prior to the surgical placement of electrode implants. Significance StatementPeople with amputation have two critical needs: (1) their prosthetic limbs being augmented with naturalistic somatic sensations, and (2) their PLP, which develops in the majority of cases, being suppressed. Electrical stimulation with peripheral nerve implants offers a solution for both needs, but invasiveness of this procedure poses a number of problems. Here we show that PMS offers a noninvasive tool for testing the effects of peripheral nerve stimulation before any invasive implants are placed. PMS causes somatic sensations, modulates PLP and evokes cortical responses evident in EEG recordings. These effects of PMS were documented in both healthy controls and amputees. The results suggest that PMS combined with EEG measurements could serve as tools for testing potential implantation sites.

Reward motivation is essential in shaping human behavior and cognition. Previous studies have shown altered reward motivation and reward brain circuitry in chronic pain conditions, including fibromyalgia. Fibromyalgia is a chronic disorder characterized by widespread musculoskeletal pain, fatigue, cognitive problems, and mood-related symptoms. In this study, we analyzed brain reward networks in patients with fibromyalgia by using a data-driven approach with task-based fMRI data. fMRI data from 24 patients with fibromyalgia and 24 healthy controls were acquired while subjects performed a monetary incentive delay (MID) reward task. Functional networks were derived using independent component analysis (ICA) focused on the gain anticipation phase of the reward task. Functional activity in the motor, value-driven attention, and basal ganglia networks was evaluated during gain anticipation in both patient and healthy control groups. Compared to controls, the motor network was more engaged during gain anticipation in patients with fibromyalgia. Our findings suggest that reward motivation may lead to hyperactivity in the motor network, possibly related to altered motor processing, such as restricted movement or dysregulated motor planning in fibromyalgia. As an exploratory analysis, we compared levels of motor network engagement during early and late timepoints of the gain anticipation phase. Both groups showed greater motor network engagement during the late timepoint (i.e., closer to response), which reflected motor preparation prior to target response. Importantly, compared to controls and consistent with the initial findings described above, patients exhibited greater engagement of the motor network during both early and late timepoints. In summary, by using a novel data-driven ICA approach to analyze task-based fMRI data, we identified elevated motor network engagement during gain anticipation in fibromyalgia.

Motor imagery is the ability to mentally simulate a motor task without actually performing it. Pain is an unpleasant sensory experience that involves different dimensions - sensory-discriminative, motivational-affective, and cognitive-evaluative - that are known to interfere with motor imagery. However, it remains unclear which specific pain dimension most significantly impairs motor imagery. This study aims to compare the effects of unpleasant auditory (primarily affective and cognitive) and thermal (primarily sensory) stimuli, which can be assimilated to pain, on discrete and continuous explicit motor imagery modalities. Eighteen healthy participants were exposed to unpleasant stimuli in addition to a control condition. Participants rated their motor imagery abilities after tasks involving rest, motor execution, and motor imagery in discrete and continuous wrist movement modalities. Results showed that during discrete motor imagery, only the aversive auditory stimulus significantly reduced motor imagery abilities, whereas thermal pain had no effect. In contrast, motor imagery abilities were preserved during the continuous modality. These findings suggest that explicit motor imagery may be more affected by the affective dimension of pain induced by aversive auditory stimuli. The preservation of motor imagery abilities in the continuous modality provides insight into the optimization of rehabilitation programs.

BackgroundIn neurophysiological pain studies, multiple types of calibration methods are used to quantify the individual pain sensation stimuli that have different modalities. However, such studies often lack calibration procedure implementation, have a vague protocol description, do not provide data quality quantification, or even omit required control for gender pain differences. All this hampers not only study repetition but also interexperimental comparisons. Moreover, typical calibration procedures are long and require a high number of stimulations which may cause participants discomfort and stimuli habituation. MethodTo overcome those shortcomings, we present an automatic staircase pain calibration method for A-delta-specific electrical stimulation adjusted to the magnetoencephalography environment. We provide an in-depth data analysis of the collected self-reports from seventy healthy volunteers (37 males) and propose a method based on a dynamic truncated linear regression model (tLRM). We compare its estimates for the sensation (t), and pain (T) thresholds, as well as for the mid-pain stimulation (MP), with those calculated using a traditional threshold method and standard linear regression models. ResultsCompared to the other threshold methods, tLRM exhibits higher R2 and requires 36% fewer stimuli application and has significantly higher t and lower T and MP intensities. Regarding sex differences, both lower t and T were found for females compared to males, regardless of the calibration method. ConclusionsThe proposed tLRM method quantifies the quality of the calibration procedure, minimizes its duration and invasiveness, as well as provides validation of linearity between stimuli intensity and subjective scores, making it an enabling technique for further studies. Moreover, our results highlight the importance of control for gender in pain studies. SummaryThe purpose of this study was to shorten and automatize the calibration method which is an enabling technique for realizing neurophysiological studies on pain. The proposed method is based on a dynamic truncated linear regression model and was shown to require 36% fewer stimuli application compared to the traditional staircase method. Furthermore, the calibration was adjusted to A-delta specific intraepidermal electrical stimulation, quantifies the quality of the resulting calibration parameters and provides a validation of linearity between stimuli intensity and subjective scores. The results also highlight the importance of control for participant gender in studies where different types of stimulation are used to induce pain sensation.

The cognitive mechanisms linking chronic pain to motivational symptoms remain poorly understood. We demonstrate that individuals with chronic temporomandibular disorder (TMD), a common cause of chronic pain, exhibit a specific deficit in adaptive learning in uncertain environments, characterized by failure to reduce uncertainty over time and maintain efficient learning rates. Using a probabilistic reward task, we pioneered the application of a novel volatile Kalman filter to model behavior in 26 TMD participants and 39 matched controls, uniquely tracking trial-wise updates in uncertainty, volatility, and learning rate. Although surface-level performance did not differ across groups, model-based analysis revealed that those with TMD failed to reduce uncertainty and adapt their learning over time. TMD participants also reported significantly greater apathy, depression, and pain catastrophizing, as well as lower health-related quality of life. Mediation analysis confirmed that impaired uncertainty adaptation partially mediated the relationship specifically between TMD and apathy. These findings identify a computational signature of disrupted uncertainty adaptation in people with TMD and provide evidence for a mechanistic link between chronic pain and motivational dysfunction. This work lays a foundation for future studies examining how belief-updating deficits contribute to broader affective and cognitive symptoms in chronic pain.

ObjectiveThis work utilises a novel high-speed robot-controlled stimulator to evaluate the effects of different levels of mechanical impulse (force and duration) of pinprick stimuli on neurophysiological responses and subjective perception. MethodsTwenty-seven healthy volunteers received pinprick stimuli on the right volar forearm using different combinations of force and duration that configured three distinct levels: low, medium and high mechanical impulse stimuli. The robotic system recorded stimulus force and duration in real time, and participants rated the pinprick perceived intensity on a numerical rating scale (NRS). The peak amplitudes and latencies of the pinprick evoked potentials (PEPs) were compared across stimulation levels. Perceived intensity ratings were analysed using linear mixed models, and the PEP features were evaluated through spatio-temporal cluster permutation tests. ResultsPerceived intensity ratings, expressed as median [IQR], were 2.5 [1.14 - 8.15] for low, 16.4 [ 8.86 - 26.9] for medium and 28.5 [10.2 - 41.4] for high impulse stimuli. Differences in brain activity were found when comparing across stimulation levels: the N2 Peak latency was longer for high impulse compared to low impulse and for medium impulse compared to low impulse. The P2 peak latency showed no differences across levels. The N2 amplitude was larger for high vs. low impulse and for medium vs. low impulse, with no significant difference observed between high and medium impulse stimulation. ConclusionsHigh speed robot-controlled pinprick stimulation successfully elicited pinprick-evoked potentials (PEPs) across different mechanical impulse levels. The use of robot-controlled systems may help standardize the assessment of mechanical nociception.

Dysregulated brain reward systems have been observed in chronic pain. Using functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task, Martucci et al. (2018) showed that neural responses to reward anticipation and outcome are altered in patients with fibromyalgia. The current study aimed to replicate these results in a separate cohort of patients with fibromyalgia recruited at a new location using a similar study design. Twenty patients with fibromyalgia and 20 healthy controls were included in the replication study. Group fMRI analyses revealed a solid and consistent trend of main findings similar to the previous results. Specifically, in the replication cohort of patients with fibromyalgia, medial prefrontal cortex (MPFC) activity was reduced during gain anticipation and increased during no-loss (non-punishment) outcomes, as compared to controls. Similar to the Martucci et al. results, again in the replication cohort, nucleus accumbens activity during gain anticipation did not differ in patients compared to controls. The same behavioral, correlational, and exploratory analyses that were conducted in the Martucci et al. study were conducted in the present replication study, with prior results largely replicated here. Thus, the present replication study results solidify observations of altered cortico-striatal processing to monetary rewards in chronic pain, which underscore relevance of altered brain reward circuits, particularly as related to the MPFC in patients with fibromyalgia.

BackgroundChronic pain affects 28 million UK adults. While physiotherapy and social prescribing are recognised as effective, evidence on integrating them remains limited. Digital biomarkers could objectively assess movement quality and pain physiology to support clinical decision-making. ObjectivesTo explore whether simple kinematic and electroencephalography (EEG) biomarkers can discriminate between correct versus incorrect exercise performance and high versus low pain states, and to consider how such tools might streamline social prescribing pathways for chronic pain. MethodsSecondary analyses of two open datasets: (1) KERAAL kinematic dataset: 900 recordings of trunk rotation exercises (21 participants) labelled "correct" or "incorrect" by physiotherapists; (2) EEG dataset: 145 resting-state recordings (100 individuals with chronic pain) categorised as high or low pain. Classification models (logistic regression, support vector machines, gradient boosting) were trained on extracted kinematic features (range of motion, smoothness, symmetry, jerk, coordination) and EEG features (frontal alpha asymmetry, connectivity, sample entropy, aperiodic exponents). Performance was assessed using accuracy, F1 score, AUC and calibration curves. ResultsKinematic classification achieved near-perfect performance: 100% accuracy and AUC = 1.00. Key features were shoulder abduction peak angle, symmetry index and jerk. EEG classification was strong: 93% accuracy, 0.97 AUC. Global theta and alpha connectivity, frontal alpha asymmetry and sample entropy were most informative. ConclusionAutomated kinematic and EEG markers can reliably differentiate correct exercise performance and current pain state. These digital biomarkers could inform physiotherapists and link workers when triaging patients into social prescribing programmes. Integrating digital assessment into social prescribing may reduce unnecessary appointments, enhance self-management and align care with the biopsychosocial model. Further studies should validate the approach in broader populations and examine implementation in real-world social prescribing services.

Fibromyalgia (FM) is a chronic condition marked by widespread pain, fatigue, sleep problems, cognitive decline, and other symptoms. Despite extensive research, the pathophysiology of FM remains poorly understood, complicating diagnosis and treatment, which often relies on self-report questionnaires. This study explored structural and functional brain changes in women with FM, identified potential biomarkers, and examined their relationship with FM severity. MRI data from 33 female FM patients and 33 matched healthy controls were utilized, focusing on T1-weighted MRI and resting-state fMRI scans. Functional connectivity (FC) analysis was performed using a machine learning framework to differentiate FM patients from healthy controls and predict FM symptom severity. No significant differences were found in brain structural features, such as gray matter volume, white matter volume, deformation-based morphometry, and cortical thickness. However, significant differences in FC were observed between FM patients and healthy controls, particularly in the default mode network (DMN), somatomotor network (SMN), visual network (VIS), and dorsal attention network (DAN). The FC metrics were significantly associated with FM severity. Our prediction model differentiated FM patients from healthy controls with an area under the curve of 0.65. FC measures accurately estimated FM symptom severities with a significant correlation (r = 0.45, p = 0.007). Functional connections in the DMN, VIS, and DAN were crucial in determining FM severity. These findings suggest that integrating brain FC measurements could serve as valuable biomarkers for early detection of FM and predicting FM symptom severity, improving diagnostic accuracy and facilitating the development of targeted therapeutic strategies.

Cognitive dysfunction is increasingly recognized as an important feature of chronic pain (CP). However, subjective cognitive complaints and objectively measured cognitive performance frequently diverge. Whether and how these two aspects of cognitive functioning differentially relate to the broad symptomatology and brain function in CP remains unclear. Here, 114 individuals with CP completed patient-reported outcome measures on cognitive functioning and multidimensional CP symptoms, as well as a visuospatial working memory task, and resting-state EEG. Bayesian correlations, network analyses, and Bayesian regression models examined how subjective and objective cognitive functioning relate to multidimensional CP symptoms and EEG activity/connectivity, while controlling for age and sex. Additional models tested whether EEG associations were independent of broader symptom burden. Results indicated that subjective and objective cognitive functioning were uncorrelated. Subjective cognitive functioning was strongly associated with psychosocial symptoms, whereas objective cognitive functioning was largely independent of broader symptom burden. EEG revealed associations between subjective cognitive functioning and bilateral frontotemporal beta connectivity; however, these relationships were substantially attenuated after accounting for broader CP symptom burden. Objective cognitive functioning showed no robust associations with EEG. These findings indicate a dissociation between subjective cognitive complaints and objective cognitive performance in CP. Subjective cognitive complaints were primarily associated with psychosocial symptom burden and beta-band hypoconnectivity. In contrast, objective cognitive performance was unrelated to the broader symptomatology of CP and EEG measures. This dissociation may inform more targeted interventions, optimize the allocation of cognitive assessment resources, and ultimately improve long-term functional outcomes in CP.

BackgroundPain with movement is common in adults with knee osteoarthritis (OA), but the effect of movement-evoked pain on gait is not well understood. This relationship is vital to understand as gait mechanics are associated with OA initiation and progression. Our current understanding of acute changes in pain and gait stems from extended bouts of walking, however these bouts likely dont represent real-world behavior. Therefore, understanding how gait changes with shorter, more intense bouts of activity may provide valuable insight into the pain experience. MethodsAdults with (n=19) and without (n=19) knee OA wore inertial measurement units (IMUs) while completing bouts of walking before and after two bouts of stair navigation (two flights). We tested whether pain and gait (speed, stride length, and lower extremity joint ranges of motion (ROM)) changed differently between adults with and without knee OA in response to multiple bouts of stair activity. FindingsThere were no significant interactions between group and stair bouts for any variable. When stratifying the OA group by those who did and did not experience pain, those who experienced a change in pain also had a greater change in early stance knee ROM in response to bouts of stairs. InterpretationThe observed changes suggest that knee kinematics may be more sensitive to acute changes in pain than gait speed or stride length. These differences were detectable using IMUs and therefore our results support the use of IMUs to measure concurrent pain and gait mechanics in less controlled and real-world settings.

ObjectiveAdults with knee osteoarthritis often experience movement-evoked pain (MEP), and that pain has the potential to alter gait mechanics and influence disease progression. However, the associations between MEP and gait biomechanics have only been assessed in typical lab settings. Gait mechanics differ in the lab compared to in the real-world, thus it is unknown whether these associations between pain and gait translate to real-world settings. Therefore, this study aimed to measure concurrent changes in MEP and gait mechanics across three days of typical real-world activity. DesignSeventeen participants with self-reported physician-diagnosed symptomatic knee osteoarthritis wore inertial measurement units on their more symptomatic limbs thigh and shank, as well as on both feet for three days of typical activity. Participants were sent 5 automated text messages a day and were instructed to complete a short 3-5 minute walk and self-report their MEP via a Numeric Rating Scale (0-10) during each of the walks. A random coefficients model was used to determine how gait speed, stride length, and knee and ankle range of motion was related to changes in pain intensity. ResultsThe average MEP experienced during the instructed walks was 1.4 {+/-} 1.3 with individual participant average pain intensities ranging from 0 to 4.8. Greater MEP was associated with a 2.7{degrees} decrease in knee range of motion per unit increase in pain (95% CI [-4.8 -0.5], p = 0.02). Seven of the seventeen participants never reported a pain level of 0. Speed, stride length, and ankle range of motion did not differ by pain intensity. ConclusionsIncreases in MEP were associated with decreases in knee range of motion. A 2.7{degrees} decrease in knee range of motion in response to a 1-unit change in pain is meaningful as 5{degrees} is generally considered the threshold for a meaningful difference in joint angles. With a change in pain intensity of 2 being common with daily activity, individuals may be experiencing meaningful changes in knee joint angles regularly. With gait mechanics being associated with disease progression, these daily acute fluctuations in pain may be influencing disease progression rates.

Embodied interoception refers to the perception of the bodys state and is a multidimensional cognitive process. It is proposed that the experience of pain also feeds interoceptive networks with information from the state of the body, and the subjective experience of pain would be influenced by an individuals trait embodied interoceptive profile. Here we developed and validated the Intero-10, a questionnaire designed to specifically evaluate embodied interoception based on trait interoceptive channels. Healthy adults (n=381) and people with neuropathic pain (n=86) were enrolled. The relationship between trait and state interoceptive responses was examined during experimentally evoked interoceptive psychophysics tasks, which were specific for each interoceptive channel. During these tests, embodied interoceptive state scores only correlated with trait ones for unpleasantness (P<0.05), but not for intensity rating, suggesting that the predicted negative valence of lived experience provided lower prediction errors than intensity estimations. The Intero-10 final version included embodied interoceptive perception intensity (heartbeat, heat, itching, dyspnea, sleep, muscle fatigue, and anguish) and unpleasantness (heartbeat, dyspnea, and nausea) categories. Intero-10 demonstrated adequate content validity, good internal consistency (Cronbachs alpha=0.81), good reliability (>0.75), and a single-factor structure. Patients with neuropathic pain filled in the Intero-10 alongside traditional pain, mood, sleep, and quality of life assessments. Embodied interoception scores correlated with mood, and quality of life, and partially mediated the correlation between pain interference and quality of life ({beta}=-0.0093). The specific assessment of embodied interoceptive channels may broaden our current assessment of people with chronic pain and of those at risk to develop it.

ObjectivePhantom limb pain (PLP) is debilitating and affects over 70% of people with lower-limb amputation. Other neuropathic pain conditions correspond with increased spinal excitability, which can be measured using reflexes and F-waves. Spinal cord neuromodulation can be used to reduce neuropathic pain in a variety of conditions and may affect spinal excitability, but has not been extensively used for treating phantom limb pain. Here, we propose using a non-invasive neuromodulation method, transcutaneous spinal cord stimulation (tSCS), to reduce PLP and modulate spinal excitability after transtibial amputation. ApproachWe recruited three participants, two males (5- and 9-years post-amputation, traumatic and alcohol-induced neuropathy) and one female (3 months post-amputation, diabetic neuropathy) for this 5-day study. We measured pain using the McGill Pain Questionnaire, visual analog scale, and pain pressure threshold test. We measured spinal reflex and motoneuron excitability using posterior root-muscle (PRM) reflexes and F-waves, respectively. We delivered tSCS for 30 minutes/day for 5 days. Main ResultsAfter 5 days of tSCS, pain scores decreased by clinically-meaningful amounts for all participants from 34.0{+/-}7.0 to 18.3{+/-}6.8. Two participants had increased pain pressure thresholds across the residual limb (Day 1: 5.4{+/-}1.6 lbf; Day 5: 11.4{+/-}1.0 lbf). F-waves had normal latencies but small amplitudes. PRM reflexes had high thresholds (59.5{+/-}6.1 {micro}C) and low amplitudes, suggesting that in PLP, the spinal cord is hypoexcitable. After 5 days of tSCS, reflex thresholds decreased significantly (38.6{+/-}12.2 {micro}C; p<0.001). SignificanceOverall, limb amputation and PLP may be associated with reduced spinal excitability and tSCS can increase spinal excitability and reduce PLP.

Chronic pain (CP) is a multidimensional condition characterized by physical, emotional, and cognitive symptoms. However, many neuroimaging studies investigating the brain mechanisms of CP have focused on single-domain measures, most commonly pain intensity. Incorporating multidimensional symptom profiles may advance the understanding of CP, its neural underpinnings, and the development of clinically actionable biomarkers. Here, we aimed to empirically derive symptom dimensions of CP and relate them to resting-state brain activity and connectivity measured by electroencephalography (EEG). Using a data-driven approach, we identified latent symptom dimensions in 207 individuals with CP based on the brief, internationally validated PROMIS-29 profile, which assesses general health across key physical, mental, and social domains. Principal component analysis revealed two dimensions, affective burden and physical burden, closely corresponding to established PROMIS-derived health dimensions in other clinical populations. Resting-state EEG was obtained in a subsample of 116 participants using a mobile, rapid-to-deploy 29-channel dry-electrode system. Bayesian regression analyses provided moderate to strong evidence for a negative association between affective burden and beta-band connectivity, particularly in left frontal and somatomotor regions. Together, these findings demonstrate how empirically derived symptom dimensions captured by PROMIS-29 can be linked to scalable, network-level EEG biomarkers. This framework illustrates an EEG-informed strategy for biopsychosocial stratification in CP, with potential relevance for personalized symptom-targeted interventions.

Previous research has demonstrated the importance of the corticostriatal circuit in chronic pain. By focusing on nucleus accumbens (NAcc) circuits related to reward, we aimed to clarify how altered brain reward systems contribute to chronic pain. Using resting-state functional magnetic resonance imaging, we compared NAcc-medial prefrontal cortex (MPFC) functional connectivity in patients with fibromyalgia vs. healthy controls. Among patients, we analyzed the extent to which functional connectivity correlated with clinical measures. We also examined NAcc functional connectivity to subcortical regions. Lastly, we compared our results to a separate dataset of patients with chronic back pain. We identified robust NAcc-MPFC functional connectivity among patients with fibromyalgia and healthy controls, with no significant group differences. We found a positive correlational trend between NAcc-MPFC functional connectivity and total mood disturbance. Notably, patients with fibromyalgia showed significantly reduced functional connectivity of the right NAcc with mesolimbic circuit regions compared to controls. These results were largely similar to the results from the separate dataset. Our results provide novel evidence of intact corticostriatal but altered subcortical functional connectivity of the NAcc during resting-state in chronic pain and suggest that measured connectivity may relate to changes in mood and the level of cognitive demand during fMRI-based measurement. PerspectiveThis article indicates complex brain valuation system alterations associated with chronic pain. Our findings expand our understanding of the valuation system and its relationship to clinical presentation in patients with fibromyalgia.

BackgroundFibromyalgia is a prevalent chronic pain condition characterized by widespread pain and sensory hypersensitivity. While much remains unknown about fibromyalgias neurobiological underpinnings, central nervous system alterations appear to be heavily implicated in its pathophysiology. Previous research examining brain structural abnormalities associated with fibromyalgia has yielded inconsistent findings. Thus, we followed previous methods to examine brain gray matter differences in fibromyalgia. We hypothesized that, relative to healthy controls, participants with fibromyalgia would exhibit lower gray matter volume in regions consistently implicated in fibromyalgia: the anterior cingulate cortex and medial prefrontal cortex. MethodsThis study used magnetic resonance imaging to evaluate regional and whole brain differences in gray matter among females with and without fibromyalgia. Group differences were analyzed with two-sample t-tests, controlling for total intracranial volume. ResultsNo significant differences in regional or whole brain gray matter volumes were detected between fibromyalgia and healthy controls. ConclusionsResults add to an existing body of disparate findings regarding brain gray matter volume differences in fibromyalgia, and suggest structural differences previously detected in fibromyalgia should be examined for reproducibility. Absent significant differences may also suggest that functional, but not structural, brain adaptations are primarily associated with fibromyalgia.

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions of dollars annually. Despite the tremendous impact of chronic pain globally, the standard of care for diagnosis depends on subjective self-reporting of pain state, with no objective assessment procedure available. This study investigated the application of signal processing and machine learning to electroencephalography (EEG) data for the development of classification algorithms capable of differentiating subjects with diverse chronic pain etiologies from pain-free subjects. The study population included participants experiencing various types of chronic pain, including nociceptive, neuropathic, and mixed etiological pain conditions. Chronic pain diagnoses were based on clinical evaluation by participating physicians and adhered to the International Association for the Study of Pain (IASP) definition, requiring pain persistence for >3 months and associated functional impairment or emotional distress. Data from 186 participants were used for algorithm development, including 35 healthy controls and 151 chronic pain patients. Machine learning methodologies were applied to the data, with Elastic Net chosen as the optimal methodology.. The classifier was able to differentiate pain versus no pain subjects with an accuracy of 79.6%, sensitivity of 82.2%, and specificity of 66.7%. This study incorporates the multidimensional nature of chronic pain, ensuring that our methods and interpretations align with current clinical and research standards. This study represents a step toward integrating EEG-based biomarkers into clinical workflows for chronic pain assessment, bridging the gap between subjective reporting and objective diagnostic tools.