An fMRI-based neurologic signature of physical pain

Pain-preferential thalamocortical neural dynamics across species

Searching for pain-preferential neural activity is essential for understanding and managing pain. Here, we investigated the preferential role of thalamocortical neural dynamics in encoding pain using human neuroimaging and rat electrophysiology across three studies. In study 1, we found that painful stimuli preferentially activated the medial-dorsal (MD) thalamic nucleus and its functional connectivity with the dorsal anterior cingulate cortex (dACC) and insula in two human functional magnetic resonance imaging (fMRI) datasets (n = 399 and n = 25). In study 2, human fMRI and electroencephalography fusion analyses (n = 220) revealed that pain-preferential MD responses were identified 89-295 ms after painful stimuli. In study 3, rat electrophysiology further showed that painful stimuli preferentially activated MD neurons and MD-ACC connectivity. These converging cross-species findings provided evidence for pain-preferential thalamocortical neural dynamics, which could guide future pain evaluation and management strategies.

Graph theory analysis reveals an assortative pain network vulnerable to attacks

The neural substrate of pain experience has been described as a dense network of connected brain regions. However, the connectivity pattern of these brain regions remains elusive, precluding a deeper understanding of how pain emerges from the structural connectivity. Here, we employ graph theory to systematically characterize the architecture of a comprehensive pain network, including both cortical and subcortical brain areas. This structural brain network consists of 49 nodes denoting pain-related brain areas, linked by edges representing their relative incoming and outgoing axonal projection strengths. Within this network, 63% of brain areas share reciprocal connections, reflecting a dense network. The clustering coefficient, a measurement of the probability that adjacent nodes are connected, indicates that brain areas in the pain network tend to cluster together. Community detection, the process of discovering cohesive groups in complex networks, successfully reveals two known subnetworks that specifically mediate the sensory and affective components of pain, respectively. Assortativity analysis, which evaluates the tendency of nodes to connect with other nodes that have similar features, indicates that the pain network is assortative. Finally, robustness, the resistance of a complex network to failures and perturbations, indicates that the pain network displays a high degree of error tolerance (local failure rarely affects the global information carried by the network) but is vulnerable to attacks (selective removal of hub nodes critically changes network connectivity). Taken together, graph theory analysis unveils an assortative structural pain network in the brain that processes nociceptive information. Furthermore, the vulnerability of this network to attack presents the possibility of alleviating pain by targeting the most connected brain areas in the network.

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/dACC has been associated with more than 15 different cognitive processes, which sometimes appear quite unrelated (e.g. body perception, cognitive conflict). As a result, understanding what the dmPFC/dACC does has become a real challenge for many neuroscientists. Several theories of this brain area's function(s) have been developed, leading to successive and competitive publications bearing different models, which sometimes contradict each other. During the last two decades, the lively scientific exchanges around the dmPFC/dACC have promoted fruitful research in cognitive neuroscience. In this review, we provide an overview of the anatomy of the dmPFC/dACC, summarize the state of the art of functions that have been associated with this brain area and present the main theories aiming at explaining the dmPFC/dACC function(s). We explore the commonalities and the arguments between the different theories. Finally, we explain what can be learned from these debates for future investigations of the dmPFC/dACC and other brain regions' functions.

Moral foundations elicit shared and dissociable cortical activation modulated by political ideology

Moral foundations theory (MFT) holds that moral judgements are driven by modular and ideologically variable moral foundations but where and how these foundations are represented in the brain and shaped by political beliefs remains an open question. Using a moral vignette judgement task (n = 64), we probed the neural (dis)unity of moral foundations. Univariate analyses revealed that moral judgement of moral foundations, versus conventional norms, reliably recruits core areas implicated in theory of mind. Yet, multivariate pattern analysis demonstrated that each moral foundation elicits dissociable neural representations distributed throughout the cortex. As predicted by MFT, individuals' liberal or conservative orientation modulated neural responses to moral foundations. Our results confirm that each moral foundation recruits domain-general mechanisms of social cognition but also has a dissociable neural signature malleable by sociomoral experience. We discuss these findings in view of unified versus dissociable accounts of morality and their neurological support for MFT.

Differential Placebo Responses for Pharmacotherapy and Neurostimulation in Late-Life Depression

BACKGROUND

The magnitude of the placebo response depends on both the modality used as the "placebo" and the intervention with which it is compared, both of which can complicate the interpretation of randomized controlled trials (RCTs) for depression in late life. Given that neurostimulation and pharmacotherapy are among the most common interventions studied for late-life depression, comparing the relative placebo responses in studies of these interventions can aid interpretation of relative effect sizes.

MATERIALS AND METHODS

We analyzed data from two RCTs of adults aged ≥60 years in an episode of treatment-resistant major depression, one comparing aripiprazole and matching placebo pills and the other comparing deep repetitive transcranial magnetic stimulation (rTMS) and sham rTMS. In both RCTs, depression was assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17). The primary comparison occurred after four weeks using analysis of covariance (ANCOVA) of HDRS-17 scores in participants who received placebo pills or sham rTMS. Relevant covariates included years of education, duration of depressive episode, and baseline HDRS-17 score.

RESULTS

Accounting for covariates, there was a larger reduction of HDRS-17 after four weeks in the sham rTMS group (estimated marginal mean ± SE: -5.90 ± 1.45; 95% CI: [-8.82, 2.98]) than in the placebo pills group (-1.07 ± 1.45; [-3.98, 1.85]). There were no significant differences between these groups in the binary outcome analysis of response and remission rates at four weeks or any outcome at trial end point comparison.

CONCLUSIONS

Sham rTMS may have a larger placebo response than placebo pills early in the treatment of older adults with treatment-resistant depression. Differential placebo responses should be considered in both the interpretation and design of RCTs.

Pain and Reorganization after Amputation: Is Interoceptive Prediction a Key?

There is an ongoing discussion on the relevance of brain reorganization following amputation for phantom limb pain. Recent attempts to provide explanations for seemingly controversial findings-specifically, maladaptive plasticity versus persistent functional representation as a complementary process-acknowledged that reorganization in the primary somatosensory cortex is not sufficient to explain phantom limb pain satisfactorily. Here we provide theoretical considerations that might help integrate the data reviewed and suppose a possible additional driver of the development of phantom limb pain-namely, an error in interoceptive predictions to somatosensory sensations and movements of the missing limb. Finally, we derive empirically testable consequences based on our considerations to guide future research.

Longitudinal changes in human supraspinal processing after RIII-feedback training to improve descending pain inhibition

The human body has the ability to influence its sensation of pain by modifying the transfer of nociceptive information at the spinal level. This modulation, known as descending pain inhibition, is known to originate supraspinally and can be activated by a variety of ways including positive mental imagery. However, its exact mechanisms remain unknown. We investigated, using a longitudinal fMRI design, the brain activity leading up and in response to painful electrical stimulation when applying positive mental imagery before and after undergoing a previously established RIII-feedback paradigm. Time course analysis of the time preceding painful stimulation shows increased haemodynamic activity during the application of the strategy in the PFC, ACC, insula, thalamus, and hypothalamus. Time course analysis of the reaction to painful stimulation shows decreased reaction post-training in brainstem and thalamus, as well as the insula and dorsolateral PFC. Our work suggests that feedback training increases activity in areas involved in pain inhibition, while simultaneously decreasing the reaction to painful stimuli in brain areas related to pain processing, which points to an activation of decreased spinal nociception. We further suggest that the insula and the thalamus may play a more important role in pain modulation than previously assumed.

Does pain hurt more in Spanish? The neurobiology of pain among Spanish-English bilingual adults

We previously found Spanish-English bilingual adults reported higher pain intensity when exposed to painful heat in the language of their stronger cultural orientation. Here, we elucidate brain systems involved in language-driven alterations in pain responses. During separate English- and Spanish-speaking fMRI scanning runs, 39 (21 female) bilingual adults rated painful heat intermixed between culturally evocative images and completed sentence reading tasks. Surveys of cultural identity and language use measured relative preference for US-American vs Hispanic culture (cultural orientation). Participants produced higher intensity ratings in Spanish compared to English. Group-level whole-brain differences in pain-evoked activity between languages emerged in somatosensory, cingulate, precuneus and cerebellar cortex. Regions of interest associated with semantic, attention and somatosensory processing showed higher average pain-evoked responses in participants' culturally preferred language, as did expression of a multivariate pain-predictive pattern. Follow-up moderated mediation analyses showed somatosensory activity mediated language effects on pain intensity, particularly for Hispanic oriented participants. These findings relate to distinct ('meddler', 'spotlight' and 'inducer') hypotheses about the nature of language effects on perception and cognition. Knowledge of language influences on pain could improve efficacy of culturally sensitive treatment approaches across the diversity of Hispanic adults to mitigate documented health disparities in this population.

Graded brain fMRI response to somatic and visual acupuncture stimulation

Increased stimulation can enhance acupuncture clinical response; however, the impact of acupuncture stimulation as "dosage" has rarely been studied. Furthermore, acupuncture can include both somatic and visual components. We assessed both somatic and visual acupuncture dosage effects on sensory ratings and brain response. Twenty-four healthy participants received somatic (needle inserted, manually stimulated) and visual (needle video, no manual stimulation) acupuncture over the leg at three different dosage levels (control, low-dose, and high-dose) during functional magnetic resonance imaging (fMRI). Participants reported the perceived deqi sensation for each acupuncture dose level. Blood-oxygen-level dependent imaging data were analyzed by general linear model and multivariate pattern analysis. For both somatic and visual acupuncture, reported deqi sensation increased with increased dosage of acupuncture stimulation. Brain fMRI analysis demonstrated that higher dosage of somatic acupuncture produced greater brain responses in sensorimotor processing areas, including anterior and posterior insula and secondary somatosensory cortex. For visual acupuncture, higher dosage of stimulation produced greater brain responses in visual-processing areas, including the middle temporal visual areas (V5/MT+) and occipital cortex. Psychophysical and psychophysiological responses to both somatic and visual acupuncture were graded in response to higher doses. Our findings suggest that acupuncture response may be enhanced by the dosage of needling-specific and nonspecific components, represented by different neural mechanisms.

Neural signatures of emotional inference and experience align during social consensus

Humans seamlessly transform dynamic social signals into inferences about the internal states of the people around them. To understand the neural processes that sustain this transformation, we collected fMRI data from participants (N = 100) while they rated the emotional intensity of people (targets) describing significant life events. Targets rated themselves on the same scale to indicate the intended "ground truth" emotional intensity of their videos. Next, we developed two multivariate models of observer brain activity- the first predicted the "ground truth" (r = 0.50, p < 0.0001) and the second predicted observer inferences (r = 0.53, p < 0.0001). When individuals make more accurate inferences, there is greater moment-by-moment concordance between these two models, suggesting that an observer's brain activity contains latent representations of other people's emotional states. Using naturalistic socioemotional stimuli and machine learning, we developed reliable brain signatures that predict what an observer thinks about a target, what the target thinks about themselves, and the correspondence between them. These signatures can be applied in clinical data to better our understanding of socioemotional dysfunction.

Impact of central sensitization on pain, disability and psychological distress in patients with knee osteoarthritis and chronic low back pain

BACKGROUND

Central sensitization (CS) is becoming increasingly recognized as a significant factor in many chronic pain conditions, including knee osteoarthritis (KOA) and chronic low back pain (CLBP). Yet it presently remains unclear how strong is the involvement of CS in KOA and CLBP and which factors are involved in CS in these two chronic disabling diseases.

METHODS

This is a cross-sectional study in which included a total of 178 patients with KOA and 118 patients with CLBP. Inclusion criteria for eligible participants for the KOA group were a confirmed diagnosis of KOA according to the American College of Rheumatology criteria, and for the CLBP group a chronic low back pain for more than 3 months. Subjects were excluded if they presented with a diagnosed psychiatric disorder or if they lacked the capacity to provide informed consent, understand study questionnaires or perform physical performance tests. In each group, were assessed; CS-related symptoms using the Central Sentization Inventory (CSI); demographic and clinical characteristics such as disease duration, pain intensity on a visual analog scale, self-reported function using the Lequesne index for KOA patients and the Oswestry Disability index for CLBP patients, and physical performance with the 6 minutes' walk test; as well as psychosocial risk factors using the Patient Health Questionnaire for depression (PHQ-9), the Generalized Anxiety Disorder (GAD-7) and the Pain Catastrophizing Scale (PCS).

RESULTS

CSI scores significantly correlated with pain intensity and disability in KOA and CLBP patients, and were highly correlated with self-reported symptoms of depression, anxiety and pain catastrophizing. Depression significantly predicted the CSI score in both groups.

CONCLUSION

These findings provide further evidence for the impact of CS on pain, function and physical performance in KOA and CLBP patients. Psychosocial symptoms such as pain catastrophizing, anxiety and depression should also be considered as they are also associated with CS.

Precision, integrative medicine for pain management in sickle cell disease

Sickle cell disease (SCD) is a prevalent and complex inherited pain disorder that can manifest as acute vaso-occlusive crises (VOC) and/or chronic pain. Despite their known risks, opioids are often prescribed routinely and indiscriminately in managing SCD pain, because it is so often severe and debilitating. Integrative medicine strategies, particularly non-opioid therapies, hold promise in safe and effective management of SCD pain. However, the lack of evidence-based methods for managing SCD pain hinders the widespread implementation of non-opioid therapies. In this review, we acknowledge that implementing personalized pain treatment strategies in SCD, which is a guideline-recommended strategy, is currently fraught with limitations. The full implementation of pharmacological and biobehavioral pain approaches targeting mechanistic pain pathways faces challenges due to limited knowledge and limited financial and personnel support. We recommend personalized medicine, pharmacogenomics, and integrative medicine as aspirational strategies for improving pain care in SCD. As an organizing model that is a comprehensive framework for classifying pain subphenotypes and mechanisms in SCD, and for guiding selection of specific strategies, we present evidence updating pain research pioneer Richard Melzack's neuromatrix theory of pain. We advocate for using the updated neuromatrix model to subphenotype individuals with SCD, to better select personalized multimodal treatment strategies, and to identify research gaps fruitful for exploration. We present a fairly complete list of currently used pharmacologic and non-pharmacologic SCD pain therapies, classified by their mechanism of action and by their hypothesized targets in the updated neuromatrix model.

Prediction of disease severity using serum biomarkers in patients with mild-moderate Atopic Dermatitis: A pilot study

Atopic dermatitis (AD) is an inflammatory skin condition that relies largely on subjective evaluation of clinical signs and symptoms for diagnosis and severity assessment. Using multivariate data, we attempted to construct prediction models that can diagnose the disease and assess its severity. We combined data from 28 mild-moderate AD patients and 20 healthy controls (HC) to create random forest models for classification (AD vs. HC) and regression analysis to predict symptom severities. The classification model outperformed the random permutation model significantly (area under the curve: 0.85 ± 0.10 vs. 0.50 ± 0.15; balanced accuracy: 0.81 ± 0.15 vs. 0.50 ± 0.15). Correlation analysis revealed a significant positive correlation between measured and predicted total SCORing Atopic Dermatitis score (SCORAD; r = 0.43), objective SCORAD (r = 0.53), eczema area and severity index scores (r = 0.58, each p < 0.001), but not between measured and predicted itch ratings (r = 0.21, p = 0.18). We developed and tested multivariate prediction models and identified important features using a variety of serum biomarkers, implying that discovering the deep-branching relationships between clinical measurements and serum measurements in mild-moderate AD patients may be possible using a multivariate machine learning method. We also suggest future methods for utilizing machine learning algorithms to enhance drug target selection, diagnosis, prognosis, and customized treatment in AD.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a lateral aspect of the right dorsolateral prefrontal cortex (latDLPFC) in migraine patients. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this latDLPFC region, and diffusion weighted imaging (DWI) verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Topological Data Analysis for Multivariate Time Series Data

Over the last two decades, topological data analysis (TDA) has emerged as a very powerful data analytic approach that can deal with various data modalities of varying complexities. One of the most commonly used tools in TDA is persistent homology (PH), which can extract topological properties from data at various scales. The aim of this article is to introduce TDA concepts to a statistical audience and provide an approach to analyzing multivariate time series data. The application's focus will be on multivariate brain signals and brain connectivity networks. Finally, this paper concludes with an overview of some open problems and potential application of TDA to modeling directionality in a brain network, as well as the casting of TDA in the context of mixed effect models to capture variations in the topological properties of data collected from multiple subjects.

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.

Functional imaging studies of acute administration of classic psychedelics, ketamine, and MDMA: Methodological limitations and convergent results

Functional magnetic resonance imaging (fMRI) is increasingly used to non-invasively study the acute impact of psychedelics on the human brain. While fMRI is a promising tool for measuring brain function in response to psychedelics, it also has known methodological challenges. We conducted a systematic review of fMRI studies examining acute responses to experimentally administered psychedelics in order to identify convergent findings and characterize heterogeneity in the literature. We reviewed 91 full-text papers; these studies were notable for substantial heterogeneity in design, task, dosage, drug timing, and statistical approach. Data recycling was common, with 51 unique samples across 91 studies. Fifty-seven studies (54%) did not meet contemporary standards for Type I error correction or control of motion artifact. Psilocybin and LSD were consistently reported to moderate the connectivity architecture of the sensorimotor-association cortical axis. Studies also consistently reported that ketamine administration increased activation in the dorsomedial prefrontal cortex. Moving forward, use of best practices such as pre-registration, standardized image processing and statistical testing, and data sharing will be important in this rapidly developing field.

Neuroimaging profiles of the negative affective network predict anxiety severity in patients with chronic insomnia disorder: A machine learning study

BACKGROUND

Sleep is instrumental in safeguarding emotional well-being. While the susceptibility to both insomnia and anxiety has been demonstrated to involve intricate brain systems, the neuroimaging profile of chronic insomnia disorder with comorbid anxiety symptoms (CID-A) remains unexplored. Employing machine learning methodologies, this study aims to elucidate the distinct neural substrates underlying CID-A and to investigate whether these cerebral markers can prognosticate anxiety symptoms in patients with insomnia.

METHODS

Functional magnetic resonance imaging (fMRI) data were procured from a relatively large cohort (dataset 1) comprised of 47 CID-A patients, 49 CID patients without anxiety (CID-NA), and 48 good sleeper controls (GSC). Aberrant cerebral functional alterations were assessed through functional connectivity strength (FCS) and resting-state functional connectivity (rsFC). Subsequently, Support Vector Regression (SVR) models were constructed to predict anxiety symptoms in CID patients based on neuroimaging features, which were validated utilizing an external cohort (dataset 2).

RESULTS

In comparison to CID-NA and GSC subjects, CID-A patients exhibited heightened FCS in the right dorsomedial prefrontal cortex (DMPFC), a central hub within the negative affective network. Moreover, the SVR models revealed that DMPFC-related rsFC/FCS features could be employed to predict anxiety symptoms in two independent cohorts of CID patients.

LIMITATION

Modifications in brain functionality might vary across insomnia subtypes.

CONCLUSION

The present findings suggest a potential negative affective network model for the neuropathophysiology of CID accompanied by anxiety. Importantly, the negative affective network pattern may serve as a predictor for anxiety symptoms in CID patients.

Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings

Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks' relationships and facilitate interventions to treat chronic pain. However, studies using high spatial and temporal resolution methods to investigate the neural encoding of pain and its psychophysical correlates have been limited. We recorded from intracranial stereo-EEG (sEEG) electrodes implanted in sixteen different brain regions of twenty patients who underwent psychophysical pain testing consisting of a tonic thermal stimulus to the hand. Broadband high-frequency local field potential amplitude (HFA; 70-150 Hz) was isolated to investigate the relationship between the ongoing neural activity and the resulting psychophysical pain evaluations. Two different generalized linear mixed-effects models (GLME) were employed to assess the neural representations underlying binary and graded pain psychophysics. The first model examined the relationship between HFA and whether the patient responded "yes" or "no" to whether the trial was painful. The second model investigated the relationship between HFA and how painful the stimulus was rated on a visual analog scale. GLMEs revealed that HFA in the inferior temporal gyrus (ITG), superior frontal gyrus (SFG), and superior temporal gyrus (STG) predicted painful responses at stimulus onset. An increase in HFA in the orbitofrontal cortex (OFC), SFG, and striatum predicted pain responses at stimulus offset. Numerous regions, including the anterior cingulate cortex, hippocampus, IFG, MTG, OFC, and striatum, predicted the pain rating at stimulus onset. However, only the amygdala and fusiform gyrus predicted increased pain ratings at stimulus offset. We characterized the spatiotemporal representations of binary and graded painful responses during tonic pain stimuli. Our study provides evidence from intracranial recordings that the neural encoding of psychophysical pain changes over time during a tonic thermal stimulus, with different brain regions being predictive of pain at the beginning and end of the stimulus.

How does feeling pain look like in depression: A review of functional neuroimaging studies

INTRODUCTION

Major Depression Disorder (MDD) and pain appear to be reciprocal risk factors and sharing common neuroanatomical pathways and biological substrates. However, the role of MDD on pain processing remains still unclear. Therefore, this review aims to focus on the effect of depression on pain anticipation, and perception, before and after treatment, through functional magnetic resonance imaging (fMRI).

METHODS

A bibliographic search was conducted on PubMed, Scopus and Web of Science, looking for fMRI studies exploring pain processing in MDD patients.

RESULTS

Amongst the 602 studies retrieved, 12 met the inclusion criteria. In terms of pain perception, studies evidenced that MDD patients generally presented increased activation in brain regions within the prefrontal cortex, insula and in the limbic system (such as amygdala, hippocampus) and occipital cortex. The studies investigating the effect of antidepressant treatment evidenced a reduced activation in areas such as insula, anterior cingulate, and prefrontal cortices. In terms of pain anticipation, contrasting results were evidenced in MDD patients, which presented both increased and decreased activity in the prefrontal cortex, the insula and the temporal lobe, alongside with increased activity in the anterior cingulate cortex, the frontal gyrus and occipital lobes.

LIMITATIONS

The small number of included studies, the heterogeneous approaches of the studies might limit the conclusions of this review.

CONCLUSIONS

Acute pain processing in MDD patients seems to involve numerous and different brain areas. However, more specific fMRI studies with a more homogeneous population and rigorous approach should be conducted to better highlight the effect of depression on pain processing.

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients

Introduction

Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known.

Methods

We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data.

Results

As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia.

Discussion

These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.

Changes of cerebral functional connectivity induced by foot reflexology in a RCT

Non-Pharmacological Interventions (NPIs) are increasingly being introduced into healthcare, but their mechanisms are unclear. In this study, 30 healthy participants received foot reflexology (FR) and sham massage, and went through a resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate NPIs effect on brain. Rs-fMRI revealed an effect of both NPIs on functional connectivity with changes occurring in the default-mode network, the sensorimotor network and a Neural Network Correlates of Pain (NNCP-a newly discovered network showing great robustness). Even if no differences were found between FR and SM, this study allowed to report brain biomarkers of well-being as well as the safety of NPIs. In further research, it could be relevant to study it in patients to look for a true reflexology induced-effect dependent of patient reported outcomes. Overall, these findings enrich the understanding of the neural correlates of well-being experienced with NPIs and provided insight into the basis of the mechanisms of NPIs.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Pediatric Neural Changes to Physical and Emotional Pain After Intensive Interdisciplinary Pain Treatment: A Pilot Study

Brain areas activated during pain can contribute to enhancing or reducing the pain experience, showing a potential connection between chronic pain and the neural response to pain in adolescents and youth. This study examined changes in brain activation associated with experiencing physical pain, and the observation of physical and emotional pain in others, by using functional magnetic resonance imaging (fMRI) before and after intensive interdisciplinary pain treatment (IIPT). Eighteen youth (age 14 to 18) with widespread chronic pain completed fMRI testing before and after IIPT to assess changes in brain activation in response to physical and emotional pain. Broadly, brain activation changes were observed in frontal, somatosensory, and limbic regions. These changes suggest improvements in descending pain modulation via thalamus and caudate, and the different pattern of brain activation after treatment suggests better discrimination between physical and emotional pain. Brain activation changes were also correlated with improvements in clinical outcomes of catastrophizing (reduced activation in right caudate, right mid-cingulate, and postcentral gyrus) and pain-related disability (increased activation in precentral gyrus, left hippocampus, right middle occipital cortex, and left superior frontal gyrus). These changes support interpretation that reduced brain protective responses to pain were associated with treatment-related improvements. This pilot study highlights the need for larger trials designed to better understand the brain mechanisms involved in pediatric widespread pain treatment.

Brain mechanisms associated with facial encoding of affective states

Affective states are typically accompanied by facial expressions, but these behavioral manifestations are highly variable. Even highly arousing and negative valent experiences, such as pain, show great instability in facial affect encoding. The present study investigated which neural mechanisms are associated with variations in facial affect encoding by focusing on facial encoding of sustained pain experiences. Facial expressions, pain ratings, and brain activity (BOLD-fMRI) during tonic heat pain were recorded in 27 healthy participants. We analyzed facial expressions by using the Facial Action Coding System (FACS) and examined brain activations during epochs of painful stimulation that were accompanied by facial expressions of pain. Epochs of facial expressions of pain were coupled with activity increase in motor areas (M1, premotor and SMA) as well as in areas involved in nociceptive processing, including primary and secondary somatosensory cortex, posterior and anterior insula, and the anterior part of the mid-cingulate cortex. In contrast, prefrontal structures (ventrolateral and medial prefrontal) were less activated during incidences of facial expressions, consistent with a role in down-regulating facial displays. These results indicate that incidences of facial encoding of pain reflect activity within nociceptive pathways interacting or possibly competing with prefrontal inhibitory systems that gate the level of expressiveness.

Beyond the brain localization of complex traits: Distributed white matter markers of personality

OBJECTIVE

Extensive work in personality neuroscience has shown mixed results in the ability to localize reliable relationships between personality traits and neuroimaging measures. However, recent work in translational neuroimaging has recognized that multifaceted psychological dispositions are not represented in discrete, highly localized brain areas. As such, standard univariate neuroimaging analyses may not be well-suited for capturing broad personality traits supported by distributed networks.

METHOD

The present study uses an out-of-sample predictive modeling approach to identify multivariate signatures of Big Five personality traits within the structural integrity of white matter pathways using diffusion magnetic resonance imaging. In Study 1 (N = 491), we trained a ridge regression model to predict each of the Big Five traits and tested these models in an independent hold-out subsample.

RESULTS

We found that models for both Neuroticism and Openness were significantly related to predictive accuracy in the hold-out sample. Study 2 (N = 108) applied Study 1's predictive models to an independent set of data collected on a different scanner and using a different Big Five scale. Here, we found that the model for Neuroticism remained a significant predictor of individual difference.

CONCLUSION

Our findings provide evidence that this white matter signature of Neuroticism generalizes across differences in measurement and samples.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Personalized treatment of neuropathic pain: Where are we now?

BACKGROUND

The treatment of neuropathic pain remains a major unmet need that the development of personalized and refined treatment strategies may contribute to address.

DATABASE

In this narrative review, we summarize the various approaches based on objective biomarkers or clinical markers that could be used.

RESULTS

In principle, the validation of objective biomarkers would be the most robust approach. However, although promising results have been reported demonstrating a potential value of genomics, anatomical or functional markers, the clinical validation of these markers has only just begun. Thus, most of the strategies documented to date have been based on the development of clinical markers. In particular, many studies have suggested that the identification of specific subgroups of patients presenting with specific combinations of symptoms and signs would be a relevant approach. Two main approaches have been used to identify relevant sensory profiles: quantitative sensory testing and specific patients reported outcomes based on description of pain qualities.

CONCLUSION

We discuss here the advantages and limitations of these approaches, which are not mutually exclusive.

SIGNIFICANCE

Recent data indicate that various new treatment strategies based on predictive biological and/or clinical markers could be helpful to better personalized and therefore improve the management of neuropathic pain.

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses show that these effects are often small. We analyzed placebo analgesia in a large fMRI study (N = 392), including placebo effects on brain responses to noxious stimuli. Placebo treatment caused robust analgesia in both conditioned thermal and unconditioned mechanical pain. Placebo did not decrease fMRI activity in nociceptive pain regions, including the Neurologic Pain Signature (NPS) and pre-registered spinothalamic pathway regions, with strong support from Bayes Factor analyses. However, placebo treatment affected activity in pre-registered analyses of a second neuromarker, the Stimulus Intensity Independent Pain Signature (SIIPS), and several associated a priori brain regions related to motivation and value, in both thermal and mechanical pain. Individual differences in behavioral analgesia were correlated with neural changes in both thermal and mechanical pain. Our results indicate that processes related to affective and cognitive aspects of pain primarily drive placebo analgesia.

Microstructural Changes in the Spinothalamic Tract of CPSS Patients: Preliminary Results from a Single-Center Diffusion-Weighted Magnetic Resonance Imaging Study

INTRODUCTION

Chronic pain after spinal surgery (CPSS), formerly known as failed back surgery syndrome, encompasses a variety of highly incapacitating chronic pain syndromes emerging after spinal surgery. The intractability of CPSS makes objective parameters that could aid classification and treatment essential. In this study, we investigated the use of cerebral diffusion-weighted magnetic resonance imaging.

METHODS

Cerebral 3T diffusion-weighted (DW-) MRI data from adult CPSS patients were assessed and compared with those of healthy controls matched by age and gender. Only imaging data without relevant artefacts or significant pathologies were included. Apparent diffusion coefficient (ADC) maps were calculated from the b0 and b1000 values using nonlinear regression. After skull stripping and affine registration of all imaging data, ADC values for fifteen anatomical regions were calculated and analyzed with independent samples T-tests.

RESULTS

A total of 32 subjects were included (sixteen CPSS patients and sixteen controls). The mean ADC value of the spinothalamic tract was found to be significantly higher in CPSS patients compared with in healthy controls (p = 0.013). The other anatomical regions did not show statistically different ADC values between the two groups.

CONCLUSION

Our results suggest that patients suffering from CPSS are subject to microstructural changes, predominantly within the cerebral spinothalamic tract. Additional research could possibly lead to imaging biomarkers derived from ADC values in CPSS patients.

Human OPRM1 and murine Oprm1 promoter driven viral constructs for genetic access to μ-opioidergic cell types

With concurrent global epidemics of chronic pain and opioid use disorders, there is a critical need to identify, target and manipulate specific cell populations expressing the mu-opioid receptor (MOR). However, available tools and transgenic models for gaining long-term genetic access to MOR+ neural cell types and circuits involved in modulating pain, analgesia and addiction across species are limited. To address this, we developed a catalog of MOR promoter (MORp) based constructs packaged into adeno-associated viral vectors that drive transgene expression in MOR+ cells. MORp constructs designed from promoter regions upstream of the mouse Oprm1 gene (mMORp) were validated for transduction efficiency and selectivity in endogenous MOR+ neurons in the brain, spinal cord, and periphery of mice, with additional studies revealing robust expression in rats, shrews, and human induced pluripotent stem cell (iPSC)-derived nociceptors. The use of mMORp for in vivo fiber photometry, behavioral chemogenetics, and intersectional genetic strategies is also demonstrated. Lastly, a human designed MORp (hMORp) efficiently transduced macaque cortical OPRM1+ cells. Together, our MORp toolkit provides researchers cell type specific genetic access to target and functionally manipulate mu-opioidergic neurons across a range of vertebrate species and translational models for pain, addiction, and neuropsychiatric disorders.

Lifeworlds in pain: a principled method for investigation and intervention

The experience of pain spans biological, psychological and sociocultural realms, both basic and complex, it is by turns necessary and devastating. Despite an extensive knowledge of the constituents of pain, the ability to translate this into effective intervention remains limited. It is suggested that current, multiscale, medical approaches, largely informed by the biopsychosocial (BPS) model, attempt to integrate knowledge but are undermined by an epistemological obligation, one that necessitates a prior isolation of the constituent parts. To overcome this impasse, we propose that an anthropological stance needs to be taken, underpinned by a Bayesian apparatus situated in computational psychiatry. Here, pain is presented within the context of lifeworlds, where attention is shifted away from the constituents of experience (e.g. nociception, reward processing and fear-avoidance), towards the dynamic affiliation that occurs between these processes over time. We argue that one can derive a principled method of investigation and intervention for pain from modelling approaches in computational psychiatry. We suggest that these modelling methods provide the necessary apparatus to navigate multiscale ontology and epistemology of pain. Finally, a unified approach to the experience of pain is presented, where the relational, inter-subjective phenomenology of pain is brought into contact with a principled method of translation; in so doing, revealing the conditions and possibilities of lifeworlds in pain.

Mediators of the association between childhood trauma and pain sensitivity in adulthood: a Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network analysis

ABSTRACT

Urologic chronic pelvic pain syndrome (UCPPS) is a complex, debilitating condition in which patients often report nonpelvic pain in addition to localized pelvic pain. Understanding differential predictors of pelvic pain only vs widespread pain may provide novel pathways for intervention. This study leveraged baseline data from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network's Symptom Pattern Study to investigate the impact of childhood sexual and nonsexual violent trauma on pelvic and nonpelvic pain sensitivity among adult patients with UCPPS, as well as potential mediators of this association. Study participants who met inclusion criteria for UCPPS completed questionnaires assessing childhood and recent trauma, affective distress, cognitive dysfunction, and generalized sensory sensitivity. Experimental pain sensitivity was also evaluated using standardized pressure pain applied to the pubic region and the arm. Bivariate analyses showed that childhood violent trauma was associated with more nonviolent childhood trauma, more recent trauma, poorer adult functioning, and greater pain sensitivity at the pubic region, but not pain sensitivity at the arm. Path analysis suggested that childhood violent trauma was indirectly associated with pain sensitivity at both sites and that this indirect association was primarily mediated by generalized sensory sensitivity. More experiences of recent trauma also contributed to these indirect effects. The findings suggest that, among participants with UCPPS, childhood violent trauma may be associated with heightened pain sensitivity to the extent that trauma history is associated with a subsequent increase in generalized sensory sensitivity.

Neural processing of pain-related distress to neck-specific movements in people with chronic whiplash-associated disorders

ABSTRACT

Pain-related distress contributes to long-term disability in chronic whiplash-associated disorders. Recently, neuroimaging studies have revealed altered neural responses to viewing pictures of movements associated with back pain in key regions for threat and affective processing. In this study, we examined neural correlates of imagining neck-specific movements designed to elicit pain-related distress in individuals with whiplash-associated disorders (n = 63) when compared with that in sex-matched pain-free controls (n = 32). In the scanner, participants were presented with neck-specific movement-related pictures divided into 3 categories (high fear, moderate-fear, and neutral control pictures) and asked to imagine how they would feel if they were performing the movement. Whole-brain analyses revealed greater differential activation (high-fear vs neutral) in individuals with whiplash-associated disorders when compared with that in pain-free controls in 6 clusters including right and left postcentral gyri, left parietal operculum, dorsal precuneus, left superior frontal gyrus/anterior cingulate cortex, and posterior cingulate cortex/ventral precuneus. For the contrast moderate-fear vs neutral, patients showed greater differential activation than controls in the right and left posterolateral cerebellum. Activation patterns in the precuneus and posterior cingulate cortex were negatively associated with pain-related fear, but no other correlations were observed. Together, the findings suggest that when conceptualizing neck-specific movements associated with pain, people with chronic whiplash-associated disorders may predict-and potentially amplify-their sensory and affective consequences and therewith trigger dysfunctional affective and/or behavioral responses. Herewith, we provide new insights into the neural mechanisms underlying chronic pain in people with whiplash-associated disorders, pointing towards a complex interplay between cognitive/affective and sensorimotor circuitry.

Brain mediators of negative affect-induced physical symptom reporting in patients with functional somatic syndromes

Functional somatic syndromes (FSS) include fibromyalgia, irritable bowel syndrome (IBS), and others. In FSS patients, merely viewing negative affective pictures can elicit increased physical symptoms. Our aim was to investigate the neural mechanisms underlying such negative affect-induced physical symptoms in FSS patients. Thirty patients with fibromyalgia and/or IBS and 30 healthy controls (all women) watched neutral, positive and negative affective picture blocks during functional MRI scanning and rated negative affect and physical symptoms after every block. We compared brain-wide activation during negative versus neutral picture viewing in FSS patients versus controls using robust general linear model analysis. Further, we compared neurologic pain signature (NPS), stimulus intensity-independent pain signature (SIIPS) and picture-induced negative emotion signature (PINES) responses to the negative versus neutral affect contrast and investigated whether they mediated between-group differences in affective picture-induced physical symptom reporting. More physical symptoms were reported after viewing negative compared to neutral pictures, and this effect was larger in patients than controls (p = 0.025). Accordingly, patients showed stronger activation in somatosensory regions during negative versus neutral picture viewing. NPS, but not SIIPS nor PINES, responses were higher in patients than controls during negative versus neutral pictures (p = 0.026). These differential NPS responses partially mediated between-group differences in physical symptoms. In conclusion, picture-induced negative affect elicits physical symptoms in FSS patients as a result of activation of somatosensory and nociceptive brain patterns, supporting the idea that affect-driven alterations in processing of somatic signals is a critical mechanism underlying FSS.

Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach

The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alcohol and tobacco has increased to 84% and 12%, respectively. It is well-known that identifying drug consumption patterns in the general population is essential in reducing overall drug consumption. However, existing approaches do not incorporate Machine Learning and/or Deep Data Mining methods in combination with spatial techniques. To enhance our understanding of mental health issues related to PAS and assist in the development of national policies, here we present a novel Deep Neural Network-based Clustering-oriented Embedding Algorithm that incorporates an autoencoder and spatial techniques. The primary goal of our model is to identify general and spatial patterns of drug consumption and abuse, while also extracting relevant features from the input data and identifying clusters during the learning process. As a test case, we used the largest publicly available database of legal and illegal PAS consumption comprising 49,600 Colombian households. We estimated and geographically represented the prevalence of consumption and/or abuse of both PAS and non-PAS, while achieving statistically significant goodness-of-fit values. Our results indicate that region, sex, housing type, socioeconomic status, age, and variables related to household finances contribute to explaining the patterns of consumption and/or abuse of PAS. Additionally, we identified three distinct patterns of PAS consumption and/or abuse. At the spatial level, these patterns indicate concentrations of drug consumption in specific regions of the country, which are closely related to specific geographic locations and the prevailing social and environmental contexts. These findings can provide valuable insights to facilitate decision-making and develop national policies targeting specific groups given their cultural, geographic, and social conditions.

A mesocorticolimbic signature of pleasure in the human brain

Pleasure is a fundamental driver of human behaviour, yet its neural basis remains largely unknown. Rodent studies highlight opioidergic neural circuits connecting the nucleus accumbens, ventral pallidum, insula and orbitofrontal cortex as critical for the initiation and regulation of pleasure, and human neuroimaging studies exhibit some translational parity. However, whether activation in these regions conveys a generalizable representation of pleasure regulated by opioidergic mechanisms remains unclear. Here we use pattern recognition techniques to develop a human functional magnetic resonance imaging signature of mesocorticolimbic activity unique to states of pleasure. In independent validation tests, this signature is sensitive to pleasant tastes and affect evoked by humour. The signature is spatially co-extensive with mu-opioid receptor gene expression, and its response is attenuated by the opioid antagonist naloxone. These findings provide evidence for a basis of pleasure in humans that is distributed across brain systems.

Reproducibility in Neuroimaging Analysis: Challenges and Solutions

Recent years have marked a renaissance in efforts to increase research reproducibility in psychology, neuroscience, and related fields. Reproducibility is the cornerstone of a solid foundation of fundamental research-one that will support new theories built on valid findings and technological innovation that works. The increased focus on reproducibility has made the barriers to it increasingly apparent, along with the development of new tools and practices to overcome these barriers. Here, we review challenges, solutions, and emerging best practices with a particular emphasis on neuroimaging studies. We distinguish 3 main types of reproducibility, discussing each in turn. Analytical reproducibility is the ability to reproduce findings using the same data and methods. Replicability is the ability to find an effect in new datasets, using the same or similar methods. Finally, robustness to analytical variability refers to the ability to identify a finding consistently across variation in methods. The incorporation of these tools and practices will result in more reproducible, replicable, and robust psychological and brain research and a stronger scientific foundation across fields of inquiry.

I Feel! Therefore, I Am from Pain to Consciousness in DOC Patients

Pain assessment and management in patients with disorders of consciousness (DOC) is a challenging and important aspect of care, with implications for detecting consciousness and promoting recovery. This narrative review explores the role of pain in consciousness, the challenges of pain assessment, pharmacological treatment in DOC, and the implications of pain assessment when detecting changes in consciousness. The review discusses the Nociception Coma Scale and its revised version, which are behavioral scales used to assess pain in DOC patients, and the challenges and controversies surrounding the appropriate pharmacological treatment of pain in these patients. Moreover, we highlight recent evidence suggesting that an accurate pain assessment may predict changes in the level of consciousness in unresponsive wakefulness syndrome/vegetative state patients, underscoring the importance of ongoing pain management in these patients.

Breaking Barriers: Artificial Intelligence Interpreting the Interplay between Mental Illness and Pain as Defined by the International Association for the Study of Pain

Low back pain is one of the main causes of motor disabilities and psychological stress, with the painful process encompassing sensory and affective components. Noxious stimuli originate on the periphery; however, the stimuli are recombined in the brain and therefore processed differently due to the emotional environment. To better understand this process, our objective was to develop a mathematical representation of the International Association for the Study of Pain (IASP) model of pain, covering the multidimensional representation of this phenomenon. Data from the Oswestry disability index; the short form of the depression, anxiety, and stress scale; and pain catastrophizing daily questionnaires were collected through online completion, available from 8 June 2022, to 8 April 2023 (1021 cases). Using the information collected, an artificial neural network structure was trained (based on anomaly detection methods) to identify the patterns that emerge from the relationship between the variables. The developed model proved to be robust and able to show the patterns and the relationship between the variables, and it allowed for differentiating the groups with altered patterns in the context of low back pain. The distinct groups all behave according to the main finding that psychological and pain events are directly associated. We conclude that our proposal is effective as it is able to test and confirm the definition of the IASP for the study of pain. Here we show that the fiscal and mental dimensions of pain are directly associated, meaning that mental illness can be an enhancer of pain episodes and functionality.

Resting-state functional magnetic resonance imaging reveals brain remodeling after Tuina therapy in neuropathic pain model

Tuina, a method of traditional Chinese manual manipulation, is an effective alternative therapy for neuropathic pain (NP), but its analgesic mechanism remains unclear. In this study, we used resting-state functional magnetic resonance imaging (R-fMRI) to explore the analgesic mechanism of Tuina in an NP rat model. After undergoing surgery to induce chronic compression of the dorsal root ganglion (CCD), one group of rats underwent Tuina at the ipsilateral BL40 acupoint once a day for 10 min during the 25 days following surgery while another group did not. Behavioral tests were performed at baseline, on the third day following surgery, and once a week for the next 4 weeks. R-fMRI was performed at baseline and 7 days and 28 days following surgery. Behavioral testing revealed that the Tuina group presented a significant response improvement to mechanical and thermal nociception stimuli compared to the untreated group 2 weeks following CCD surgery. Interestingly, rats submitted to Tuina presented higher measures of spontaneous neuronal activity in basal forebrain region, primary somatosensory cortex barrel field, dentate gyrus, secondary somatosensory cortex, striatum, descending corticofugal pathways, and globus pallidum of the left hemisphere 4 weeks after the CCD surgery compared to rats having undergone CCD only. In addition, on the 28th day, the ALFF signals of the left dentate gyrus, left secondary somatosensory cortex, left striatum, and bilateral primary cingulate cortex were significantly increased while those in the right dentate gyrus and bilateral periaqueductal gray were significantly decreased compared to those on the 7th day. Correlation analysis showed that the ALFF values of the left descending corticofugal pathways and globus pallidum had a positive correlation with mechanical withdrawal threshold and paw withdrawal thermal latency tests. Altogether, these results indicate that NPP induced by CCD surgery affects the plasticity of the cerebral cortex, and that Tuina alleviate pain behavior by promoting cortical remodeling.

How Instructions, Learning, and Expectations Shape Pain and Neurobiological Responses

Treatment outcomes are strongly influenced by expectations, as evidenced by the placebo effect. Meta-analyses of clinical trials reveal that placebo effects are strongest in pain, indicating that psychosocial factors directly influence pain. In this review, I focus on the neural and psychological mechanisms by which instructions, learning, and expectations shape subjective pain. I address new experimental designs that help researchers tease apart the impact of these distinct processes and evaluate the evidence regarding the neural mechanisms by which these cognitive factors shape subjective pain. Studies reveal that expectations modulate pain through parallel circuits that include both pain-specific and domain-general circuits such as those involved in affect and learning. I then review how expectations, learning, and verbal instructions impact clinical outcomes, including placebo analgesia and responses to pharmacological treatments, and discuss implications for future work.

Adapting psychedelic medicine for headache and chronic pain disorders

INTRODUCTION

While the majority of current research and development surrounds depression, demoralization, and substance use disorders, there are numerous reports of psychedelics having beneficial effects in other branches of medicine, including for headache disorders and chronic pain.

AREAS COVERED

This perspective reviews conventional forms of treatment for headache and other chronic pain disorders and describes historical, recent, and ongoing investigations of the therapeutic effects of psychedelics in these disorders. The first two clinical trials of psilocybin in headache disorders and recent case reports of psilocybin mushroom self-administration in chronic pain patients are described. This perspective highlights several factors related to the application of psychedelics in chronic pain disorders, comparing this with the standard psychedelic-assisted psychotherapy model of treatment.

EXPERT OPINION

When faced with a more constricted view of psychedelic medicine that features larger doses, underscores subjective effects in the mediation of therapeutic outcomes, and requires adjunctive psychotherapy to ensure safety and efficacy, the application of psychedelics in headache and chronic pain disorders may face challenges. It will be important to allow for flexibility and adaptation in protocols to evaluate different treatment paradigms, mechanisms of action, and the range of pharmacologic and extra-pharmacologic factors that affect psychedelic treatment outcomes.

Altered Dynamic Functional Network Connectivity in Healthy Adults with Acute Pain: Findings from the Human Connectome Project

Characterizing the neural signature of pain and its modulation is critical for assessing treatment efficacy and conducting translational clinical research. However, the dynamics of pain processing in the brain have remained largely unknown. In this study, we employed independent component analysis (ICA) as a data-driven clustering method on resting-state functional magnetic resonance imaging (fMRI) to obtain intrinsic connectivity networks (ICNs) in a cohort of healthy adults from the Human Connectome Project (HCP) who were identified as having acute pain. We examined the temporal dynamic functional network connectivity (dFNC) with sliding time window correlation and k-means clustering, and compared dFNC state properties and meta-state metrics between groups. Results showed that acute pain had a significant impact on dFNC in a common connectivity state (dynamic state 5) among several ICN pairs, including the salience network, default mode network, central executive, dorsal attention networks, and basal ganglia (false discovery rate [FDR]-corrected p of 0.05). Furthermore, healthy adults with and without acute pain exhibited differences in mean dwell time (dynamic state 3), which indicated that individuals with acute pain spent more time in particular states than those without pain. Meta-state dynamic analysis further indicated significant group differences in the number of states (i.e., unique time windows for each subject), changes between states (i.e., number of times each subject changes from one meta-state to other), and total travelled distances. These preliminary results provide new information about time-varying properties of pain states related to acute pain and advocate for further state-based analyses of pain for future pain biomarker discovery and development.

The Secondary Somatosensory Cortex Gates Mechanical and Thermal Sensitivity

The cerebral cortex is vital for the perception and processing of sensory stimuli. In the somatosensory axis, information is received by two distinct regions, the primary (S1) and secondary (S2) somatosensory cortices. Top-down circuits stemming from S1 can modulate mechanical and cooling but not heat stimuli such that circuit inhibition causes blunted mechanical and cooling perception. Using optogenetics and chemogenetics, we find that in contrast to S1, an inhibition of S2 output increases mechanical and heat, but not cooling sensitivity. Combining 2-photon anatomical reconstruction with chemogenetic inhibition of specific S2 circuits, we discover that S2 projections to the secondary motor cortex (M2) govern mechanical and thermal sensitivity without affecting motor or cognitive function. This suggests that while S2, like S1, encodes specific sensory information, that S2 operates through quite distinct neural substrates to modulate responsiveness to particular somatosensory stimuli and that somatosensory cortical encoding occurs in a largely parallel fashion.

Brain-to-brain mechanisms underlying pain empathy and social modulation of pain in the patient-clinician interaction

Social interactions such as the patient-clinician encounter can influence pain, but the underlying dynamic interbrain processes are unclear. Here, we investigated the dynamic brain processes supporting social modulation of pain by assessing simultaneous brain activity (fMRI hyperscanning) from chronic pain patients and clinicians during video-based live interaction. Patients received painful and nonpainful pressure stimuli either with a supportive clinician present (Dyadic) or in isolation (Solo). In half of the dyads, clinicians performed a clinical consultation and intake with the patient prior to hyperscanning (Clinical Interaction), which increased self-reported therapeutic alliance. For the other half, patient-clinician hyperscanning was completed without prior clinical interaction (No Interaction). Patients reported lower pain intensity in the Dyadic, relative to the Solo, condition. In Clinical Interaction dyads relative to No Interaction, patients evaluated their clinicians as better able to understand their pain, and clinicians were more accurate when estimating patients' pain levels. In Clinical Interaction dyads, compared to No Interaction, patients showed stronger activation of the dorsolateral and ventrolateral prefrontal cortex (dlPFC and vlPFC) and primary (S1) and secondary (S2) somatosensory areas (Dyadic-Solo contrast), and clinicians showed increased dynamic dlPFC concordance with patients' S2 activity during pain. Furthermore, the strength of S2-dlPFC concordance was positively correlated with self-reported therapeutic alliance. These findings support that empathy and supportive care can reduce pain intensity and shed light on the brain processes underpinning social modulation of pain in patient-clinician interactions. Our findings further suggest that clinicians' dlPFC concordance with patients' somatosensory processing during pain can be boosted by increasing therapeutic alliance.

Chronic pain, chronic stress and substance use: overlapping mechanisms and implications

Chronic pain is among the most common reasons adults in the U.S. seek medical care. Despite chronic pain's substantial impact on individuals' physical, emotional, and financial wellness, the biologic underpinnings of chronic pain remain incompletely understood. Such deleterious impact on an individuals' wellness is also manifested in the substantial co-occurrence of chronic stress with chronic pain. However, whether chronic stress and adversity and related alcohol and substance misuse increases risk of developing chronic pain, and, if so, what the overlapping psychobiological processes are, is not well understood. Individuals suffering with chronic pain find alleviation through prescription opioids as well as non-prescribed cannabis, alcohol, and other drugs to control pain, and use of these substances have grown significantly. Substance misuse also increases experience of chronic stress. Thus, given the evidence showing a strong correlation between chronic stress and chronic pain, we aim to review and identify overlapping factors and processes. We first explore the predisposing factors and psychologic features common to both conditions. This is followed by examining the overlapping neural circuitry of pain and stress in order to trace a common pathophysiologic processes for the development of chronic pain and its link to substance use. Based on the previous literature and our own findings, we propose a critical role for ventromedial prefrontal cortex dysfunction, an overlapping brain area associated with the regulation of both pain and stress that is also affected by substance use, as key in the risk of developing chronic pain. Finally, we identify the need for future research in exploring the role of medial prefrontal circuits in chronic pain pathology. Critically, in order to alleviate the enormous burden of chronic pain without exacerbating the co-occurring substance misuse crisis, we emphasize the need to find better approaches to treat and prevent chronic pain.

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.

Network targets for therapeutic brain stimulation: towards personalized therapy for pain

Precision neuromodulation of central brain circuits is a promising emerging therapeutic modality for a variety of neuropsychiatric disorders. Reliably identifying in whom, where, and in what context to provide brain stimulation for optimal pain relief are fundamental challenges limiting the widespread implementation of central neuromodulation treatments for chronic pain. Current approaches to brain stimulation target empirically derived regions of interest to the disorder or targets with strong connections to these regions. However, complex, multidimensional experiences like chronic pain are more closely linked to patterns of coordinated activity across distributed large-scale functional networks. Recent advances in precision network neuroscience indicate that these networks are highly variable in their neuroanatomical organization across individuals. Here we review accumulating evidence that variable central representations of pain will likely pose a major barrier to implementation of population-derived analgesic brain stimulation targets. We propose network-level estimates as a more valid, robust, and reliable way to stratify personalized candidate regions. Finally, we review key background, methods, and implications for developing network topology-informed brain stimulation targets for chronic pain.

Detection of brain regions responsible for chronic pain in osteoarthritis: an fMRI-based neuroimaging study using deep learning

INTRODUCTION

Chronic pain is a multifaceted condition that has yet to be fully comprehended. It is frequently linked with a range of disorders, particularly osteoarthritis (OA), which arises from the progressive deterioration of the protective cartilage that cushions the bone endings over time.

METHODS

In this paper, we examine the impact of chronic pain on the brain using advanced deep learning (DL) algorithms that leverage resting-state functional magnetic resonance imaging (fMRI) data from both OA pain patients and healthy controls. Our study encompasses fMRI data from 51 pain patients and 20 healthy subjects. To differentiate chronic pain-affected OA patients from healthy controls, we introduce a DL-based computer-aided diagnosis framework that incorporates Multi-Layer Perceptron and Convolutional Neural Networks (CNN), separately.

RESULTS

Among the examined algorithms, we discovered that CNN outperformed the others and achieved a notable accuracy rate of nearly 85%. In addition, our investigation scrutinized the brain regions affected by chronic pain and successfully identified several regions that have not been mentioned in previous literature, including the occipital lobe, the superior frontal gyrus, the cuneus, the middle occipital gyrus, and the culmen.

DISCUSSION

This pioneering study explores the applicability of DL algorithms in pinpointing the differentiating brain regions in OA patients who experience chronic pain. The outcomes of our research could make a significant contribution to medical research on OA pain patients and facilitate fMRI-based pain recognition, ultimately leading to enhanced clinical intervention for chronic pain patients.