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Previous studies have established the role of the cortico-mesolimbic and descending pain modulation systems in chronic pain prediction. Mild traumatic brain injury (mTBI) is an acute pain model where chronic pain is prevalent and complicated for prediction. In this study, we set out to study whether functional connectivity (FC) of the nucleus accumbens (NAc) and the periaqueductal gray matter (PAG) is predictive of pain chronification in early-acute mTBI.To estimate FC, resting-state functional magnetic resonance imaging (fMRI) of 105 participants with mTBI following a motor vehicle collision was acquired within 72 hours post-accident. Participants were classified according to pain ratings provided at 12-months post-collision into chronic pain (head/neck pain ≥30/100, n = 44) and recovery (n = 61) groups, and their FC maps were compared.The chronic pain group exhibited reduced negative FC between NAc and a region within the primary motor cortex corresponding with the expected representation of the area of injury. A complementary pattern was also demonstrated between PAG and the primary somatosensory cortex. PAG and NAc also shared increased FC to the rostral anterior cingulate cortex (rACC) within the recovery group. Brain connectivity further shows high classification accuracy (area under the curve [AUC] = .86) for future chronic pain, when combined with an acute pain intensity report.FC features obtained shortly after mTBI predict its transition to long-term chronic pain, and may reflect an underlying interaction of injury-related primary sensorimotor cortical areas with the mesolimbic and pain modulation systems. Our findings indicate a potential predictive biomarker and highlight targets for future early preventive interventions. ANN NEUROL 2022;92:819-833.

Chronic pain is a leading cause of disability worldwide and its prevalence is likely to increase over the next decades. Treatment for chronic pain remains insufficient and therapeutical advances have not made comparable progress with that for many chronic disorders, thus amplifying the concern on the future burden of the disease. At the same time, and even after decades of intense research, the underlying pathophysiology of chronic pain remains minimally understood. We believe advancing our current understanding of chronic pain requires mechanistically explicit, hypothesis-driven, and clinically focused models. In this review we highlight some of the main findings over the last decades that have contributed to the present knowledge of brain mechanisms of chronic pain, and how such advances were possible due to a reverse translational research approach. We argue that this approach is essential in the chronic pain field, in order to generate new scientific hypotheses, probe physiological mechanisms, develop therapeutic strategies and translate findings back into promising human clinical trials.

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site - namely conditioned pain modulation and magnitude of suprathreshold pain-, and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white-matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

We used a recently advanced technique, morphometric similarity (MS), in a large sample of lumbar disc herniation patients with chronic pain (LDH-CP) to examine morphometric features derived from multimodal MRI data. To do so, we evenly allocated 136 LDH-CPs to exploratory and validation groups with matched healthy controls (HC), randomly chosen from the pool of 157 HCs. We developed three MS-based models to discriminate LDH-CPs from HCs and to predict the pain intensity of LDH-CPs. In addition, we created analogous models using resting state functional connectivity (FC) to perform the above discrimination and prediction of pain, in addition to comparing the performance of FC- and MS-based models and investigating if an ensemble model, combining morphometric features and resting-state signals, could improve performance. We conclude that 1) MS-based models were able to discriminate LDH-CPs from HCs and the MS networks (MSN) model performed best; 2) MSN was able to predict the pain intensity of LDH-CPs; 3) FC networks constructed were able to discriminate LDH-CPs from HCs, but they could not predict pain intensity; and 4) the ensemble model neither improved discrimination nor pain prediction performance. Generally, MSN is sensitive enough to uncover brain morphology alterations associated with chronic pain and provides novel insights regarding the neuropathology of chronic pain.

We studied the behavioral consequences of fentanyl vapor self-administration (SA) in mice with and without chronic neuropathic pain (one month after spared-nerve injury(SNI) model or sham injury). We assessed fentanyl consumption, motivation, and seeking during as well as anxiety, hyperactivity, immobility, and pain for two regimens of fentanyl SA: 1) Dose escalation, where over a 3-week period mice are exposed (daily 2-hour sessions) to escalating numbers of fentanyl puffs per active nosepoke (from 1 puff/active nosepoke for first 3 days, up to 6 puffs/active nosepoke in days 16-18). 2) Effort escalation, where over a 3-week period (daily 2-hour sessions) mice need to increase effort to acquire the same amount of fentanyl (fixed ratio 1 (FR) = 1 active nosepoke results in 1 fentanyl puff, while second and third week we use FR5 and FR10). We observe sex-, injury- and regimen-dependent differences in outcomes. Importantly the dose escalation regimen resulted in higher seeking behavior (post forced abstinence, context and cue driven nosepoking in the absence of fentanyl delivery), long lasting increased anxiety, immobility, and hyperactivity, as well as transient but full pain relief in SNI mice. Therefore, this regimen seems a better rodent model for translating outcomes to human chronic pain patients managed with opioids.

SummaryHow does the human brain generate coherent, subjective perceptions—transforming yellow and oblong visual sensory information into the perception of an edible banana1? This is a hard problem. The standard viewpoint posits that anatomical and functional networks integrate local, specialized processing across the brain to somehow construct unique percepts. Here, we provide evidence for a novel organizational concept by uncovering task-specific information distributed across the human brain. First, we show that functional magnetic resonance imaging (fMRI) can uncover task-specific information throughout the neocortex, even across voxels traditionally discarded as “noise” (t-statistics ≈ 0), challenging the sensitivity of traditional linear, univariate analytical approaches. Remarkably, task-specific signals could also be uncovered from across-subject variances and were ubiquitous even in the subcortex and cerebellum. Finally, we show that the widespread signal in regions remote from a task’s primary and secondary sensory cortices depends on the level of sedation, suggesting it is related to perception†rather than sensory stimulus encoding. We hypothesize that these widespread, task-specific, and consciousness level-dependent signals may be the basis for coherent, subjective perceptions.

A workshop was sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases to focus on research gaps and opportunities in pancreatic pain. The event was held on July 21, 2021, and structured into 4 sessions: (1) pathophysiology; (2) biomarkers, mediators, and pharmacology of pain; (3) pain assessment; and (4) pain treatment challenges and opportunities. The current state of knowledge was reviewed; many knowledge gaps and research needs were identified that require further investigation. Common themes included the need to better understand the underlying mechanisms of pain in pancreatic diseases, the relationship of visceral neural pathways and central pain centers, the role of behavioral factors and disorders on the perception of pain, and differences in pain perception and processes in children when compared with adults. In addition, the role of genetic risk factors for pain and the mechanisms and role of placebos in pain treatment were discussed. Methods of pain assessment including quantitative sensory testing were examined, as well as the process of central sensitization of pain. Finally, newer approaches to pain management including cognitive behavioral therapy, nerve stimulation, experimental (nonopioid) drugs, and cannabinoid compounds were covered.

Supplemental Digital Content is Available in the Text. Pharmacological, optogenetic, and chemogenetic modulation of neuronal excitability of the dorsal, but not the ventral, hippocampus induces analgesia in rodent models of neuropathic pain., Accumulating evidence suggests hippocampal impairment under the chronic pain phenotype. However, it is unknown whether neuropathic behaviors are related to dysfunction of the hippocampal circuitry. Here, we enhanced hippocampal activity by pharmacological, optogenetic, and chemogenetic techniques to determine hippocampal influence on neuropathic pain behaviors. We found that excitation of the dorsal (DH), but not the ventral (VH) hippocampus induces analgesia in 2 rodent models of neuropathic pain (SNI and SNL) and in rats and mice. Optogenetic and pharmacological manipulations of DH neurons demonstrated that DH-induced analgesia was mediated by N-Methyl-D-aspartate and μ-opioid receptors. In addition to analgesia, optogenetic stimulation of the DH in SNI mice also resulted in enhanced real-time conditioned place preference for the chamber where the DH was activated, a finding consistent with pain relief. Similar manipulations in the VH were ineffective. Using chemo-functional magnetic resonance imaging (fMRI), where awake resting-state fMRI was combined with viral vector-mediated chemogenetic activation (PSAM/PSEM89s) of DH neurons, we demonstrated changes of functional connectivity between the DH and thalamus and somatosensory regions that tracked the extent of relief from tactile allodynia. Moreover, we examined hippocampal functional connectivity in humans and observe differential reorganization of its anterior and posterior subdivisions between subacute and chronic back pain. Altogether, these results imply that downregulation of the DH circuitry during chronic neuropathic pain aggravates pain-related behaviors. Conversely, activation of the DH reverses pain-related behaviors through local excitatory and opioidergic mechanisms affecting DH functional connectivity. Thus, this study exhibits a novel causal role for the DH but not the VH in controlling neuropathic pain–related behaviors.

Although placebo effect sizes in clinical trials of chronic pain treatments have been increasing, it remains unknown if characteristics of individuals' thoughts or prior experiences can reliably infer placebo pill responses. Research using language to investigate emotional and cognitive processes has recently gained momentum. Here, we quantified placebo response in chronic low back pain using over 300 semantic and psycholinguistic features derived from patients' language. This speech content was collected in an exit interview as part of a clinical trial investigating placebo analgesia (62 patients, 42 treated; 20 not treated). Utilizing a nested leave-one-out cross-validated approach, we distinguished placebo responders from non-responders with 79% accuracy using language features alone; a subset of these features - semantic distances to identity and stigma and the number of achievement-related words - also explained 46% of the variance in placebo analgesia. Importantly, these language features were not due to generic treatment effects and were associated with patients' specific baseline psychological traits previously shown to be predictive of placebo including awareness and personality characteristics, explaining an additional 31% of the variance in placebo analgesia beyond that of personality. Initial interpretation of the features suggests that placebo responders differed in how they talked about negative emotions and the extent that they expressed awareness to various aspects of their experiences; differences were also seen in time spent talking about leisure activities. These results indicate that patients' language is sufficient to identify placebo response and implies that specific speech features may be predictive of responders prior to treatment.

The autonomic nervous system governs the body's multifaceted internal adaptation to diverse changes in the external environment, a role more complex than is accessible to the methods—and data scales—hitherto used to illuminate its operation. Here we apply generative graphical modelling to large-scale multimodal neuroimaging data encompassing normal and abnormal states to derive a comprehensive hierarchical representation of the autonomic brain. We demonstrate that whereas conventional structural and functional maps identify regions jointly modulated by parasympathetic and sympathetic systems, only graphical analysis discriminates between them, revealing the cardinal roles of the autonomic system to be mediated by high-level distributed interactions. We provide a novel representation of the autonomic system—a multidimensional, generative network—that renders its richness tractable within future models of its function in health and disease.

The objective of this study is to validate a placebo pill response predictive model-a biosignature-that classifies chronic pain patients into placebo responders (predicted-PTxResp) and nonresponders (predicted-PTxNonR) and test whether it can dissociate placebo and active treatment responses. The model, based on psychological and brain functional connectivity, was derived in our previous study and blindly applied to current trial participants. Ninety-four chronic low back pain (CLBP) patients were classified into predicted-PTxResp or predicted-PTxNonR and randomized into no treatment, placebo treatment, or naproxen treatment. To monitor analgesia, back pain intensity was collected twice a day: 3 weeks baseline, 6 weeks of treatment, and 3 weeks of washout. Eighty-nine CLBP patients were included in the intent-to-treat analyses and 77 CLBP patients in the per-protocol analyses. Both analyses showed similar results. At the group level, the predictive model performed remarkably well, dissociating the separate effect sizes of pure placebo response and pure active treatment response and demonstrating that these effects interacted additively. Pain relief was about 15% stronger in the predicted-PTxResp compared with the predicted-PTxNonR receiving either placebo or naproxen, and the predicted-PTxNonR successfully isolated the active drug effect. At a single subject level, the biosignature better predicted placebo nonresponders, with poor accuracy. One component of the biosignature (dorsolateral prefrontal cortex-precentral gyrus functional connectivity) could be generalized across 3 placebo studies and in 2 different cohorts-CLBP and osteoarthritis pain patients. This study shows that a biosignature can predict placebo response at a group level in the setting of a randomized controlled trial.

Head motion is a major confounding factor impairing the quality of functional magnetic resonance imaging (fMRI) data. In particular, head motion can reduce analytical efficiency, and its effects are still present even after preprocessing. To examine the validity of motion removal and to evaluate the remaining effects of motion on the quality of the preprocessed fMRI data, a new metric of group quality control (QC), dissimilarity of functional connectivity, is introduced. Here, we investigate the association between head motion, represented by mean framewise displacement, and dissimilarity of functional connectivity by applying four preprocessing methods in two independent resting‐state fMRI datasets: one consisting of healthy participants (N = 167) scanned in a 3T GE‐Discovery 750 with longer TR (2.5 s), and the other of chronic back pain patients (N = 143) in a 3T Siemens Magnetom Prisma scanner with shorter TR (0.555 s). We found that dissimilarity of functional connectivity uncovers the influence of participant's motion, and this relationship is independent of population, scanner, and preprocessing method. The association between motion and dissimilarity of functional connectivity, and how the removal of high‐motion participants affects this association, is a new strategy for group‐level QC following preprocessing., Dissimilarity of functional connectivity uncovers the influence of participant's motion, and this relationship is independent of population, scanner, and preprocessing method. Participants with the greatest motion determined the strength of the association between motion and dissimilarity of functional connectivity. A new group‐based quality control strategy is proposed: if a group data set is large enough, participants with large motion in the data set be removed to make the regression slope of the association as flat as possible.

The interaction between osteoarthritis (OA) pain and brain properties remains minimally understood, although anatomical and functional neuroimaging studies suggest that OA, similar to other chronic pain conditions, may impact as well as partly be determined by brain properties. Here, we studied brain gray matter (GM) properties in OA patients scheduled to undergo total joint replacement surgery. We tested the hypothesis that brain regional GM volume is distinct between hip OA (HOA) and knee OA (KOA) patients, relative to healthy controls and moreover, that these properties are related to OA pain. Voxel-based morphometry group contrasts showed lower anterior cingulate GM volume only in HOA. When we reoriented the brains (flipped) to examine the hemisphere contralateral to OA pain, precentral GM volume was lower in KOA and HOA, and 5 additional brain regions showed distortions between groups. These GM changes, however, did not reflect clinical parameters. Next, we subdivided the brain into larger regions, approximating Brodmann areas, and performed univariable and machine learning-based multivariable contrasts. The univariable analyses approximated voxel-based morphometry results. Our multivariable model distinguished between KOA and controls, was validated in a KOA hold-out sample, and generalized to HOA. The multivariable model in KOA, but not HOA, was related to neuropathic OA pain. These results were mapped into term space (using Neurosynth), providing a meta-analytic summary of brain anatomical distortions in OA. Our results indicate more subtle cortical anatomical differences in OA than previously reported and also emphasize the interaction between OA pain, namely its neuropathic component, and OA brain anatomy.

The positive or negative value (valence) of past experiences is normally integrated into neuronal circuits that encode episodic memories and plays an important role in guiding behavior. Here, we show, using mouse behavioral models, that glutamatergic afferents from the ventral tegmental area to the dorsal hippocampus (VTA→DH) signal negative valence to memory circuits, leading to the formation of fear-inducing context memories and to context-specific reinstatement of fear. To a lesser extent, these projections also contributed to opioid-induced place preference, suggesting a role in signaling positive valence as well, and thus a lack of dedicated polarity. Manipulations of VTA terminal activity were more effective in females and paralleled by sex differences in glutamatergic signaling. By prioritizing retrieval of negative and positive over neutral memories, the VTA→DH circuit can facilitate the selection of adaptive behaviors when current and past experiences are valence congruent., The neuronal pathway that signals the positive or negative value of memories is not well understood. Here, the authors report that an excitatory projection from the ventral tegmental area to the dorsal hippocampus carries the valence information, contributing, especially in females, to the recurrence of fear and to drug seeking behavior.

Patients with chronic pain show large placebo effects in clinical trials, and inert pills can lead to clinically meaningful analgesia that can last from days to weeks. Whether the placebo response can be predicted reliably, and how to best predict it, is still unknown. We have shown previously that placebo responders can be identified through the language content of patients because they speak about their life, and their pain, after a placebo treatment. In this study, we examine whether these language properties are present before placebo treatment and are thus predictive of placebo response and whether a placebo prediction model can also dissociate between placebo and drug responders. We report the fine-tuning of a language model built based on a longitudinal treatment study where patients with chronic back pain received a placebo (study 1) and its validation on an independent study where patients received a placebo or drug (study 2). A model built on language features from an exit interview from study 1 was able to predict, a priori, the placebo response of patients in study 2 (area under the curve = 0.71). Furthermore, the model predicted as placebo responders exhibited an average of 30% pain relief from an inert pill, compared with 3% for those predicted as nonresponders. The model was not able to predict who responded to naproxen nor spontaneous recovery in a no-treatment arm, suggesting specificity of the prediction to placebo. Taken together, our initial findings suggest that placebo response is predictable using ecological and quick measures such as language use.

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 172 patients with mTBI, following a motorized vehicle collision and used a machine learning approach to extract white matter structural and resting state fMRI functional connectivity measures to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site – namely conditioned pain modulation and magnitude of suprathreshold pain–, and with pain sensitivity questionnaire scores. Our validated findings demonstrate a stable white-matter network, the properties of which determine a significant amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

Following surgical repair after peripheral nerve injury, neuropathic pain diminishes in most patients but can persist in a small proportion of cases, the mechanism of which remains poorly understood. Based on the spared nerve injury (SNI), we developed a rat nerve repair (NR) model, where a delayed reconstruction of the SNI-injured nerves resulted in alleviating chronic pain-like behavior only in a subpopulation of rats. Multiple behavioral measures were assayed over 11-week presurgery and postsurgery periods (tactile allodynia, pain prick responses, sucrose preference, motor coordination, and cold allodynia) in SNI (n = 10), sham (n = 8), and NR (n = 12) rats. All rats also underwent resting-state functional magnetic resonance imaging under anesthesia at multiple time points postsurgery, and at 10 weeks, histology and retrograde labeling were used to calculate peripheral reinnervation. Behavioral measures indicated that at approximately 5 weeks postsurgery, the NR group separated to pain persisting (NR persisting, n = 5) and recovering (NR recovering, n = 7) groups. Counts of afferent nerves and dorsal root ganglion cells were not different between NR groups. Therefore, NR group differences could not be explained by peripheral reorganization. By contrast, large brain functional connectivity differences were observed between NR groups, where corticolimbic reorganization paralleled with pain recovery (repeated-measures analysis of variance, false discovery rate, P0.05), and functional connectivity between accumbens and medial frontal cortex was related both to tactile allodynia (nociception) and to sucrose preference (anhedonia) in the NR group. Our study highlights the importance of brain circuitry in the reversal of neuropathic pain as a natural pain-relieving mechanism. Further studies regarding the therapeutic potentials of these processes are warranted.

Brain functional network properties are globally disrupted in multiple musculoskeletal chronic pain conditions. Back pain with lumbar disk herniation (LDH) is highly prevalent and a major route for progression to chronic back pain. However, brain functional network properties remain unknown in such patients. Here, we examined resting-state functional magnetic resonance imaging-based functional connectivity networks in chronic back pain patients with clear evidence for LDH (LDH-chronic pain n = 146), in comparison to healthy controls (HCs, n = 165). The study was conducted in China, thus providing the opportunity to also examine the influence of culture on brain functional reorganization with chronic pain. The data were equally subdivided into discovery and validation subgroups (n = 68 LDH-chronic pain and n = 68 HC, for each subgroup), and contrasted to an off-site data set (n = 272, NITRC 1000). Graph disruption indices derived from 3 network topological measurements, degree, clustering coefficient, and efficiency, which respectively represent network hubness, segregation, and integration, were significantly decreased compared with HC, across all predefined link densities, in both discovery and validation groups. However, global mean clustering coefficient and betweenness centrality were decreased in the discovery group and showed trend in the validation group. The relationship between pain and graph disruption indices was limited to males with high education. These results deviate somewhat from recent similar analysis for other musculoskeletal chronic pain conditions, yet we cannot determine whether the differences are due to types of pain or also to cultural differences between patients studied in China and the United States.

Background Preventing transition to chronic back pain (CBP) is a long-sought strategy that could rescue patients from prolonged suffering. Recent rodent and human brain imaging studies suggest involvement of sexually dimorphic, dopaminergic-motivational, mesolimbic circuits in the transition to chronic pain (tCBP), and hint that the combination of carbidopa/levodopa and naproxen (LDP + NPX) may block tCBP. Here we evaluated, in people with recent-onset back pain, whether a 3-month treatment with LDP + NPX is safe, blocks tCBP, and whether its efficacy is sex-dependent. Methods A total of 72 participants were enrolled and stratified by risk for tCBP using brain-imaging biomarkers. Low-risk participants entered a no-treatment arm. Others were randomized to placebo + naproxen or LDP + NPX for 3 months. Results Both treatments resulted in more than 50% pain relief for approximately 75% of participants. A strong sex by treatment interaction was observed for daily pain intensity (phone NRS, P = 0.007), replicated on 4-week average pain (Pain/4w, P = 0.00001), and in intent-to-treat analysis (Pain/4w, P = 0.000004). Nucleus accumbens functional connectivity with medial prefrontal cortex, a predefined objective biomarker, showed sex dependence at baseline (P = 0.03) and sex-by-treatment interaction effect 3 months after treatment cessation (P = 0.031). Treatment modified the psychological profile of participants, and disrupted brain modeling-based predicted back pain intensity trajectories. Forty participants were queried 3.3 years from trial start; back pain ratings were similar between end of treatment and at 3.3 years (P = 0.62), indicating persistence of relief for this duration. Conclusions These results provide the first evidence for preventing transition to chronic back pain using sex-specific pharmacotherapy. These provocative observations require confirmation in a larger study. ClinicalTrials.gov identifier: NCT01951105. Supplementary Information The online version contains supplementary material available at 10.1007/s40122-021-00297-2.

Both pain rating and exponential model revealed that percutaneous endoscopic lumbar discectomy provided rapid pain recovery that was maintained for at least 3 months compared with conservative treatments., Introduction: Lumbar disc herniation (LDH) is a common back disorder that evokes back and/or leg pain. Percutaneous endoscopic lumbar discectomy (PELD) is a minimally invasive surgery for patients with LDH. However, there is little evidence of effectiveness of PELD compared with conservative treatments. Objective: The goal of this study was to quantify the efficacy of PELD compared with conservative treatments. Methods: Here, we conducted a prospective observational cohort study using momentary pain assessments via a smartphone app during 3 months following surgery. The trajectories of daily ecological momentary pain assessments were fitted with an exponential model containing two parameters: a pain reduction coefficient and the percentage of persistent pain. To control for selection bias between PELD and Conservative groups (N = 167 and 34), we used inverse probability (IP) of treatment weighting for statistical comparisons. Results: Compared with conservative treatments, both momentary pain rating and the exponential model showed statistically significant pain recovery following PELD (p < 0.001). In addition, PELD had a faster pain recovery rate (hazard ratio (95% confidence interval): 1.75 (1.40, 2.20), p < 0.001), greater overall pain recovery rate (odds ratio (95%CI): 2.35 (2.01, 5.26), p < 0.001), faster pain reduction (t199 = 3.32, p = 0.001), and lower estimated persistent pain (Z = 2.53, p = 0.011). Greater pain intensity and lower anxiety before the surgery were predictors of faster pain reduction in the recovery subgroup following PELD. Conclusions: In conclusion, momentary pain rating and the model fitting revealed that PELD provided rapid pain recovery that lasted for at least three months. Greater pain intensity and lower anxiety before the surgery were predictors of faster pain reduction in the recovery subgroup following PELD. Daily momentary pain rating on a smartphone may be able to provide more informative data to evaluate effect of an intervention than pain assessment on hospital visits.

Osteoarthritis (OA) manifests with chronic pain, motor impairment, and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in a large sample of knee and hip OA (KOA, n = 91; HOA, n = 23) patients. We used a robust validation strategy by subdividing the KOA data into discovery and testing groups and tested the generalizability of our findings in HOA. Despite brain global topological properties being conserved in OA, we show there is a network wide pattern of reorganization that can be captured at the subject‐level by a single measure, the hub disruption index. We localized reorganization patterns and uncovered a shift in the hierarchy of network hubs in OA: primary sensory and motor regions and parahippocampal gyrus behave as hubs and insular cortex loses its central placement. At an intermediate level of network structure, frontoparietal and cingulo‐opercular modules showed preferential reorganization. We examined the association between network properties and clinical correlates: global disruption indices and isolated degree properties did not reflect clinical parameters; however, by modeling whole brain nodal degree properties, we identified a distributed set of regions that reliably predicted pain intensity in KOA and generalized to hip OA. Together, our findings reveal that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions, challenging the extent of dependence of OA pain on nociceptive signaling., Osteoarthritis (OA) manifests with chronic pain, motor impairment and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in knee and hip OA. We show that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions found:insula/M1/S1/parahippocampus; challenging the extent of dependence of OA pain on nociceptive signaling.

SUMMARYHigh-profile studies claim to assess mental states across individuals using multi-voxel decoders of brain activity. The fixed, fine-grained, multi-voxel patterns in these “optimized” decoders are purportedly necessary for discriminating between, and accurately identifying, mental states. Here, we present compelling evidence that the efficacy of these decoders is overstated. Across a variety of tasks, decoder patterns were not necessary. Not only were “optimized decoders” spatially imprecise and 90% redundant, but they also performed similarly to simpler decoders, built from average brain activity. We distinguish decoder performance when used for discriminating between, in contrast to identifying, mental states, and show even when discrimination performance is strong, identification can be poor. Using similarity rules, we derived novel and intuitive discriminability metrics that capture 95% and 68% of discrimination performance within- and across-subjects, respectively. These findings demonstrate that current across-subject decoders remain inadequate for real-life decision making.

The opiate epidemic has severe medical and social consequences. Opioids are commonly prescribed in patients with chronic pain, and are a main contributor to the opiate epidemic. The adverse effects of long-term opioid usage have been studied primarily in dependence/addiction disorders, but not in chronic pain. Here, we examine the added iatrogenic effects, psychology, and brain morphology of long-term opioid use in matched patients with chronic pain with and without opioid use (case-controlled design).We compared psychosocial, functional, and psychological measures between patients with chronic back pain (CBP) who were managing their pain with or without opioids, thereby controlling for the effect of pain on these outcomes. In addition, we investigated brain morphological differences associated with long-term opioid usage. We recruited 58 patients with CBP, 29 of them on long-term opioids and 29 who did not use opioids, and who were matched in terms of age, sex, pain intensity, and pain duration. Questionnaires were used to assess pain quality, pain psychology, negative and positive emotions, physical, cognitive, sensory, and motor functions, quality of life, and personality traits.Patients with CBP on opioids displayed more negative emotion, poorer physical function, and more pain interference (p 0.001), whereas there were no statistical differences in cognitive and motor functions and personality traits. Voxel-based morphometry using structural brain imaging data identified decreased gray matter density of the dorsal paracingulate cortex (family-wise error-corrected p 0.05) in patients with opioids, which was associated with negative emotion (p = 0.03). Finally, a volumetric analysis of hippocampal subfields identified lower volume of the left presubiculum in patients on opioids (p 0.001).Long-term opioid use in chronic pain is associated with adverse negative emotion and disabilities, as well as decreased gray matter volumes of specific brain regions.

Sex differences in the quality and prevalence of chronic pain are manifold, with females generally presenting higher incidence and severity. Uncovering chronic pain-related sex differences informs neural mechanisms and may lead to novel treatment routes. In a multi-center morphological study (total n=374), we investigated whether the shape of subcortical regions would reflect sex differences in back pain. Given the hormone-dependent functions of the hippocampus, and its role in the transition to chronic pain, this region constituted our primary candidate. We found that the anterior part of the left hippocampus (alHP) presented outer deformation in females with chronic back pain (CBP), identified in CBP in the USA (n=77 females vs. n=78 males) and validated in a Chinese dataset (n=29 females vs. n=58 males with CBP, in contrast to n=53 female and n=43 male healthy controls). Next, we examined this region in subacute back pain (SBP) who persisted with back pain a year later (SBPp; n=18 females vs. n=18 males), and in a subgroup with persistent back pain for 3-years. Weeks after onset of back pain there was no deformation within alHP, but at 1-year and 3-years females exhibited a trend for outer deformation. The alHP partly overlapped with the subiculum and entorhinal cortex, whose functional connectivity, in healthy subjects, was associated with emotional and episodic memory related terms (Neurosynth, reverse inference). These findings suggest that in females alHP undergoes anatomical changes with pain persistence, highlighting sexually-dimorphic involvement of emotional and episodic memory-related circuitry with chronic pain.

Although placebo effect sizes in clinical trials of chronic pain treatments have been increasing, it remains unknown if characteristics of individuals' thoughts or previous experiences can reliably infer placebo pill responses. Research using language to investigate emotional and cognitive processes has recently gained momentum. Here, we quantified placebo responses in chronic back pain using more than 300 semantic and psycholinguistic features derived from patients' language. This speech content was collected in an exit interview as part of a clinical trial investigating placebo analgesia (62 patients, 42 treated; 20 not treated). Using a nested leave-one-out cross-validated approach, we distinguished placebo responders from nonresponders with 79% accuracy using language features alone; a subset of these features-semantic distances to identity and stigma and the number of achievement-related words-also explained 46% of the variance in placebo analgesia. Importantly, these language features were not due to generic treatment effects and were associated with patients' specific baseline psychological traits previously shown to be predictive of placebo including awareness and personality characteristics, explaining an additional 31% of the variance in placebo analgesia beyond that of personality. Initial interpretation of the features suggests that placebo responders differed in how they talked about negative emotions and the extent that they expressed awareness to various aspects of their experiences; differences were also seen in time spent talking about leisure activities. These results indicate that patients' language is sufficient to identify a placebo response and implie that specific speech features may be predictive of responders' previous treatment.

The nucleus accumbens (NAc) and the ventral tegmental area (VTA) are critical hubs in the brain circuitry controlling chronic pain. Yet, how these 2 regions interact to shape the chronic pain state is poorly understood. Our studies show that in mice, spared nerve injury (SNI) induced alterations in the functional connectome of D2-receptor expressing spiny projection neurons in the core region of the NAc-enhancing connections with prelimbic cortex and weakening them with basolateral amygdala. These changes, which were attributable in part to SNI-induced suppression of VTA dopaminergic signaling, were adaptive because mimicking them chemogenetically alleviated the anxiety and social withdrawal accompanying injury. By contrast, chemogenetic enhancement of activity in VTA dopaminergic neurons projecting to the medial shell of the NAc selectively suppressed tactile allodynia in SNI mice. These results suggest that SNI induces regionally specific alterations in VTA dopaminergic signaling in the NAc to promote environmental reengagement after injury. However, countervailing, homeostatic mechanisms limit these adaptive changes, potentially leading to the chronic pain state.

Almost 30 years ago, technology based on magnetic resonance imaging (MRI) made it possible to visualize the functional states of the human brain. This technology immediately spurred pain researchers to examine brain circuitry of human pain and relate brain activity patterns with verbal reports of subjective perception. There was a brief period prior to functional MRI (fMRI) when positron emission tomography (PET) and single-photon emission computed tomography (SPECT) technologies were used to identify brain states in humans reporting pain, but the noninvasiveness of fMRI and its higher spatial and temporal resolution quickly made the latter the preferred choice to study human brain physiology. Prior to the advent of such human brain imaging technologies, whether the neocortex was involved in pain perception was still an open question: In human brain injury studies, large cortical lesions seemed to have little effect on pain perception, and in animal electrophysiological studies (mostly done in anesthetized preparations) several years of single-unit electrophysiological explorations from large expanses of the cortex yielded a measly number of neurons responding to nociceptive stimuli and not a single neocortical column dedicated to nociception. What has been learned between the introduction of the technology and today? This chapter briefly reviews the subject, highlighting advances and novel insights and pointing to lingering gaps. It also outlines future directions from the viewpoint of understanding mechanisms for nociception, acute pain, and chronic pain. From a brain imaging viewpoint, the chapter tackles the last concepts regarding local neuronal representation and across neuronal integration of information.

Background:. More than 75% of major limb amputees experience chronic pain; however, data on severity and experience of pain are inconsistent. Without a benchmark using quantitative patient-reported outcomes, it is difficult to critically assess the efficacy of novel treatment strategies. Our primary objective is to report quantitative pain parameters for a large sample of amputees using the validated Patient-reported Outcomes Measurement System (PROMIS). Secondarily, we hypothesize that certain patient factors will be associated with worse pain. Methods:. PROMIS and Numerical Rating Scales for residual limb pain (RLP) and phantom limb pain (PLP) were obtained from a cross-sectional survey of upper and lower extremity amputees recruited throughout North America via amputee clinics and websites. Demographics (gender, age, race, and education) and clinical information (cause, amputation level, and time since amputation) were collected. Regression modeling identified factors associated with worse pain scores (P < 0.05). Results:. Seven hundred twenty-seven surveys were analyzed, in which 73.4% reported RLP and 70.4% reported PLP. Median residual PROMIS scores were 46.6 [interquartile range (IQR), 41–52] for RLP Intensity, 56.7 (IQR, 51–61) for RLP Behavior, and 55.9 (IQR, 41–63) for RLP Interference. Similar scores were calculated for PLP parameters: 46.8 (IQR, 41–54) for PLP Intensity, 56.2 (IQR, 50–61) for PLP Behavior, and 54.6 (IQR, 41–62) for PLP Interference. Female sex, lower education, trauma-related amputation, more proximal amputation, and closer to time of amputation increased odds of PLP. Female sex, lower education, and infection/ischemia-related amputation increased odds of RLP. Conclusion:. This survey-based analysis provides quantitative benchmark data regarding RLP and PLP in amputees with more granularity than has previously been reported.

Even though a number of findings, based on information content or information integration, are shown to define neural underpinnings characteristic of a conscious experience, the neurophysiological mechanism of consciousness is still poorly understood. Here, we investigated the brain activity and functional connectivity changes that occur in the isoflurane-anesthetized unconscious state in contrast to the awake state in rats (awake and/or anesthetized, n = 68 rats). We examined nine information measures previously shown to distinguish between conscious states: blood oxygen level-dependent (BOLD) variability, functional connectivity strength, modularity, weighted modularity, efficiency, clustering coefficient, small-worldness, and spatial and temporal Lempel-Ziv complexity measure. We also identified modular membership, seed-based network connectivity, and absolute and normalized power spectrums to assess the integrity of the BOLD functional networks between awake and anesthesia. fMRI BOLD variability and related absolute power were the only information measures significantly higher during the awake state compared with isoflurane anesthesia across animals, and with varying levels of anesthesia, after correcting for motion and respiration confounds. Thus, we conclude that, at least under the specific conditions examined here, global measures of information integration/sharing do not properly distinguish the anesthetized state from wakefulness, and heightened overall, global and local, BOLD variability is the most reliable determinant of conscious brain activity relative to isoflurane anesthesia. NEW & NOTEWORTHY Multiple metrics previously suggested to be able to distinguish between states of consciousness were compared, within and across rats in awake and isoflurane anesthesia-induced unconsciousness. All measures tested showed sensitivity to confounds, correcting for motion and for respiration changes due to anesthesia. Resting state local BOLD variability and the related absolute power were the only information measures that robustly differentiated wakefulness states. These results caution against the general applicability of global information measures in identifying levels of consciousness, thus challenging the popular concept that these measures reflect states of consciousness, and also pointing to local signal variability as a more reliable indicator of states of wakefulness.

Experiences and memories are often mismatched. While multiple studies have investigated psychological underpinnings of recall error with respect to emotional events, the neurobiological mechanisms underlying the divergence between experiences and memories remain relatively unexplored in the domain of chronic pain. Here we examined the discrepancy between experienced chronic low back pain (CBP) intensity (twice daily ratings) and remembered pain intensity (n = 48 subjects) relative to psychometric properties, hippocampus morphology, memory capabilities, and personality traits related to reward. 77% of CBP patients exaggerated remembered pain, which depended on their strongest experienced pain and their most recent mood rating. This bias persisted over nearly 1 year and was related to reward memory bias and loss aversion. Shape displacement of a specific region in the left posterior hippocampus mediated personality effects on pain memory bias, predicted pain memory bias in a validation CBP group (n = 21), and accounted for 55% of the variance of pain memory bias. In two independent groups (n = 20/group), morphology of this region was stable over time and unperturbed by the development of chronic pain. These results imply that a localized hippocampal circuit, and personality traits associated with reward processing, largely determine exaggeration of daily pain experiences in chronic pain patients.