Individual variability in brain representations of pain

Brain effect mechanism of lever positioning manipulation on LDH analgesia based on multimodal MRI: a study protocol

INTRODUCTION

The clinical symptoms of Lumbar Disc Herniation (LDH) can be effectively ameliorated through Lever Positioning Manipulation (LPM), which is closely linked to the brain's pain-regulating mechanisms. Magnetic Resonance Imaging (MRI) offers an objective and visual means to study how the brain orchestrates the characteristics of analgesic effects. From the perspective of multimodal MRI, we applied functional MRI (fMRI) and Magnetic Resonance Spectrum (MRS) techniques to comprehensively evaluate the characteristics of the effects of LPM on the brain region of LDH from the aspects of brain structure, brain function and brain metabolism. This multimodal MRI technique provides a biological basis for the clinical application of LPM in LDH.

METHODS AND ANALYSIS

A total of 60 LDH patients and 30 healthy controls, matched by gender, age, and years of education, will be enrolled in this study. The LDH patients will be divided into two groups (Group 1, n = 30; Group 2, n = 30) using a random number table method. Group 1 will receive LPM treatment once every two days, for a total of 12 times over 4 weeks. Group 2 will receive sham LPM treatment during the same period as Group 1. All 30 healthy controls will be divided into Group 3. Multimodal MRI will be performed on Group 1 and Group 2 at three time points (TPs): before LPM (TP1), after one LPM session (TP2), and after a full course of LPM treatment. The healthy controls (Group 3) will not undergo LPM and will be subject to only a single multimodal MRI scan. Participants in both Group 1 and Group 2 will be required to complete clinical questionnaires. These assessments will focus on pain intensity and functional disorders, using the Visual Analog Scale (VAS) and the Japanese Orthopaedic Association (JOA) scoring systems, respectively.

DISCUSSION

The purpose of this study is to investigate the multimodal brain response characteristics of LDH patients after treatment with LPM, with the goal of providing a biological basis for clinical applications.

TRIAL REGISTRATION NUMBER

https://clinicaltrials.gov/ct2/show/NCT05613179 , identifier: NCT05613179.

Functional and Structural Abnormalities in the Pain Network of Generalized Anxiety Disorder Patients with Pain Symptoms

Pain symptoms significantly impact the well-being and work capacity of individuals with generalized anxiety disorder (GAD), and hinder treatment and recovery. Despite existing literature focusing on the neural substrate of pain and anxiety separately, further exploration is needed to understand the possible neuroimaging mechanisms of the pain symptoms in GAD patients. We recruited 73 GAD patients and 75 matched healthy controls (HC) for clinical assessments, as well as resting-state functional and structural magnetic resonance imaging scans. We defined a pain-related network through a published meta-analysis, including the insula, thalamus, periaqueductal gray, prefrontal cortex, anterior cingulate cortex, amygdala, and hippocampus. Subsequently, we conducted the regional homogeneity (ReHo) and the gray matter volume (GMV) within the pain-related network. Correlation analysis was then employed to explore associations between abnormal regions and self-reported outcomes, assessed using the Patient Health Questionnaire-15 (PHQ-15) and pain scores. We observed significantly increased ReHo in the bilateral insula but decreased GMV in the bilateral thalamus of GAD compared to HC. Further correlation analysis revealed a positive correlation between ReHo of the left anterior insula and pain scores in GAD patients, while a respective negative correlation between GMV of the bilateral thalamus and PHQ-15 scores. In summary, GAD patients exhibit structural and functional abnormalities in pain-related networks. The enhanced ReHo in the left anterior insula is correlated with pain symptoms, which might be a crucial brain region of pain symptoms in GAD.

fMRI, LFP, and anatomical evidence for hierarchical nociceptive routing pathway between somatosensory and insular cortices

The directional organization of multiple nociceptive regions, particularly within obscure operculoinsular areas, underlying multidimensional pain processing remains elusive. This study aims to establish the fundamental organization between somatosensory and insular cortices in routing nociceptive information. By employing an integrated multimodal approach of high-field fMRI, intracranial electrophysiology, and transsynaptic viral tracing in rats, we observed a hierarchically organized connection of S1/S2 → posterior insula → anterior insula in routing nociceptive information. The directional nociceptive pathway determined by early fMRI responses was consistent with that examined by early evoked LFP, intrinsic effective connectivity, and anatomical projection, suggesting fMRI could provide a valuable facility to discern directional neural circuits in animals and humans non-invasively. Moreover, our knowledge of the nociceptive hierarchical organization of somatosensory and insular cortices and the interface role of the posterior insula may have implications for the development of targeted pain therapies.

Distributed neural representations of conditioned threat in the human brain

Detecting and responding to threat engages several neural nodes including the amygdala, hippocampus, insular cortex, and medial prefrontal cortices. Recent propositions call for the integration of more distributed neural nodes that process sensory and cognitive facets related to threat. Integrative, sensitive, and reproducible distributed neural decoders for the detection and response to threat and safety have yet to be established. We combine functional MRI data across varying threat conditioning and negative affect paradigms from 1465 participants with multivariate pattern analysis to investigate distributed neural representations of threat and safety. The trained decoders sensitively and specifically distinguish between threat and safety cues across multiple datasets. We further show that many neural nodes dynamically shift representations between threat and safety. Our results establish reproducible decoders that integrate neural circuits, merging the well-characterized 'threat circuit' with sensory and cognitive nodes, discriminating threat from safety regardless of experimental designs or data acquisition parameters.

A novel theta-controlled vibrotactile brain-computer interface to treat chronic pain: a pilot study

Limitations in chronic pain therapies necessitate novel interventions that are effective, accessible, and safe. Brain-computer interfaces (BCIs) provide a promising modality for targeting neuropathology underlying chronic pain by converting recorded neural activity into perceivable outputs. Recent evidence suggests that increased frontal theta power (4-7 Hz) reflects pain relief from chronic and acute pain. Further studies have suggested that vibrotactile stimulation decreases pain intensity in experimental and clinical models. This longitudinal, non-randomized, open-label pilot study's objective was to reinforce frontal theta activity in six patients with chronic upper extremity pain using a novel vibrotactile neurofeedback BCI system. Patients increased their BCI performance, reflecting thought-driven control of neurofeedback, and showed a significant decrease in pain severity (1.29 ± 0.25 MAD, p = 0.03, q = 0.05) and pain interference (1.79 ± 1.10 MAD p = 0.03, q = 0.05) scores without any adverse events. Pain relief significantly correlated with frontal theta modulation. These findings highlight the potential of BCI-mediated cortico-sensory coupling of frontal theta with vibrotactile stimulation for alleviating chronic pain.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population-rather than individual-based inferences due to limited within-individual sampling. Here, three densely-sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely-sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously-unrecognized inter-individual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

Pain-sensorimotor interactions: New perspectives and a new model

How pain and sensorimotor behavior interact has been the subject of research and debate for many decades. This article reviews theories bearing on pain-sensorimotor interactions and considers their strengths and limitations in the light of findings from experimental and clinical studies of pain-sensorimotor interactions in the spinal and craniofacial sensorimotor systems. A strength of recent theories is that they have incorporated concepts and features missing from earlier theories to account for the role of the sensory-discriminative, motivational-affective, and cognitive-evaluative dimensions of pain in pain-sensorimotor interactions. Findings acquired since the formulation of these recent theories indicate that additional features need to be considered to provide a more comprehensive conceptualization of pain-sensorimotor interactions. These features include biopsychosocial influences that range from biological factors such as genetics and epigenetics to psychological factors and social factors encompassing environmental and cultural influences. Also needing consideration is a mechanistic framework that includes other biological factors reflecting nociceptive processes and glioplastic and neuroplastic changes in sensorimotor and related brain and spinal cord circuits in acute or chronic pain conditions. The literature reviewed and the limitations of previous theories bearing on pain-sensorimotor interactions have led us to provide new perspectives on these interactions, and this has prompted our development of a new concept, the Theory of Pain-Sensorimotor Interactions (TOPSMI) that we suggest gives a more comprehensive framework to consider the interactions and their complexity. This theory states that pain is associated with plastic changes in the central nervous system (CNS) that lead to an activation pattern of motor units that contributes to the individual's adaptive sensorimotor behavior. This activation pattern takes account of the biological, psychological, and social influences on the musculoskeletal tissues involved in sensorimotor behavior and on the plastic changes and the experience of pain in that individual. The pattern is normally optimized in terms of biomechanical advantage and metabolic cost related to the features of the individual's musculoskeletal tissues and aims to minimize pain and any associated sensorimotor changes, and thereby maintain homeostasis. However, adverse biopsychosocial factors and their interactions may result in plastic CNS changes leading to less optimal, even maladaptive, sensorimotor changes producing motor unit activation patterns associated with the development of further pain. This more comprehensive theory points towards customized treatment strategies, in line with the management approaches to pain proposed in the biopsychosocial model of pain.

Effects of Orange Oil Aromatherapy on Pain and Anxiety During Invasive Interventions in Patients With Hematopoietic Stem Cell Transplants

Invasive interventions, such as peripheral intravenous cannula, port needle placement, and blood collection, are often required for both inpatient and outpatient follow-up patients with hematological malignancies and hematopoietic stem cell transplants. This prospective, randomized controlled experimental study assessed the effect of orange oil inhalation used in aromatherapy on pain and anxiety levels in invasive interventions with hematological malignancies and hematopoietic stem cell transplants. It was conducted prospectively with 80 patients with hematological malignancies who were treated in the adult bone marrow transplant unit and adult hematology service of a private hospital between May 2021 and April 2022. The orange oil inhalation used in aromatherapy was applied to patients in the intervention group. The Visual Analog Scale (VAS) and State-Trait Anxiety Inventory (STAI) were used for data collection. Regarding the personal characteristics of the patients, 42.5% were ≥61 years old, 60% were men, and 85% were married. VAS pain scores of the intervention group were statistically lower than those of the control group (P < .001). However, there was no statistically significant difference in the STAI scores of groups (P >.05). The study results show that orange oil inhalation has been determined to reduce pain during invasive interventions.

Safinamide for pain management in patients with Parkinson's disease

INTRODUCTION

Pain is often neglected in Parkinson's disease (PD), although it impacts most PD patients. While the mechanism of pain in PD is still being studied, various pharmacological, interventional, and alternative treatment options have been offered for pain relief. Safinamide, a recently approved drug for PD, has shown promising results in improving pain in patients with PD. Several clinical studies report changes in pain scores in PD patients treated with safinamide, but these have not been systematically summarized. Therefore, our main goal was to perform a systematic review and statistical analysis of relevant studies.

METHODS

A systematic search of studies was conducted using four databases: Pubmed, Cochrane Library, Google Scholar, and Scopus. The nine included randomized controlled trials did not provide sufficient data for a meta-analysis; therefore, we conducted a qualitative systematic review.

RESULTS

Our results suggest that safinamide at a daily dose of 100mg is more effective for treating PD pain than that of 50mg. Moreover, the reduction in fluctuation-related pain and pain from edema was more consistent when treated with safinamide compared to other PD pain types. We also attempted to suggest a mechanism of action for safinamide on pain processing in the brain, which should be explored in more detail in future studies.

CONCLUSION

Clinical evidence suggests that safinamide may be particularly beneficial for PD patients experiencing fluctuation-related pain and pain from edema, as these subtypes of pain showed greater improvement compared to other types of pain. Based on the findings of the included studies, safinamide appears to relieve the overall pain burden. However, the lack of sufficient data for conducting a meta-analysis highlights the need for future studies to report mean pain scores and their standard deviations.

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.

The role of evolving concepts and new technologies and approaches in advancing pain research, management, and education since the establishment of the International Association for the Study of Pain

ABSTRACT

The decades since the inauguration of the International Association for the Study of Pain have witnessed major advances in scientific concepts (such as the biopsychosocial model and chronic primary pain as a disease in its own right) and in new technologies and approaches (from molecular biology to brain imaging) that have inspired innovations in pain research. These have guided progress in pain management and education about pain for healthcare professionals, the general public, and administrative agencies.

Chronic pain is associated with less grey matter volume in the anterior cingulum, anterior and posterior insula and hippocampus across three different chronic pain conditions

BACKGROUND

Chronic pain of different aetiologies and localization has been associated with less grey matter volume (GMV) in several cortical and subcortical brain areas. Recent meta-analyses reported low reproducibility of GMV alterations between studies and pain syndromes.

METHODS

To investigate GMV in common chronic pain conditions defined by body location (chronic back pain, n = 174; migraine, n = 92; craniomandibular disorder, n = 39) compared to controls (n = 296), we conducted voxel-based morphometry and determined GMV from high-resolution cranial MRIs obtained in an epidemiologic survey. Mediation analyses were performed between the presence of chronic pain and GMV testing the mediators stress and mild depression. The predictability of chronic pain was investigated with binomial logistic regression.

RESULTS

Whole-brain analyses yielded reduced GMV within the left anterior insula and the anterior cingulate cortex, for a ROI approach additionally the left posterior insula and left hippocampus showing less GMV across all patients with chronic pain. The relationship of pain with GMV in the left hippocampus was mediated by self-reported stressors in the last 12 months. Binomial logistic regression revealed a predictive effect for GMV in the left hippocampus and left anterior insula/temporal pole for the presence of chronic pain.

CONCLUSIONS

Chronic pain across three different pain conditions was characterized by less GMV in brain regions consistently described for different chronic pain conditions before. Less GMV in the left hippocampus mediated by experienced stress during the last year might be related to altered pain learning mechanisms in chronic pain patients.

SIGNIFICANCE

Grey matter reorganization could serve as a diagnostic biomarker for chronic pain. In a large cohort, we here replicated findings of less grey matter volume across three pain conditions in the left anterior and posterior insula, anterior cingulate and left hippocampus. Less hippocampal grey matter was mediated by experienced stress.

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.

First-in-human prediction of chronic pain state using intracranial neural biomarkers

Chronic pain syndromes are often refractory to treatment and cause substantial suffering and disability. Pain severity is often measured through subjective report, while objective biomarkers that may guide diagnosis and treatment are lacking. Also, which brain activity underlies chronic pain on clinically relevant timescales, or how this relates to acute pain, remains unclear. Here four individuals with refractory neuropathic pain were implanted with chronic intracranial electrodes in the anterior cingulate cortex and orbitofrontal cortex (OFC). Participants reported pain metrics coincident with ambulatory, direct neural recordings obtained multiple times daily over months. We successfully predicted intraindividual chronic pain severity scores from neural activity with high sensitivity using machine learning methods. Chronic pain decoding relied on sustained power changes from the OFC, which tended to differ from transient patterns of activity associated with acute, evoked pain states during a task. Thus, intracranial OFC signals can be used to predict spontaneous, chronic pain state in patients.