Pain-free resting-state functional brain connectivity predicts individual pain sensitivity

Multimodal covarying brain patterns mediate genetic and psychological contributions to individual differences in pain sensitivity

ABSTRACT

Individuals vary significantly in their pain sensitivity, with contributions from the brain, genes, and psychological factors. However, a multidimensional model integrating these factors is lacking due to their complex interactions. To address this, we measured pain sensitivity (ie, pain threshold and pain tolerance) using the cold pressor test, collected magnetic resonance imaging (MRI) data and genetic data, and evaluated psychological factors (ie, pain catastrophizing, pain-related fear, and pain-related anxiety) from 450 healthy participants with both sexes (160 male, 290 female). Using multimodal MRI fusion methods, we identified 2 pairs of covarying structural and functional brain patterns associated with pain threshold and tolerance, respectively. These patterns primarily involved regions related to self-awareness, sensory-discriminative, cognitive-evaluative, motion preparation and execution, and emotional aspects of pain. Notably, pain catastrophizing was negatively correlated with pain tolerance, and this relationship was mediated by the multimodal covarying brain patterns in male participants only. Furthermore, we identified an association between the single-nucleotide polymorphism rs4141964 within the fatty acid amide hydrolase gene and pain threshold, mediated by the identified multimodal covarying brain patterns across all participants. In summary, we suggested a model that integrates the brain, genes, and psychological factors to elucidate their role in shaping interindividual variations in pain sensitivity, highlighting the important contribution of the multimodal covarying brain patterns as important biological mediators in the associations between genes/psychological factors and pain sensitivity.

EEG-Based Cortical Alterations in Individuals With Chronic Knee Pain Secondary to Osteoarthritis: A Cross-sectional Investigation

Chronic painful knee osteoarthritis (OA) is a disabling physical health condition. Alterations in brain responses to arthritic changes in the knee may explain persistent pain. This study investigated source localized, resting-state electroencephalography activity and functional connectivity in people with knee OA, compared to healthy controls. Adults aged 44 to 85 years with knee OA (n = 37) and healthy control (n = 39) were recruited. Resting-state electroencephalography was collected for 10 minutes and decomposed into infraslow frequency (ISF) to gamma frequency bands. Standard low-resolution electromagnetic brain tomography statistical nonparametric maps were conducted, current densities of regions of interest were compared between groups and correlation analyses were performed between electroencephalography (EEG) measures and clinical pain and functional outcomes in the knee OA group. Standard low-resolution electromagnetic brain tomography nonparametric maps revealed higher (P = .006) gamma band activity over the right insula (RIns) in the knee OA group. A significant (P < .0001) reduction in ISF band activity at the pregenual anterior cingulate cortex, whereas higher theta, alpha, beta, and gamma band activity at the dorsal anterior cingulate cortex, pregenual anterior cingulate cortex, the somatosensory cortex, and RIns in the knee OA group were identified. ISF activity of the dorsal anterior cingulate cortex was positively correlated with pain measures and psychological distress scores. Theta and alpha activity of RIns were negatively correlated with pain interference. In conclusion, aberrations in infraslow and faster frequency EEG oscillations at sensory discriminative, motivational-affective, and descending inhibitory cortical regions were demonstrated in people with chronic painful knee OA. Moreover, EEG oscillations were correlated with pain and functional outcome measures. PERSPECTIVE: This study confirms alterations in the rsEEG oscillations and its relationship with pain experience in people with knee OA. The study provides potential cortical targets and the EEG frequency bands for neuromodulatory interventions for managing chronic pain experience in knee OA.

Machine learning and artificial intelligence in neuroscience: A primer for researchers

Artificial intelligence (AI) is often used to describe the automation of complex tasks that we would attribute intelligence to. Machine learning (ML) is commonly understood as a set of methods used to develop an AI. Both have seen a recent boom in usage, both in scientific and commercial fields. For the scientific community, ML can solve bottle necks created by complex, multi-dimensional data generated, for example, by functional brain imaging or *omics approaches. ML can here identify patterns that could not have been found using traditional statistic approaches. However, ML comes with serious limitations that need to be kept in mind: their tendency to optimise solutions for the input data means it is of crucial importance to externally validate any findings before considering them more than a hypothesis. Their black-box nature implies that their decisions usually cannot be understood, which renders their use in medical decision making problematic and can lead to ethical issues. Here, we present an introduction for the curious to the field of ML/AI. We explain the principles as commonly used methods as well as recent methodological advancements before we discuss risks and what we see as future directions of the field. Finally, we show practical examples of neuroscience to illustrate the use and limitations of ML.

Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach

ABSTRACT

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

Oxytocin promotes prefrontal population activity via the PVN-PFC pathway to regulate pain

Neurons in the prefrontal cortex (PFC) can provide top-down regulation of sensory-affective experiences such as pain. Bottom-up modulation of sensory coding in the PFC, however, remains poorly understood. Here, we examined how oxytocin (OT) signaling from the hypothalamus regulates nociceptive coding in the PFC. In vivo time-lapse endoscopic calcium imaging in freely behaving rats showed that OT selectively enhanced population activity in the prelimbic PFC in response to nociceptive inputs. This population response resulted from the reduction of evoked GABAergic inhibition and manifested as elevated functional connectivity involving pain-responsive neurons. Direct inputs from OT-releasing neurons in the paraventricular nucleus (PVN) of the hypothalamus are crucial to maintaining this prefrontal nociceptive response. Activation of the prelimbic PFC by OT or direct optogenetic stimulation of oxytocinergic PVN projections reduced acute and chronic pain. These results suggest that oxytocinergic signaling in the PVN-PFC circuit constitutes a key mechanism to regulate cortical sensory processing.

Structural brain connectivity predicts early acute pain after mild traumatic brain injury

ABSTRACT

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 postinjury pain is important because 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, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 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 2 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.

A Comparison of Functional Connectivity in the Human Brainstem and Spinal Cord Associated with Noxious and Innocuous Thermal Stimulation Identified by Means of Functional MRI

The somatosensory system is multidimensional and processes important information for survival, including the experience of pain. The brainstem and spinal cord serve pivotal roles in both transmitting and modulating pain signals from the periphery; although, they are studied less frequently with neuroimaging when compared to the brain. In addition, imaging studies of pain often lack a sensory control condition, failing to differentiate the neural processes associated with pain versus innocuous sensations. The purpose of this study was to investigate neural connectivity between key regions involved in descending modulation of pain in response to a hot, noxious stimulus as compared to a warm, innocuous stimulus. This was achieved with functional magnetic resonance imaging (fMRI) of the brainstem and spinal cord in 20 healthy men and women. Functional connectivity was observed to vary between specific regions across painful and innocuous conditions. However, the same variations were not observed in the period of anticipation prior to the onset of stimulation. Specific connections varied with individual pain scores only during the noxious stimulation condition, indicating a significant role of individual differences in the experience of pain which are distinct from that of innocuous sensation. The results also illustrate significant differences in descending modulation before and during stimulation in both conditions. These findings contribute to a deeper understanding of the mechanisms underlying pain processing at the level of the brainstem and spinal cord, and how pain is modulated.

STING controls opioid-induced itch and chronic itch via spinal tank-binding kinase 1-dependent type I interferon response in mice

BACKGROUND

Patients receiving epidural or intrathecal opioids administration for neuraxial analgesia frequently suffer from an irritating itch. STING (stimulator of interferon genes), an innate immune modulator, is strongly implicated in pain pathogenesis via neuron-immune modulation. Given that pain and itch share some common neurocircuits, we evaluate the therapeutic potential of STING agonists in opioid-induced itch and chronic itch.

METHODS

Opioids (morphine, fentanyl and sufentanil) were intrathecally injected to induce acute itch. Chronic itch was induced by dry skin and contact dermatitis. Opioids analgesic effect, itch-induced scratching behavior, spinal expression of STING, phosphorylation of TBK1 (tank-binding kinase 1), IRF3 (interferon regulatory factor-3) and ERK (extracellular signal-regulated kinase), as well as production of IFN-α and IFN-β were examined. STING agonists (DMXAA and ADU-S100), TBK1 inhibitor, recombinant IFN-α and IFN-β elucidated the mechanism and treatment of itch. Whole-brain functional connectivity was evaluated using resting-state fMRI.

RESULTS

We report the primary expression of STING protein by the spinal dorsal horn neurons. Intraperitoneal injection of DMXAA dose-dependently reduces morphine-induced scratch bouts, without impairing morphine antinociception. Simultaneously, DMXAA alleviates fentanyl- and sufentanil-induced itching-like behavior, and chronic scratching behavior caused by dry skin and contact dermatitis. Furthermore, DMXAA drastically increases spinal phosphorylation of TBK1 and IRF3 following morphine exposure, dry skin and contact dermatitis. DMXAA-induced anti-pruritus effects and spinal productions of IFN-α and IFN-β are compensated by intrathecal delivery of the TBK1 inhibitor. Also, ADU-S100, recombinant IFN-α and IFN-β exhibits remarkable attenuation in scratching behaviors after morphine injection and dermatitis. Recombinant IFN-α inhibits morphine-induced spinal phosphorylation of ERK. Finally, DMXAA prevents dermatitis-induced the increase of cerebral functional connectivity between regions of interests such as primary somatosensory cortex, piriform cortex, retrosplenial cortex, colliculus and ventral thalamus.

CONCLUSIONS

STING activation confers protection against opioid-induced itch and chronic itch through spinal up-regulation of TBK1-IRF3-type I interferon cascades in mice, suggesting that STING agonists are promising candidates in translational development for pruritus relief.

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

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

Gray matter volume and pain tolerance in a general population: the Tromsø study

ABSTRACT

As pain is processed by an extensive network of brain regions, the structural status of the brain may affect pain perception. We aimed to study the association between gray matter volume (GMV) and pain sensitivity in a general population. We used data from 1522 participants in the seventh wave of the Tromsø study, who had completed the cold pressor test (3°C, maximum time 120 seconds), undergone magnetic resonance imaging (MRI) of the brain, and had complete information on covariates. Cox proportional hazards regression models were fitted with time to hand withdrawal from cold exposure as outcome. Gray matter volume was the independent variable, and analyses were adjusted for intracranial volume, age, sex, education level, and cardiovascular risk factors. Additional adjustment was made for chronic pain and depression in subsamples with available information on the respective item. FreeSurfer was used to estimate vertexwise cortical and subcortical gray matter volumes from the T1-weighted MR image. Post hoc analyses were performed on cortical and subcortical volume estimates. Standardized total GMV was associated with risk of hand withdrawal (hazard ratio [HR] 0.81, 95% confidence interval [CI] 0.71-0.93). The effect remained significant after additional adjustment for chronic pain (HR 0.84, 95% CI 0.72-0.97) or depression (HR 0.82, 95% CI 0.71-0.94). In post hoc analyses, positive associations between standardized GMV and pain tolerance were seen in most brain regions, with larger effect sizes in regions previously shown to be associated with pain. In conclusion, our findings indicate that larger GMV is associated with longer pain tolerance in the general population.

Changes in global functional network properties predict individual differences in habit formation

Prior evidence suggests that sensorimotor regions play a crucial role in habit formation. Yet, whether and how their global functional network properties might contribute to a more comprehensive characterization of habit formation still remains unclear. Capitalizing on advances in Elastic Net regression and predictive modeling, we examined whether learning-related functional connectivity alterations distributed across the whole brain could predict individual habit strength. Using the leave-one-subject-out cross-validation strategy, we found that the habit strength score of the novel unseen subjects could be successfully predicted. We further characterized the contribution of both, individual large-scale networks and individual brain regions by calculating their predictive weights. This highlighted the pivotal role of functional connectivity changes involving the sensorimotor network and the cingulo-opercular network in subject-specific habit strength prediction. These results contribute to the understanding the neural basis of human habit formation by demonstrating the importance of global functional network properties especially also for predicting the observable behavioral expression of habits.

Predictive modeling of optimism bias using gray matter cortical thickness

People have been shown to be optimistically biased when their future outcome expectancies are assessed. In fact, we display optimism bias (OB) toward our own success when compared to a rival individual's (personal OB [POB]). Similarly, success expectancies for social groups we like reliably exceed those we mention for a rival group (social OB [SOB]). Recent findings suggest the existence of neural underpinnings for OB. Mostly using structural/functional MRI, these findings rely on voxel-based mass-univariate analyses. While these results remain associative in nature, an open question abides whether MRI information can accurately predict OB. In this study, we hence used predictive modelling to forecast the two OBs. The biases were quantified using a validated soccer paradigm, where personal (self versus rival) and social (in-group versus out-group) forms of OB were extracted at the participant level. Later, using gray matter cortical thickness, we predicted POB and SOB via machine-learning. Our model explained 17% variance (R² = 0.17) in individual variability for POB (but not SOB). Key predictors involved the rostral-caudal anterior cingulate cortex, pars orbitalis and entorhinal cortex-areas that have been associated with OB before. We need such predictive models on a larger scale, to help us better understand positive psychology and individual well-being.

Occupational therapy using a robotic-assisted glove ameliorates finger dexterity and modulates functional connectivity in amyotrophic lateral sclerosis

INTRODUCTION

Although rehabilitation is recommended for amyotrophic lateral sclerosis (ALS), improvement of functional decline has hardly been achieved. We investigated the effect of occupational therapy that uses a robotic-assisted glove (RAG) on hand dexterity and the functional connectivities found in the brain of ALS patients.

METHOD

Ten patients diagnosed with ALS and admitted to the Shiga University of Medical Science (SUMS) Hospital from December 2018 to December 2021 participated in the study. These participants chose the hand side to wear RAG and exercised for two weeks. A sham movement was performed on the other side. We administered several functional assessments, including the Simple Test for Evaluating Hand Function (STEF), grip strength, pinch meter for grip strength, Canadian occupational performance measure (COPM), as well as nerve conduction study (NCS) before and after the exercise, and evaluated the results. We also analyzed six patients' resting-state functional magnetic resonance imaging (rs-fMRI).

RESULTS

Two-week robotic rehabilitation improved the STEF, grip strength, and COPM scores when compared with those of the other side. However, no significant effect was observed in the pinch meter and the NCS results. The rs-fMRI data analysis revealed that the robotic rehabilitation augmented two functional connectivities between the left pallidum-right supplementary motor cortex and right insular cortex-right sensorimotor network among the patients, which had beneficial effects.

CONCLUSION

The occupational therapy using RAG displayed improved hand dexterity. The enhanced functional connectivities around the sensorimotor network might be associated with the improvement in hand dexterity because of the RAG.

Limbic Connectivity Underlies Pain Treatment Response in Small-Fiber Neuropathy

OBJECTIVE

Small-fiber neuropathy (SFN) is characterized by neuropathic pain due to degeneration of small-diameter nerves in the skin. Given that brain reorganization occurs following chronic neuropathic pain, this study investigated the structural and functional basis of pain-related brain changes after skin nerve degeneration.

METHODS

Diffusion-weighted and resting-state functional MRI data were acquired from 53 pathologically confirmed SFN patients, and the structural and functional connectivity of the pain-related network was assessed using network-based statistic (NBS) analysis.

RESULTS

Compared with age- and sex-matched controls, the SFN patients exhibited a robust and global reduction of functional connectivity, mainly across the limbic and somatosensory systems. Furthermore, lower functional connectivity was associated with skin nerve degeneration measured by reduced intraepidermal nerve fiber density and better therapeutic response to anti-neuralgia medications, particularly for the connectivity between the insula and the limbic areas including the anterior and middle cingulate cortices. Similar to the patterns of functional connectivity changes, the structural connectivity was robustly reduced among the limbic and somatosensory areas, and the cognition-integration areas including the inferior parietal lobule. There was shared reduction of structural and functional connectivity among the limbic, somatosensory, striatal, and cognition-integration systems: (1) between the middle cingulate cortex and inferior parietal lobule and (2) between the thalamus and putamen. These observations indicate the structural basis underlying altered functional connectivity in SFN.

INTERPRETATION

Our findings provide imaging evidence linking structural and functional brain dysconnectivity to sensory deafferentation caused by peripheral nerve degeneration and therapeutic responses for neuropathic pain in SFN. ANN NEUROL 2022.

The functional connectivity of the basal ganglia subregions changed in mid-aged and young males with chronic prostatitis/chronic pelvic pain syndrome

Background

The Basal ganglia (BG) played a crucial role in the brain-level mechanisms of chronic pain disorders. However, the functional changes of BG in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still poorly understood. This study investigated the BG subregions’ resting-state functional connectivity (rs-FC) in CP/CPPS patients compared with healthy controls.

Methods

Twenty eight patients with CP/CPPS and 28 age- and education-matched healthy males underwent clinical measurements and 3T brain MR imaging, including T1-weighted structural images and resting-state functional imaging. The data were analyzed by the seeded-based rs-FC analysis. Then, a machine learning method was applied to assess the feasibility of detecting CP/CPPS patients through the changed rs-FC.

Results

Compared with healthy males, patients presented decreased rs-FC between the BG subregions and right middle cingulate cortex, and correlated with pain (r = 0.51, p-uncorrected = 0.005) and urinary symptoms (r = –0.4, p-uncorrected = 0.034). The left superior temporal gyrus and right supramarginal gyrus showed decreased rs-FC with the BG subregions as well. The area under the receiver operating characteristic curve of 0.943 (accuracy = 80%, F1-score = 80.6%) was achieved for the classification of CP/CPPS patients and healthy males with support vector machine (SVM) based on the changed rs-FC.

Conclusion

These findings provide evidence of altered BG subregions’ rs-FC in CP/CPPS, which may contribute to our understanding of the BG’s role in CP/CPPS.

Genome-wide association study of pain sensitivity assessed by questionnaire and the cold pressor test

ABSTRACT

We deployed an online pain sensitivity questionnaire (PSQ) and an at-home version of the cold pressor test (CPT) in a large genotyped cohort. We performed genome-wide association studies on the PSQ score (25,321 participants) and CPT duration (6853). We identified one new genome-wide significant locus associated with the PSQ score, which was located in the TSSC1 (also known as EIPR1 ) gene (rs58194899, OR = 0.950 [0.933-0.967], P -value = 1.9 × 10 -8 ). Although high pain sensitivity measured by both PSQ and CPT was associated with individual history of chronic and acute pains, genetic correlation analyses surprisingly suggested an opposite direction: PSQ score was inversely genetically correlated with neck and shoulder pain ( rg = -0.71), rheumatoid arthritis (-0.68), and osteoarthritis (-0.38), and with known risk factors, such as the length of working week (-0.65), smoking (-0.36), or extreme BMI (-0.23). Gene-based analysis followed by pathway analysis showed that genome-wide association studies results were enriched for genes expressed in the brain and involved in neuronal development and glutamatergic synapse signaling pathways. Finally, we confirmed that females with red hair were more sensitive to pain and found that genetic variation in the MC1R gene was associated with an increase in self-perceived pain sensitivity as assessed by the PSQ.

Migraine disability, pain catastrophizing, and headache severity are associated with evoked pain and targeted by mind-body therapy

ABSTRACT

Meta-analysis suggests that migraine patients are no more sensitive to experimentally evoked pain than healthy control subjects. At the same time, studies have linked some migraine symptoms to quantitative sensory testing (QST) profiles. Unfortunately, previous studies associating migraine symptoms and QST have important methodological shortcomings, stemming from small sample sizes, and frequent use of univariate statistics for multivariate research questions. In the current study, we seek to address these limitations by using a large sample of episodic migraine patients (n = 103) and a multivariate analysis that associates pain ratings from many thermal intensities simultaneously with 12 clinical measures ranging from headache frequency to sleep abnormalities. We identified a single dimension of association between thermal QST and migraine symptoms that relates to pain ratings for all stimulus intensities and a subset of migraine symptoms relating to disability (Headache Impact Test 6 and Brief Pain Inventory interference), catastrophizing (Pain Catastrophizing Scale), and pain severity (average headache pain, Brief Pain Inventory severity, and Short-Form McGill Pain Questionnaire 2). Headache frequency, allodynia, affect, and sleep disturbances were unrelated to this dimension. Consistent with previous research, we did not observe any difference in QST ratings between migraine patients and healthy control subjects. Additionally, we found that the linear combination of symptoms related to QST was modified by the mind-body therapy enhanced mindfulness-based stress reduction (MBSR+). These results suggest that QST has a selective relationship with pain symptoms even in the absence of between-subjects differences between chronic pain patients and healthy control subjects.

Statistical quantification of confounding bias in machine learning models

BACKGROUND

The lack of nonparametric statistical tests for confounding bias significantly hampers the development of robust, valid, and generalizable predictive models in many fields of research. Here I propose the partial confounder test, which, for a given confounder variable, probes the null hypotheses of the model being unconfounded.

RESULTS

The test provides a strict control for type I errors and high statistical power, even for nonnormally and nonlinearly dependent predictions, often seen in machine learning. Applying the proposed test on models trained on large-scale functional brain connectivity data (N= 1,865) (i) reveals previously unreported confounders and (ii) shows that state-of-the-art confound mitigation approaches may fail preventing confounder bias in several cases.

CONCLUSIONS

The proposed test (implemented in the package mlconfound; https://mlconfound.readthedocs.io) can aid the assessment and improvement of the generalizability and validity of predictive models and, thereby, fosters the development of clinically useful machine learning biomarkers.

Neuroimaging in Breast Implant Illness: An fMRI Pilot Study

BACKGROUND

Some women with breast implants report systemic and cognitive symptoms known as breast implant illness (BII), which are very similar to those of fibromyalgia. Functional MRI (fMRI) has shown altered brain activity in fibromyalgia patients.

OBJECTIVES

The aim of this pilot study was to investigate whether brain alterations could be observed in BII patients by fMRI.

METHODS

Women aged 18 to 76 with silicone breast implants for cosmetic reasons were recruited through a Dutch online BII support organization (MKS) and through the Maastricht University Medical Center. Study participants comprised 12 women with BII and 12 women without symptoms. Participants completed questionnaires regarding demographic characteristics, medical history, psychosocial complaints (Four-Dimensional Symptom Questionnaire), cognitive failure (Mini-Mental State Examination), and pain intensity and pain-related disability (Chronic Pain Grade Scale). Subsequently, brain images of all participants were obtained by resting-state fMRI and diffusion tensor imaging in a 3-T MRI scanner (Siemens Medical System, Erlangen, Germany).

RESULTS

Eleven BII patients and 12 healthy controls were included in the analysis. Baseline characteristics were similar in the 2 groups and the mean silicone exposure was 15 years. Patients scored significantly higher than controls on both pain intensity and disability. Patients scored worse on depression, somatization, distress, and anxiety compared with asymptomatic women. Mini-Mental State Examination scores were normal. However, the analyses of both functional connectivity and structural integrity showed no significant differences between the 2 groups.

CONCLUSIONS

This pilot study showed no evidence of brain alterations in BII patients. However, patients scored significantly worse on psychosocial symptoms than controls. Psychological factors appear to play an important role in BII and should be further investigated.

LEVEL OF EVIDENCE: 2

Pain is Not a "thing": How That Error Affects Language and Logic in Pain Medicine

Effectiveness in academic and clinical communication depends upon agreement on what words and concepts denote and on the consequent ability to argue logically and accurately. In the pain medicine literature there are many examples of imprecision and confusion in this respect, including misnomers and fallacies in reasoning. This article firstly critically examines some of these misnomers. Identified themes include pain being conceptualised as a "thing," conflation between nociception and pain, and confusion between stimulus and response and between the perspectives of the experiencer and the observer of "pain." Secondly, fallacies in reasoning are identified that contribute to imprecision and confusion. These include reification of pain, attributing to the brain functions that belong to whole organisms, and the illusory truth effect. Thirdly, these themes are identified also in constructs that are shown to be based more on speculation than on fact. Taken together, these observations reveal a need to review and, where necessary, modify terminology and concepts used in Pain Medicine. PERSPECTIVE: This article examines a number of words and constructs commonly found in the pain literature from the perspective of accuracy in terms of their consistency of usage, concordance with fact, degree of speculation and logical argument. A common major theme is the error of considering pain as a "thing" that has agentive properties. A need to clarify much of the language used in Pain Medicine is identified.

Source localized infraslow neurofeedback training in people with chronic painful knee osteoarthritis: A randomized, double-blind, sham-controlled feasibility clinical trial

Persistent pain is a key symptom in people living with knee osteoarthritis (KOA). Infra-slow Neurofeedback (ISF-NF) training is a recent development focusing on modulating cortical slow-wave activity to improve pain outcomes. A parallel, two-armed double-blinded, randomized sham-controlled, feasibility clinical trial aimed to determine the feasibility and safety of a novel electroencephalography-based infraslow fluctuation neurofeedback (EEG ISF-NF) training in people with KOA and determine the variability of clinical outcomes and EEG changes following NF training. Eligible participants attended nine 30-min ISF-NF training sessions involving three cortical regions linked to pain. Feasibility measures were monitored during the trial period. Pain and functional outcomes were measured at baseline, post-intervention, and follow-up after 2 weeks. Resting-state EEG was recorded at baseline and immediate post-intervention. Participants were middle-aged (61.7 ± 7.6 years), New Zealand European (90.5%), and mostly females (62%) with an average knee pain duration of 4 ± 3.4 years. The study achieved a retention rate of 91%, with 20/22 participants completing all the sessions. Participants rated high levels of acceptance and “moderate to high levels of perceived effectiveness of the training.” No serious adverse events were reported during the trial. Mean difference (95% CI) for clinical pain and function measures are as follows for pain severity [active: 0.89 ± 1.7 (−0.27 to 2.0); sham: 0.98 ± 1.1 (0.22–1.7)], pain interference [active: 0.75 ± 2.3 (−0.82 to 2.3); Sham: 0.89 ± 2.1 (−0.60 to 2.4)], pain unpleasantness [active: 2.6 ± 3.7 (0.17–5.1); sham: 2.8 ± 3 (0.62–5.0)] and physical function [active: 6.2 ± 13 (−2.6 to 15); sham: 1.6 ± 12 (−6.8 to 10)]. EEG sources demonstrated frequency-specific neuronal activity, functional connectivity, and ISF ratio changes following NF training. The findings of the study indicated that the ISF-NF training is a feasible, safe, and acceptable intervention for pain management in people with KOA, with high levels of perceived effectiveness. The study also reports the variability in clinical, brain activity, and connectivity changes following training.

Personal Pain Sensitivity Prediction from Ultra-short-term Resting Heart Rate Variability

Pain is a subjective experience with interpersonal perception sensitivity differences. Pain sensitivity is of scientific and clinical interest, as it is a risk factor for several pain conditions. Resting heart rate variability (HRV) is a potential pain sensitivity measure reflecting the parasympathetic tone and baroreflex function, but it remains unclear how well the prediction can achieve. This work investigated the relationship between different ultra-short-term HRV features and various pain sensitivity representations from heat and electrical pain tests. From leave-subject-out cross-validated results, we found that HRV can better predict a composite pain sensitivity score built from different tests and measures than a single measure in terms of the agreement between predictions and observations. Heat pain sensitivity was more possibly predicted than electrical pain. SDNN, RMSSD and LF better predicted the composite pain sensitivity score than other feature combinations, consis-tent with pain's physical and emotional attributes. It should be emphasized that the validity is probably limited within HRV at the resting state rather than an arbitrary measurement. This work implies a potential pain sensitivity prediction possibility that may be worth further validation.

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.

Top-down threat bias in pain perception is predicted by intrinsic structural and functional connections of the brain

Top-down processes such as expectations play a key role in pain perception. In specific contexts, inferred threat of impending pain can affect perceived pain more than the noxious intensity. This biasing effect of top-down threats can affect some individuals more strongly than others due to differences in fear of pain. The specific characteristics of intrinsic brain characteristics that mediate the effects of top-down threat bias are mainly unknown. In this study, we examined whether threat bias is associated with structural and functional brain connectivity. The variability in the top-down bias was mapped to the microstructure of white matter in diffusion weighted images (DWI) using MRTrix3. Mean functional connectivity of five canonical resting state networks was tested for association with bias scores and with the identified DWI metrics. We found that the fiber density of the splenium of the corpus callosum was significantly low in individuals with high top-down threat bias (FWE corrected with 5000 permutations, p < 0.05). The mean functional connectivity within the language/memory and between language/memory and default mode networks predicted the bias scores. Functional connectivity within language memory networks predicted the splenium fiber density, higher pain catastrophizing and lower mindful awareness. Probabilistic tractography showed that the identified region in the splenium connected several sensory regions and high-order parietal regions between the two hemispheres, indicating the splenium's role in sensory integration. These findings demonstrate that individuals who show more change in pain with changes in the threat of receiving a stronger noxious stimulus have lower structural connectivity in the pathway necessary for integrating top-down cue information with bottom-up sensory information. Conversely, systems involved in memory recall, semantic and self-referential processing are more strongly connected in people with top-down threat bias.

Stretchable Temperature-Responsive Multimodal Neuromorphic Electronic Skin with Spontaneous Synaptic Plasticity Recovery

Multimodal electronic skin devices capable of detecting multimodal signals provide the possibility for health monitoring. Sensing and memory for temperature and deformation by human skin are of great significance for the perception and monitoring of physiological changes of the human body. Electronic skin is highly expected to have similar functions as human skin. Here, by implementing intrinsically stretchable neuromorphic transistors with mechanoreceptors and thermoreceptors in an array, we have realized stretchable temperature-responsive multimodal neuromorphic electronic skin (STRM-NES) with both sensory and memory functions, in which synaptic plasticity can be modulated by multiple modalities, in situ temperature variations, and stretching deformations. Temperature-responsive functions, spontaneous recovery, and temperature-dependent multitrial learning are proposed. Furthermore, a stretchable temperature neuromorphic array composed of multiple fully functional subcells is demonstrated to identify temperature distributions and variations at different regions and conditions after various strains of skin. The STRM-NES has temperature- and strain-responsive neuromorphic functions, excellent self-healing, and reusable capability, showing similar abilities as human skin to sense, transmit, memory, and recovery from external stimuli. It is expected to facilitate the development of wearable electronics, intelligent robotics, and prosthetic applications.

EEG Microstate-Specific Functional Connectivity and Stroke-Related Alterations in Brain Dynamics

The brain, as a complex dynamically distributed information processing system, involves the coordination of large-scale brain networks such as neural synchronization and fast brain state transitions, even at rest. However, the neural mechanisms underlying brain states and the impact of dysfunction following brain injury on brain dynamics remain poorly understood. To this end, we proposed a microstate-based method to explore the functional connectivity pattern associated with each microstate class. We capitalized on microstate features from eyes-closed resting-state EEG data to investigate whether microstate dynamics differ between subacute stroke patients (N = 31) and healthy populations (N = 23) and further examined the correlations between microstate features and behaviors. An important finding in this study was that each microstate class was associated with a distinct functional connectivity pattern, and it was highly consistent across different groups (including an independent dataset). Although the connectivity patterns were diminished in stroke patients, the skeleton of the patterns was retained to some extent. Nevertheless, stroke patients showed significant differences in most parameters of microstates A, B, and C compared to healthy controls. Notably, microstate C exhibited an opposite pattern of differences to microstates A and B. On the other hand, there were no significant differences in all microstate parameters for patients with left-sided vs. right-sided stroke, as well as patients before vs. after lower limb training. Moreover, support vector machine (SVM) models were developed using only microstate features and achieved moderate discrimination between patients and controls. Furthermore, significant negative correlations were observed between the microstate-wise functional connectivity and lower limb motor scores. Overall, these results suggest that the changes in microstate dynamics for stroke patients appear to be state-selective, compensatory, and related to brain dysfunction after stroke and subsequent functional reconfiguration. These findings offer new insights into understanding the neural mechanisms of microstates, uncovering stroke-related alterations in brain dynamics, and exploring new treatments for stroke patients.

Conditioned pain modulation is associated with heightened connectivity between the periaqueductal grey and cortical regions

Introduction

Conditioned pain modulation (CPM) is a psychophysical assessment used to estimate the efficiency of an individual's endogenous modulatory mechanisms. Conditioned pain modulation has been used as a predictive assessment for the development of chronic pain and responses to pain interventions. Although much is known about the spinal cord mechanisms associated with descending pain modulation, less is known about the contribution of supraspinal and especially cortical regions.

Objectives

We aimed to explore how whole-brain connectivity of a core modulatory region, the periaqueductal grey (PAG), is associated with conditioned pain modulation, and endogenous pain modulation more broadly.

Methods

We measured CPM and resting-state connectivity of 35 healthy volunteers, absent of chronic pain diagnoses. As a region of interest, we targeted the PAG, which is directly involved in endogenous modulation of input to the spinal cord and is a key node within the descending pain modulation network.

Results

We found that CPM was associated with heightened connectivity between the PAG and key regions associated with pain processing and inhibition, such as the primary and secondary somatosensory cortices, as well as the motor, premotor, and dorsolateral prefrontal cortices. These findings are consistent with connectivity findings in other resting-state and event-related fMRI studies.

Conclusion

These findings indicate that individuals who are efficient modulators have greater functional connectivity between the PAG and regions involved in processing pain. The heightened connectivity of these regions may contribute to the beneficial outcomes in clinical pain management, as quantified by CPM. These results may function as brain-based biomarkers for vulnerability or resilience to pain.

Increased functional connectivity between limbic brain areas in healthy individuals with high versus low sensitivity to cold pain: A resting state fMRI study

Background

The representation of variability in sensitivity to pain by differences in neural connectivity patterns and its association with psychological factors needs further investigation. This study assessed differences in resting-state functional connectivity (rsFC) and its association to cognitive-affective aspects of pain in two groups of healthy subjects with low versus high sensitivity to pain (LSP vs. HSP). We hypothesized that HSP will show stronger connectivity in brain regions involved in the affective-motivational processing of pain and that this higher connectivity would be related to negative affective and cognitive evaluations of pain.

Methods

Forty-eight healthy subjects were allocated to two groups according to their tolerability to cold stimulation (cold pressor test, CPT, 1°C). Group LSP (N = 24) reached the cut-off time of 180±0 sec and group HSP tolerated the CPT for an average of 13±4.8 sec. Heat, cold and mechanical evoked pain were measured, as well as pain-catastrophizing (PCS), depression, anxiety and stress (DASS-21). All subjects underwent resting state fMRI. ROI-to-ROI analysis was performed.

Results

In comparison to the LSP, the HSP had stronger interhemispheric connectivity of the amygdala (p = 0.01) and between the amygdala and nucleus accumbens (NAc) (p = 0.01). Amygdala connectivity was associated with higher pain catastrophizing in the HSP only (p<0.01).

Conclusions

These findings suggest that high sensitivity to pain may be reflected by neural circuits involved in affective and motivational aspects of pain. To what extent this connectivity within limbic brain structures relates to higher alertness and more profound withdrawal behavior to aversive events needs to be further investigated.

Individual differences in mental imagery modulate effective connectivity of scene-selective regions during resting state

Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals' ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex, and Occipital Place Area (OPA) using Dynamic Causal Modelling for resting-state functional magnetic resonance data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire. We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

Combining Regional and Connectivity Metrics of Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging for Individualized Prediction of Pain Sensitivity

Characterization and prediction of individual difference of pain sensitivity are of great importance in clinical practice. MRI techniques, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), have been popularly used to predict an individual's pain sensitivity, but existing studies are limited by using one single imaging modality (fMRI or DTI) and/or using one type of metrics (regional or connectivity features). As a result, pain-relevant information in MRI has not been fully revealed and the associations among different imaging modalities and different features have not been fully explored for elucidating pain sensitivity. In this study, we investigated the predictive capability of multi-features (regional and connectivity metrics) of multimodal MRI (fMRI and DTI) in the prediction of pain sensitivity using data from 210 healthy subjects. We found that fusing fMRI-DTI and regional-connectivity features are capable of more accurately predicting an individual's pain sensitivity than only using one type of feature or using one imaging modality. These results revealed rich information regarding individual pain sensitivity from the brain's both structural and functional perspectives as well as from both regional and connectivity metrics. Hence, this study provided a more comprehensive characterization of the neural correlates of individual pain sensitivity, which holds a great potential for clinical pain management.

Supraspinal Mechanisms Underlying Ocular Pain

Supraspinal mechanisms of pain are increasingly understood to underlie neuropathic ocular conditions previously thought to be exclusively peripheral in nature. Isolating individual causes of centralized chronic conditions and differentiating them is critical to understanding the mechanisms underlying neuropathic eye pain and ultimately its treatment. Though few functional imaging studies have focused on the eye as an end-organ for the transduction of noxious stimuli, the brain networks related to pain processing have been extensively studied with functional neuroimaging over the past 20 years. This article will review the supraspinal mechanisms that underlie pain as they relate to the eye.

Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI

Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation-based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area-parabrachial pigmented nucleus complex, microcellular tegmental nucleus-prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus - alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting-state fMRI, ad-hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting-state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo-autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem-cortical connectivity and good yet weaker translatability for brainstem-brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.

Multi-Region Local Field Potential Signatures in Response to the Formalin-induced Inflammatory Stimulus in Male Rats

Pain can be ignited by noxious chemical (e.g., acid), mechanical (e.g., pressure), and thermal (e.g., heat) stimuli and generated by the activation of sensory neurons and their axonal terminals called nociceptors in the periphery. Nociceptive information transmitted from the periphery is projected to the central nervous system (thalamus, somatosensory cortex, insular, anterior cingulate cortex, amygdala, periaqueductal grey, prefrontal cortex, etc.) to generate a unified experience of pain. Local field potential (LFP) recording is one of the neurophysiological tools to investigate the combined neuronal activity, ranging from several hundred micrometers to a few millimeters (radius), located around the embedded electrode. The advantage of recording LFP is that it provides stable simultaneous activities in various brain regions in response to external stimuli. In this study, differential LFP activities from the contralateral anterior cingulate cortex (ACC), ventral tegmental area (VTA), and bilateral amygdala in response to peripheral noxious formalin injection were recorded in anesthetized male rats. The results indicated increased power of delta, theta, alpha, beta, and gamma bands in the ACC and amygdala but no change of gamma-band in the right amygdala. Within the VTA, intensities of the delta, theta, and beta bands were only enhanced significantly after formalin injection. It was found that the connectivity (i.t. the coherence) among these brain regions reduced significantly under the formalin-induced nociception, which suggests a significant interruption within the brain. With further study, it will sort out the key combination of structures that will serve as the signature for pain state.

Altered Functional Connectivity and Sensory Processing in Blepharospasm and Hemifacial Spasm: Coexistence and Difference

Background: Blepharospasm (BSP) and hemifacial spasm (HFS) are both facial hyperkinesia however BSP is thought to be caused by maladaptation in multiple brain regions in contrast to the peripherally induced cause in HFS. Plausible coexisting pathophysiologies between these two distinct diseases have been proposed.

Objectives: In this study, we compared brain resting state functional connectivity (rsFC) and quantitative thermal test (QTT) results between patients with BSP, HFS and heathy controls (HCs).

Methods: This study enrolled 12 patients with BSP, 11 patients with HFS, and 15 HCs. All subjects received serial neuropsychiatric evaluations, questionnaires determining disease severity and functional impairment, QTT, and resting state functional MRI. Image data were acquired using seed-based analyses using the CONN toolbox.

Results: A higher cold detection threshold was found in the BSP and HFS patients compared to the HCs. The BSP and HFS patients had higher rsFC between the anterior cerebellum network and left occipital regions compared to the HCs. In all subjects, impaired cold detection threshold in the QTT of lower extremities had a correlation with higher rsFC between the anterior cerebellar network and left lingual gyrus. Compared to the HCs, increased rsFC in right postcentral gyrus in the BSP patients and decreased rsFC in the right amygdala and frontal orbital cortex in the HFS subjects were revealed when the anterior cerebellar network was used as seed.

Conclusions: Dysfunction of sensory processing detected by the QTT is found in the BSP and HSP patients. Altered functional connectivity between the anterior cerebellar network and left occipital region, especially the Brodmann area 19, may indicate the possibility of shared pathophysiology among BSP, HFS, and impaired cold detection threshold. Further large-scale longitudinal study is needed for testing this theory in the future.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R² = 0.076; p < 0.001 and R² = 0.031; p < 0.029) and composite pain sensitivity (R² = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.

The brain's structural differences between postherpetic neuralgia and lower back pain

The purpose is to explore the brain's structural difference in local morphology and between-region networks between two types of peripheral neuropathic pain (PNP): postherpetic neuralgia (PHN) and lower back pain (LBP). A total of 54 participants including 38 LBP and 16 PHN patients were enrolled. The average pain scores were 7.6 and 7.5 for LBP and PHN. High-resolution structural T1 weighted images were obtained. Both grey matter volume (GMV) and morphological connectivity (MC) were extracted. An independent two-sample t-test with false discovery rate (FDR) correction was used to identify the brain regions where LBP and PHN patients showed significant GMV difference. Next, we explored the differences of MC network between LBP and PHN patients and detected the group differences in network properties by using the two-sample t-test and FDR correction. Compared with PHN, LBP patients had significantly larger GMV in temporal gyrus, insula and fusiform gyrus (p < 0.05). The LBP cohort had significantly stronger MC in the connection between right precuneus and left opercular part of inferior frontal gyrus (p < 0.05). LBP patients had significantly stronger degree in left anterior cingulate gyrus and left rectus gyrus (p < 0.05) while had significantly weaker degree than PHN patients in left orbital part of middle frontal gyrus, left supplementary motor area and left superior parietal lobule (p < 0.05). LBP and PHN patients had significant differences in the brain's GMV, MC, and network properties, which implies that different PNPs have different neural mechanisms concerning pain modulation.

Disrupted population coding in the prefrontal cortex underlies pain aversion

The prefrontal cortex (PFC) regulates a wide range of sensory experiences. Chronic pain is known to impair normal neural response, leading to enhanced aversion. However, it remains unknown how nociceptive responses in the cortex are processed at the population level and whether such processes are disrupted by chronic pain. Using in vivo endoscopic calcium imaging, we identify increased population activity in response to noxious stimuli and stable patterns of functional connectivity among neurons in the prelimbic (PL) PFC from freely behaving rats. Inflammatory pain disrupts functional connectivity of PFC neurons and reduces the overall nociceptive response. Interestingly, ketamine, a well-known neuromodulator, restores the functional connectivity among PL-PFC neurons in the inflammatory pain model to produce anti-aversive effects. These results suggest a dynamic resource allocation mechanism in the prefrontal representations of pain and indicate that population activity in the PFC critically regulates pain and serves as an important therapeutic target.

Li et al. reveal that inflammatory pain disrupts the functional connectivity of neurons in the prelimbic prefrontal cortex (PL-PFC) and the overall nociceptive response. Ketamine, meanwhile, restores the functional connectivity of neurons in the PL-PFC in the inflammatory pain state to produce anti-aversive effects.

Regional homogeneity alterations in multi-frequency bands in tension-type headache: a resting-state fMRI study

OBJECTIVES

In this study, we aimed to investigate the spontaneous neural activity in the conventional frequency band (0.01-0.08 Hz) and two sub-frequency bands (slow-4: 0.027-0.073 Hz, and slow-5: 0.01-0.027 Hz) in tension-type headache (TTH) patients with regional homogeneity (ReHo) analyses.

METHODS

Thirty-eight TTH patients and thirty-eight healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scanning to investigate abnormal spontaneous neural activity using ReHo analysis in conventional frequency band (0.01-0.08 Hz) and two sub-frequency bands (slow-4: 0.027-0.073 Hz and slow-5: 0.01-0.027 Hz).

RESULTS

In comparison with the HC group, patients with TTH exhibited ReHo increases in the right medial superior frontal gyrus in the conventional frequency band (0.01-0.08 Hz). The between group differences in the slow-5 band (0.01-0.027 Hz) highly resembled the differences in the conventional frequency band (0.01-0.08 Hz); even the voxels with increased ReHo were spatially more extensive, including the right medial superior frontal gyrus and the middle frontal gyrus. In contrast, no region showed significant between-group differences in the slow-4 band (0.027-0.073 Hz). The correlation analyses showed no correlation between the ReHo values in TTH patients and VAS scores, course of disease and number of seizures per month in conventional band (0.01-0.08 Hz), slow-4 band (0.027-0.073 Hz), as well as in slow-5 band (0.01-0.027 Hz).

CONCLUSIONS

The results showed that the superior frontal gyrus and middle frontal gyrus were involved in the integration and processing of pain signals. In addition, the abnormal spontaneous neural activity in TTH patients was frequency-specific. Namely, slow-5 band (0.01-0.027 Hz) might contain additional useful information in comparison to slow-4 band (0.027-0.073 Hz). This preliminary exploration might provide an objective imaging basis for the understanding of the pathophysiological mechanism of TTH.

Flexible brain transitions between hierarchical network segregation and integration associated with cognitive performance during a multisource interference task

Cognition involves locally segregated and globally integrated processing. This process is hierarchically organized and linked to evidence from hierarchical modules in brain networks. However, researchers have not clearly determined how flexible transitions between these hierarchical processes are associated with cognitive behavior. Here, we designed a multisource interference task (MSIT) and introduced the nested-spectral partition (NSP) method to detect hierarchical modules in brain functional networks. By defining hierarchical segregation and integration across multiple levels, we showed that the MSIT requires higher network segregation in the whole brain and most functional systems but generates higher integration in the control system. Meanwhile, brain networks have more flexible transitions between segregated and integrated configurations in the task state. Crucially, higher functional flexibility in the resting state, less flexibility in the task state and more efficient switching of the brain from resting to task states were associated with better task performance. Our hierarchical modular analysis was more effective at detecting alterations in functional organization and the phenotype of cognitive performance than graph-based network measures at a single level.

Decoding pain from brain activity

Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.

Brain Circuits Involved in the Development of Chronic Musculoskeletal Pain: Evidence From Non-invasive Brain Stimulation

It has been well-documented that the brain changes in states of chronic pain. Less is known about changes in the brain that predict the transition from acute to chronic pain. Evidence from neuroimaging studies suggests a shift from brain regions involved in nociceptive processing to corticostriatal brain regions that are instrumental in the processing of reward and emotional learning in the transition to the chronic state. In addition, dysfunction in descending pain modulatory circuits encompassing the periaqueductal gray and the rostral anterior cingulate cortex may also be a key risk factor for pain chronicity. Although longitudinal imaging studies have revealed potential predictors of pain chronicity, their causal role has not yet been determined. Here we review evidence from studies that involve non-invasive brain stimulation to elucidate to what extent they may help to elucidate the brain circuits involved in pain chronicity. Especially, we focus on studies using non-invasive brain stimulation techniques [e.g., transcranial magnetic stimulation (TMS), particularly its repetitive form (rTMS), transcranial alternating current stimulation (tACS), and transcranial direct current stimulation (tDCS)] in the context of musculoskeletal pain chronicity. We focus on the role of the motor cortex because of its known contribution to sensory components of pain via thalamic inhibition, and the role of the dorsolateral prefrontal cortex because of its role on cognitive and affective processing of pain. We will also discuss findings from studies using experimentally induced prolonged pain and studies implicating the DLPFC, which may shed light on the earliest transition phase to chronicity. We propose that combined brain stimulation and imaging studies might further advance mechanistic models of the chronicity process and involved brain circuits. Implications and challenges for translating the research on mechanistic models of the development of chronic pain to clinical practice will also be addressed.

Recommendations for the Development of Socioeconomically-Situated and Clinically-Relevant Neuroimaging Models of Pain

Pain is a complex, multidimensional experience that emerges from interactions among sensory, affective, and cognitive processes in the brain. Neuroimaging allows us to identify these component processes and model how they combine to instantiate the pain experience. However, the clinical impact of pain neuroimaging models has been limited by inadequate population sampling - young healthy college students are not representative of chronic pain patients. The biopsychosocial approach to pain management situates a person's pain within the diverse socioeconomic environments they live in. To increase the clinical relevance of pain neuroimaging models, a three-fold biopsychosocial approach to neuroimaging biomarker development is recommended. The first level calls for the development of diagnostic biomarkers via the standard population-based (nomothetic) approach with an emphasis on diverse sampling. The second level calls for the development of treatment-relevant models via a constrained person-based (idiographic) approach tailored to unique individuals. The third level calls for the development of prevention-relevant models via a novel society-based (social epidemiologic) approach that combines survey and neuroimaging data to predict chronic pain risk based on one's socioeconomic conditions. The recommendations in this article address how we can leverage pain's complexity in service of the patient and society by modeling not just individuals and populations, but also the socioeconomic structures that shape any individual's expectations of threat, safety, and resource availability.

Baseline resting-state functional connectivity determines subsequent pain ratings to a tonic ecologically valid experimental model of orofacial pain

ABSTRACT

Pain is a subjective experience with significant individual differences. Laboratory studies investigating pain thresholds and experimental acute pain have identified structural and functional neural correlates. However, these types of pain stimuli have limited ecological validity to real-life pain experiences. Here, we use an orthodontic procedure-the insertion of an elastomeric separator between teeth-which typically induces mild to moderate pain that peaks within 2 days and lasts several days. We aimed to determine whether the baseline structure and resting-state functional connectivity of key regions along the trigeminal nociceptive and pain modulatory pathways correlate with subsequent peak pain ratings. Twenty-six healthy individuals underwent structural and resting-state functional MRI scanning before the placement of a separator between the first molar and second premolar, which was kept in place for 5 days. Participants recorded pain ratings 3 times daily on a 100-mm visual analogue scale. Peak pain was not significantly correlated with diffusion metrics of the trigeminal nerve or gray matter volume of any brain region. Peak pain did, however, positively correlate with baseline resting-state functional connectivity between the thalamus contralateral to the separator and bilateral insula, and negatively correlated with connectivity between the periaqueductal gray (PAG) and core nodes of the default mode network (medial prefrontal and posterior cingulate cortices). The ascending (thalamic) nociceptive and the descending (PAG) pain modulatory pathways at baseline each explained unique variation in peak pain intensity ratings. In sum, preinterventional functional neural architecture of both systems determined the individual pain experience to a subsequent ecologically valid pain stimulus.

Dynamic alterations of amplitude of low-frequency fluctuations in patients with chronic neck pain

Background

The pathogenesis of neck pain in the brain, which is the fourth most common cause of disability, remains unclear. Furthermore, little is known about the characteristics of dynamic local functional brain activity in cervical pain.

Objective

The present study aimed to investigate the changes of local brain activity caused by chronic neck pain and the factors leading to neck pain.

Methods

Using the amplitude of low-frequency fluctuations (ALFF) method combined with sliding window approach, we compared local brain activity that was measured by the functional magnetic resonance imaging (fMRI) of 107 patients with chronic neck pain (CNP) with that of 57 healthy control participants. Five pathogenic factors were selected for correlation analysis.

Results

The group comparison results of dynamic amplitude of low-frequency fluctuation (dALFF) variability showed that patients with CNP exhibited decreased dALFF variability in the left inferior temporal gyrus, the middle temporal gyrus, the angular gyrus, the inferior parietal marginal angular gyrus, and the middle occipital gyrus. The abnormal dALFF variability of the left inferior temporal gyrus was negatively correlated with the average daily working hours of patients with neck pain.

Conclusions

The findings indicated that the brain regions of patients with CNP responsible for audition, vision, memory, and emotion were subjected to temporal variability of abnormal regional brain activity. Moreover, the dALFF variability in the left inferior temporal gyrus might be a risk factor for neck pain.This study revealed the brain dysfunction of patients with CNP from the perspective of dynamic local brain activity, and highlighted the important role of dALFF variability in understanding the neural mechanism of CNP.

Network properties and regional brain morphology of the insular cortex correlate with individual pain thresholds

Pain thresholds vary considerably across individuals and are influenced by a number of behavioral, genetic and neurobiological factors. However, the neurobiological underpinnings that account for individual differences remain to be fully elucidated. In this study, we used voxel‐based morphometry (VBM) and graph theory, specifically the local clustering coefficient (CC) based on resting‐state connectivity, to identify brain regions, where regional gray matter volume and network properties predicted individual pain thresholds. As a main finding, we identified a cluster in the left posterior insular cortex (IC) reaching into the left parietal operculum, including the secondary somatosensory cortex, where both regional gray matter volume and the local CC correlated with individual pain thresholds. We also performed a resting‐state functional connectivity analysis using the left posterior IC as seed region, demonstrating that connectivity to the pre‐ as well as postcentral gyrus bilaterally; that is, to the motor and primary sensory cortices were correlated with individual pain thresholds. To our knowledge, this is the first study that applied VBM in combination with voxel‐based graph theory in the context of pain thresholds. The co‐location of the VBM and the local CC cluster provide first evidence that both structure and function map to the same brain region while being correlated with the same behavioral measure; that is, pain thresholds. The study highlights the importance of the posterior IC, not only for pain perception in general, but also for the determination of individual pain thresholds.

Anterior Cingulate Cortex Activity During Rest Is Related to Alterations in Pain Perception in Aging

Alterations in the affective component of pain perception are related to the development of chronic pain and may contribute to the increased vulnerability to pain observed in aging. The present study analyzed age-related changes in resting-state brain activity and their possible relation to an increased pain perception in older adults. For this purpose, we compared EEG current source density and fMRI functional-connectivity at rest in older (n = 20, 66.21 ± 3.08 years) and younger adults (n = 21, 20.71 ± 2.30 years) and correlated those brain activity parameters with pain intensity and unpleasantness ratings elicited by painful stimulation. We found an age-related increase in beta2 and beta3 activity in temporal, frontal, and limbic areas, and a decrease in alpha activity in frontal areas. Moreover, older participants displayed increased functional connectivity in the anterior cingulate cortex (ACC) and the insula with precentral and postcentral gyrus. Finally, ACC beta3 activity was positively correlated with pain intensity and unpleasantness ratings in older, and ACC-precentral/postcentral gyrus connectivity was positively correlated with unpleasantness ratings in older and younger participants. These results reveal that ACC resting-state hyperactivity is a stable trait of brain aging and may underlie their characteristic altered pain perception.

The Motor Basis for Misophonia

Misophonia is a common disorder characterized by the experience of strong negative emotions of anger and anxiety in response to certain everyday sounds, such as those generated by other people eating, drinking, and breathing. The commonplace nature of these "trigger" sounds makes misophonia a devastating disorder for sufferers and their families. How such innocuous sounds trigger this response is unknown. Since most trigger sounds are generated by orofacial movements (e.g., chewing) in others, we hypothesized that the mirror neuron system related to orofacial movements could underlie misophonia. We analyzed resting state fMRI (rs-fMRI) connectivity (N = 33, 16 females) and sound-evoked fMRI responses (N = 42, 29 females) in misophonia sufferers and controls. We demonstrate that, compared with controls, the misophonia group show no difference in auditory cortex responses to trigger sounds, but do show: (1) stronger rs-fMRI connectivity between both auditory and visual cortex and the ventral premotor cortex responsible for orofacial movements; (2) stronger functional connectivity between the auditory cortex and orofacial motor area during sound perception in general; and (3) stronger activation of the orofacial motor area, specifically, in response to trigger sounds. Our results support a model of misophonia based on "hyper-mirroring" of the orofacial actions of others with sounds being the "medium" via which action of others is excessively mirrored. Misophonia is therefore not an abreaction to sounds, per se, but a manifestation of activity in parts of the motor system involved in producing those sounds. This new framework to understand misophonia can explain behavioral and emotional responses and has important consequences for devising effective therapies.SIGNIFICANCE STATEMENT Conventionally, misophonia, literally "hatred of sounds" has been considered as a disorder of sound emotion processing, in which "simple" eating and chewing sounds produced by others cause negative emotional responses. Our data provide an alternative but complementary perspective on misophonia that emphasizes the action of the trigger-person rather than the sounds which are a byproduct of that action. Sounds, in this new perspective, are only a "medium" via which action of the triggering-person is mirrored onto the listener. This change in perspective has important consequences for devising therapies and treatment methods for misophonia. It suggests that, instead of focusing on sounds, which many existing therapies do, effective therapies should target the brain representation of movement.

Quantitative language features identify placebo responders in chronic back pain

ABSTRACT

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.

Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity

Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.