Learning to identify CNS drug action and efficacy using multistudy fMRI data

Systematic review and co-ordinate based meta-analysis to summarize the utilization of functional brain imaging in conjunction with human models of peripheral and central sensitization

BACKGROUND AND OBJECTIVE

Functional magnetic resonance imaging, in conjunction with models of peripheral and/or central sensitization, has been used to assess analgesic efficacy in healthy humans. This review aims to summarize the use of these techniques to characterize brain mechanisms of hyperalgesia/allodynia and to evaluate the efficacy of analgesics.

DATABASES AND DATA TREATMENT

Searches were performed (PubMed-Medline, Cochrane, Web of Science and Clinicaltrials.gov) to identify and review studies. A co-ordinate based meta-analysis (CBMA) was conducted to quantify neural activity that was reported across multiple independent studies in the hyperalgesic condition compared to control, using GingerALE software.

RESULTS

Of 217 publications, 30 studies met the inclusion criteria. They studied nine different models of hyperalgesia/allodynia assessed in the primary (14) or secondary hyperalgesia zone (16). Twenty-three studies focused on neural correlates of hyperalgesic conditions and showed consistent changes in the somatosensory cortex, prefrontal cortices, insular cortex, anterior cingulate cortex, thalamus and brainstem. The CBMA on 12 studies that reported activation coordinates for a contrast comparing the hyperalgesic state to control produced six activation clusters (significant at false discovery rate of 0.05) with more peaks for secondary (17.7) than primary zones (7.3). Seven studies showed modulation of brain activity by analgesics in five of the clusters but also in four additional regions.

CONCLUSIONS

This meta-analysis revealed substantial but incomplete overlap between brain areas related to neural mechanisms of hyperalgesia and those reflecting the efficacy of analgesic drugs. Studies testing in the secondary zone were more sensitive to evaluate analgesic efficacy on central sensitization at brainstem or thalamocortical levels.

SIGNIFICANCE

Experimental pain models that provide a surrogate for features of pathological pain conditions in healthy humans and functional imaging techniques are both highly valuable research tools. This review shows that when used together, they provide a wealth of information about brain activity during pain states and analgesia. These tools are promising candidates to help bridge the gap between animal and human studies, to improve translatability and provide opportunities for identification of new targets for back-translation to animal studies.

Bibliometric analysis of functional magnetic resonance imaging studies on chronic pain over the past 20 years

PURPOSE

The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain.

METHODS

All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023.

RESULTS

A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain.

CONCLUSIONS

This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain.

Reliability of quantitative sensory testing in the assessment of somatosensory function after high-frequency stimulation-induced sensitisation of central nociceptive pathways

ABSTRACT

The high frequency stimulation (HFS) model can be used alongside quantitative sensory testing (QST) to assess the sensitisation of central nociceptive pathways. However, the validity and between-session reliability of using QST z -score profiles to measure changes in mechanical and thermal afferent pathways in the HFS model are poorly understood. In this study, 32 healthy participants underwent QST before and after HFS (5× 100 Hz trains; 10× electrical detection threshold) in the same heterotopic skin area across 2 repeated sessions. The only mechanical QST z -score profiles that demonstrated a consistent gain of function across repeated test sessions were mechanical pain threshold (MPT) and mechanical pain sensitivity (MPS), which were associated with moderate and good reliability, respectively. There was no relationship between HFS intensity and MPT and MPS z -score profiles. There was no change in low intensity, but a consistent facilitation of high-intensity pin prick stimuli in the mechanical stimulus response function across repeated test sessions. There was no change in cold pain threshold (CPT) and heat pain threshold (HPT) z -score profiles across session 1 and 2, which were associated with moderate and good reliability, respectively. There were inconsistent changes in the sensitivity to innocuous thermal QST parameters, with cool detection threshold (CDT), warm detection threshold (WDT), and thermal sensory limen (TSL) all producing poor reliability. These data suggest that HFS-induced changes in MPS z -score profiles is a reliable way to assess experimentally induced central sensitisation and associated secondary mechanical hyperalgesia in healthy participants.

Effects of remifentanil on brain responses to noxious stimuli during deep propofol sedation

BACKGROUND

The safety of anaesthesia has improved as a result of better control of anaesthetic depth. However, conventional monitoring does not inform on the nature of nociceptive processes during unconsciousness. A means of inferring the quality of potentially painful experiences could derive from analysis of brain activity using neuroimaging. We have evaluated the dose effects of remifentanil on brain response to noxious stimuli during deep sedation and spontaneous breathing.

METHODS

Optimal data were obtained in 26 healthy subjects. Pressure stimulation that proved to be moderately painful before the experiment was applied to the thumbnail. Functional MRI was acquired in 4-min periods at low (0.5 ng ml^-1), medium (1 ng ml^-1), and high (1.5 ng ml^-1) target plasma concentrations of remifentanil at a stable background infusion of propofol adjusted to induce a state of light unconsciousness.

RESULTS

At low remifentanil doses, we observed partial activation in brain areas processing sensory-discriminative and emotional-affective aspects of pain. At medium doses, relevant changes were identified in structures highly sensitive to general brain arousal, including the brainstem, cerebellum, thalamus, auditory and visual cortices, and the frontal lobe. At high doses, no significant activation was observed.

CONCLUSIONS

The response to moderately intense focal pressure in pain-related brain networks is effectively eliminated with safe remifentanil doses. However, the safety margin in deep sedation-analgesia would be narrowed in minimising not only nociceptive responses, but also arousal-related biological stress.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

The Role of fMRI in Drug Development: An Update

Functional magnetic resonance imaging (fMRI) of the brain is a technology that holds great potential for increasing the efficiency of drug development for the central nervous system (CNS). In preclinical studies and both early- and late-phase human trials, fMRI has the potential to improve cross-species translation of drug effects, help to de-risk compounds early in development, and contribute to the portfolio of evidence for a compound's efficacy and mechanism of action. However, to date, the utilization of fMRI in the CNS drug development process has been limited. The purpose of this chapter is to explore this mismatch between potential and utilization. This chapter provides introductory material related to fMRI and drug development, describes what is required of fMRI measurements for them to be useful in a drug development setting, lists current capabilities of fMRI in this setting and challenges faced in its utilization, and ends with directions for future development of capabilities in this arena. This chapter is the 5-year update of material from a previously published workshop summary (Carmichael et al., Drug DiscovToday 23(2):333-348, 2018).

Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders

Despite advances in pharmacology and neuroscience, the path to new medications for psychiatric disorders largely remains stagnated. Drug repurposing offers a more efficient pathway compared with de novo drug discovery with lower cost and less risk. Various computational approaches have been applied to mine the vast amount of biomedical data generated over recent decades. Among these methods, network-based drug repurposing stands out as a potent tool for the comprehension of multiple domains of knowledge considering the interactions or associations of various factors. Aligned well with the poly-pharmacology paradigm shift in drug discovery, network-based approaches offer great opportunities to discover repurposing candidates for complex psychiatric disorders. In this review, we present the potential of network-based drug repurposing in psychiatry focusing on the incentives for using network-centric repurposing, major network-based repurposing strategies and data resources, applications in psychiatry and challenges of network-based drug repurposing. This review aims to provide readers with an update on network-based drug repurposing in psychiatry. We expect the repurposing approach to become a pivotal tool in the coming years to battle debilitating psychiatric disorders.

Role of Brain Imaging in Drug Development for Psychiatry

Background:

Over the last decades, many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited.

Objective:

In this review, we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units.

Conclusion:

Brain imaging technology has revolutionized the study of psychiatric illnesses, and during the last decade, neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to new validated targets for drug development.

The neurologic pain signature responds to nonsteroidal anti-inflammatory treatment vs placebo in knee osteoarthritis

Supplemental Digital Content is Available in the Text.

fMRI-based measures, validated for nociceptive pain, respond to acute osteoarthritis pain, are not sensitive to placebo, and are mild-to-moderately sensitive to naproxen.

Introduction:

Many drug trials for chronic pain fail because of high placebo response rates in primary endpoints. Neurophysiological measures can help identify pain-linked pathophysiology and treatment mechanisms. They can also help guide early stop/go decisions, particularly if they respond to verum treatment but not placebo. The neurologic pain signature (NPS), an fMRI-based measure that tracks evoked pain in 40 published samples and is insensitive to placebo in healthy adults, provides a potentially useful neurophysiological measure linked to nociceptive pain.

Objectives:

This study aims to validate the NPS in knee osteoarthritis (OA) patients and test the effects of naproxen on this signature.

Methods:

In 2 studies (50 patients, 64.6 years, 75% females), we (1) test the NPS and other control signatures related to negative emotion in knee OA pain patients; (2) test the effect of placebo treatments; and (3) test the effect of naproxen, a routinely prescribed nonsteroidal anti-inflammatory drug in OA.

Results:

The NPS was activated during knee pain in OA (d = 1.51, P < 0.001) and did not respond to placebo (d = 0.12, P = 0.23). A single dose of naproxen reduced NPS responses (vs placebo, NPS d = 0.34, P = 0.03 and pronociceptive NPS component d = 0.38, P = 0.02). Naproxen effects were specific for the NPS and did not appear in other control signatures.

Conclusion:

This study provides preliminary evidence that fMRI-based measures, validated for nociceptive pain, respond to acute OA pain, do not appear sensitive to placebo, and are mild-to-moderately sensitive to naproxen.

Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent short-term (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with ≥60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions.

Neuroimaging enters the pain biomarker arena

Neuroimaging methods can be used to identify biomarkers of acute and chronic pain.

Understanding the Psychological, Physiological, and Genetic Factors Affecting Precision Pain Medicine: A Narrative Review

PURPOSE

Precision pain medicine focuses on employing methods to assess each patient individually, identify their risk profile for disproportionate pain and/or the development of chronic pain, and optimize therapeutic strategies to target specific pathological processes underlying chronic pain. This review aims to provide a concise summary of the current body of knowledge regarding psychological, physiological, and genetic determinants of chronic pain related to precision pain medicine.

METHODS

Following the Scale for the Assessment of Narrative Review Articles (SANRA) criteria, we employed PubMed/Medline to identify relevant articles using primary database search terms to query articles such as: precision medicine, non-modifiable factors, pain, anesthesiology, quantitative sensory testing, genetics, pain medicine, and psychological.

RESULTS

Precision pain medicine provides an opportunity to identify populations at risk, develop personalized treatment strategies, and reduce side effects and cost through elimination of ineffective treatment strategies. As in other complex chronic health conditions, there are two broad categories that contribute to chronic pain risk: modifiable and non-modifiable patient factors. This review focuses on three primary determinants of health, representing both modifiable and non-modifiable factors, that may contribute to a patient's profile for risk of developing pain and most effective management strategies: psychological, physiological, and genetic factors.

CONCLUSION

Consideration of these three domains is already being integrated into patient care in other specialties, but by understanding the role they play in development and maintenance of chronic pain, we can begin to implement both precision and personalized treatment regimens.

Precision Psychiatry: Machine learning as a tool to find new pharmacological targets

There is an increasing amount of data arising from neurobehavioral sciences and medical records that cannot be adequately analyzed by traditional research methods. New drugs develop at a slow rate and seem unsatisfactory for the majority of neurobehavioral disorders. Machine learning (ML) techniques, instead, can incorporate psychopathological, computational, cognitive, and neurobiological underpinning knowledge leading to a refinement of detection, diagnosis, prognosis, treatment, research, and support. Machine and deep learning methods are currently used to accelerate the process of discovering new pharmacological targets and drugs.

OBJECTIVE

The present work reviews current evidence regarding the contribution of machine learning to the discovery of new drug targets.

METHODS

Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published until May 2021 were included in this review.

RESULTS

The most significant areas of research are schizophrenia, depression and anxiety, Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders. Drug repositioning studies using ML have identified multiple drug candidates as promising therapeutic agents.

CONCLUSION

Next-generation ML techniques and subsequent deep learning may power new findings regarding the discovery of new pharmacological agents by bridging the gap between biological data and chemical drug information.

Effects of Chronic Pain Treatment on Altered Functional and Metabolic Activities in the Brain: A Systematic Review and Meta-Analysis of Functional Neuroimaging Studies

Previous studies have identified altered brain changes in chronic pain patients, however, it remains unclear whether these changes are reversible. We summarized the neural and molecular changes in patients with chronic pain and employed a meta-analysis approach to quantify the changes. We included 75 studies and 11 of these 75 studies were included in the activation likelihood estimation (ALE) analysis. In the 62 functional magnetic resonance imaging (fMRI) studies, the primary somatosensory and motor cortex (SI and MI), thalamus, insula, and anterior cingulate cortex (ACC) showed significantly decreased activity after the treatments compared to baseline. In the 13 positron emission tomography (PET) studies, the SI, MI, thalamus, and insula showed significantly increased glucose uptake, blood flow, and opioid-receptor binding potentials after the treatments compared to baseline. A meta-analysis of fMRI studies in patients with chronic pain, during pain-related tasks, showed a significant deactivation likelihood cluster in the left medial posterior thalamus. Further studies are warranted to understand brain reorganization in patients with chronic pain compared to the normal state, in terms of its relationship with symptom reduction and baseline conditions.

A spatial Bayesian latent factor model for image-on-image regression

Image-on-image regression analysis, using images to predict images, is a challenging task, due to (1) the high dimensionality and (2) the complex spatial dependence structures in image predictors and image outcomes. In this work, we propose a novel image-on-image regression model, by extending a spatial Bayesian latent factor model to image data, where low-dimensional latent factors are adopted to make connections between high-dimensional image outcomes and image predictors. We assign Gaussian process priors to the spatially varying regression coefficients in the model, which can well capture the complex spatial dependence among image outcomes as well as that among the image predictors. We perform simulation studies to evaluate the out-of-sample prediction performance of our method compared with linear regression and voxel-wise regression methods for different scenarios. The proposed method achieves better prediction accuracy by effectively accounting for the spatial dependence and efficiently reduces image dimensions with latent factors. We apply the proposed method to analysis of multimodal image data in the Human Connectome Project where we predict task-related contrast maps using subcortical volumetric seed maps.

Cortico-spinal imaging to study pain

Functional magnetic resonance imaging of the brain has helped to reveal mechanisms of pain perception in health and disease. Recently, imaging approaches have been developed that allow recording neural activity simultaneously in the brain and in the spinal cord. These approaches offer the possibility to examine pain perception in the entire central pain system and in addition, to investigate cortico-spinal interactions during pain processing. Although cortico-spinal imaging is a promising technique, it bears challenges concerning data acquisition and data analysis strategies. In this review, we discuss studies that applied simultaneous imaging of the brain and spinal cord to explore central pain processing. Furthermore, we describe different MR-related acquisition techniques, summarize advantages and disadvantages of approaches that have been implemented so far and present software that has been specifically developed for the analysis of spinal fMRI data to address challenges of spinal data analysis.

Inferring pain experience in infants using quantitative whole-brain functional MRI signatures: a cross-sectional, observational study

Background

In the absence of verbal communication, it is challenging to infer an individual's sensory and emotional experience. In communicative adults, functional MRI (fMRI) has been used to develop multivariate brain activity signatures, which reliably capture elements of human pain experience. We aimed to translate whole-brain fMRI signatures that encode pain perception in adults to the newborn infant brain, to advance understanding of functional brain development and pain perception in early life.

Methods

In this cross-sectional, observational study, we recruited adults at the University of Oxford (Oxford, UK) and infants on the postnatal wards of John Radcliffe Hospital (Oxford, UK). Healthy full-term infants were eligible for inclusion if they were clinically stable, self-ventilating in air, and had no neurological abnormalities. Infants were consecutively recruited in two cohorts (A and B) due to the installation of a new fMRI scanner using the same recruitment criteria. Adults (aged ≥18 years) were eligible if they were postgraduate students or staff at the University of Oxford. Participants were stimulated with low intensity nociceptive stimuli (64, 128, 256, and 512 mN in adults; 64 and 128 mN in infants) during acquisition of fMRI data. fMRI pain signatures (neurologic pain signature [NPS] and stimulus intensity independent pain signature-1 [SIIPS1]), and four control signatures (the vicarious pain signature, the picture-induced negative emotion signature [PINES], the social rejection signature, and a global signal signature) were applied directly to the adult data and translated to the infant brain. We assessed the concordance of the signatures with the brain responses of adults and infants using cosine similarity scores, and we assessed stimulus intensity encoding of the signature responses using a Spearman rank correlation test. We also assessed brain activity in pro-pain and anti-pain components of the signatures.

Findings

Between May 22, 2013, and Jan 29, 2018, we recruited ten healthy participants to the adult cohort (five women and five men; mean age 28·3 years [range 23-36]), 15 infants to infant cohort A (six girls and nine boys; mean postnatal age 4 days [range 1-11]), and 22 infants to infant cohort B (11 girls and 11 boys; mean postnatal age 3 days [range 1-10]). The NPS was activated in both the adults and infants, and reliably encoded stimulus intensity. The NPS was activated in the adult cohort (p<0·0001) and both infant cohorts (p=0·048 for infant cohort A; p=0·001 for infant cohort B). The SIIPS1 was only expressed in adults. Pro-pain brain regions showed similar activation patterns in adults and infants, whereas responses in anti-pain brain regions were divergent.

Interpretation

Basic intensity encoding of nociceptive information is similar in adults and infants. However, translation of adult brain signatures to infants indicated substantial differences in infant cerebral processing of nociceptive information, which might reflect their absence of expectation, motivation, and contextualisation associated with pain. This study expands the use of brain activity pain signatures to non-verbal patients and provides a potential research approach to assess the impact of analgesic interventions on brain function in infants.

Funding

Wellcome Trust, Supporting the Sick Newborn and their Parents Medical Research Fund.

Deconstructing biomarkers for chronic pain: context- and hypothesis-dependent biomarker types in relation to chronic pain

This review expounds on types and properties of biomarkers for chronic pain, given a mechanistic model of processes underlying development of chronic pain. It covers advances in the field of developing biomarkers for chronic pain, while outlining the general principles of categorizing types of biomarkers driven by specific hypotheses regarding underlying mechanisms. Within this theoretical construct, example biomarkers are described and their properties expounded. We conclude that the field is advancing in important directions and the developed biomarkers have the potential of impacting both the science and the clinical practice regarding chronic pain.

Paracetamol is a centrally acting analgesic using mechanisms located in the periaqueductal grey

BACKGROUND AND PURPOSE

We previously demonstrated that paracetamol has to be metabolised in the brain by fatty acid amide hydrolase enzyme into AM404 (N-(4-hydroxyphenyl)-5Z,8Z,11Z,14Z-eicosatetraenamide) to activate CB₁ receptors and TRPV1 channels, which mediate its analgesic effect. However, the brain mechanisms supporting paracetamol-induced analgesia remain unknown.

EXPERIMENTAL APPROACH

The effects of paracetamol on brain function in Sprague-Dawley rats were determined by functional MRI. Levels of neurotransmitters in the periaqueductal grey (PAG) were measured using in vivo ¹ H-NMR and microdialysis. Analgesic effects of paracetamol were assessed by behavioural tests and challenged with different inhibitors, administered systemically or microinjected in the PAG.

KEY RESULTS

Paracetamol decreased the connectivity of major brain structures involved in pain processing (insula, somatosensory cortex, amygdala, hypothalamus, and the PAG). This effect was particularly prominent in the PAG, where paracetamol, after conversion to AM404, (a) modulated neuronal activity and functional connectivity, (b) promoted GABA and glutamate release, and (c) activated a TRPV1 channel-mGlu₅ receptor-PLC-DAGL-CB₁ receptor signalling cascade to exert its analgesic effects.

CONCLUSIONS AND IMPLICATIONS

The elucidation of the mechanism of action of paracetamol as an analgesic paves the way for pharmacological innovations to improve the pharmacopoeia of analgesic agents.

Whole-Brain Exploratory Analysis of Functional Task Response Following Erythropoietin Treatment in Mood Disorders: A Supervised Machine Learning Approach

A core symptom of mood disorders is cognitive impairment in attention, memory and executive functions. Erythropoietin (EPO) is a candidate treatment for cognitive impairment in unipolar and bipolar disorders (UD and BD) and modulates cognition-related neural activity across a fronto-temporo-parietal network. This report investigates predicting the pharmacological treatment from functional magnetic resonance imaging (fMRI) data using a supervised machine learning approach. A total of 84 patients with UD or BD were included in a randomized double-blind parallel-group study in which they received eight weekly infusions of either EPO (40 000 IU) or saline. Task fMRI data were collected before EPO/saline infusions started (baseline) and 6 weeks after last infusion (follow-up). During the scanning sessions, participants were given an n-back working memory and a picture encoding task. Linear classification models with different regularization techniques were used to predict treatment status from both cross-sectional data (at follow-up) and longitudinal data (difference between baseline and follow-up). For the n-back and picture encoding tasks, data were available and analyzed for 52 (EPO; n = 28, Saline; n = 24) and 59 patients (EPO; n = 31, Saline; n = 28), respectively. We found limited evidence that the classifiers used could predict treatment status at a reliable level of performance (≤60% accuracy) when tested using repeated cross-validation. There was no difference in using cross-sectional versus longitudinal data. Whole-brain multivariate decoding applied to pharmaco-fMRI in small to moderate samples seems to be suboptimal for exploring data driven neuronal treatment mechanisms.

Evidence for decreased Neurologic Pain Signature activation following thoracic spinal manipulation in healthy volunteers and participants with neck pain

•

The use of brain-based models of pain were explored in two clinical studies.

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Neurologic pain signature activation decreased following spinal manipulation.

•

Spinal manipulation altered the processing of pain-related brain activity.

•

We provide evidence for a centrally mediated therapeutic action of spinal manipulation.

•

Brain-based models have potential as objective clinical biomarkers of pain.

Background Context

Spinal manipulation (SM) is a common treatment for neck and back pain, theorized to mechanically affect the spine leading to therapeutic mechanical changes. The link between specific mechanical effects and clinical improvement is not well supported. SM's therapeutic action may instead be partially mediated within the central nervous system.

Purpose

To introduce brain-based models of pain for spinal pain and manual therapy research, characterize the distributed central mechanisms of SM, and advance the preliminary validation of brain-based models as potential clinical biomarkers of pain.

Study Design

Secondary analysis of two functional magnetic resonance imaging studies investigating the effect of thoracic SM on pain-related brain activity: A non-controlled, non-blinded study in healthy volunteers (Study 1, n = 10, 5 females, and mean age = 31.2 ± 10.0 years) and a randomized controlled study in participants with acute to subacute neck pain (Study 2, n = 24, 16 females, mean age = 38.0 ± 15.1 years).

Methods

Functional magnetic resonance imaging was performed during noxious mechanical stimulation of the right index finger cuticle pre- and post-intervention. The effect of SM on pain-related activity was studied within brain regions defined by the Neurologic Pain Signature (NPS) that are predictive of physical pain.

Results

In Study 1, evoked mechanical pain (p < 0.001) and NPS activation (p = 0.010) decreased following SM, and the changes in evoked pain and NPS activation were correlated (r_RM² = 0.418, p = 0.016). Activation within the NPS subregions of the dorsal anterior cingulate cortex (dACC, p = 0.012) and right secondary somatosensory cortex/operculum (rS2_Op, p = 0.045) also decreased following SM, and evoked pain was correlated with dACC activity (r_RM² = 0.477, p = 0.019). In Study 2, neck pain (p = 0.046) and NPS (p = 0.033) activation decreased following verum but not sham SM. Associations between evoked pain, neck pain, and NPS activation, were not significant and less clear, possibly due to inadequate power, methodological limitations, or other confounding factors.

Conclusions

The findings provide preliminary evidence that SM may alter the processing of pain-related brain activity within specific pain-related brain regions and support the use of brain-based models as clinical biomarkers of pain.

Placebo Effects on the Neurologic Pain Signature: A Meta-analysis of Individual Participant Functional Magnetic Resonance Imaging Data

Importance

Placebo effects reduce pain and contribute to clinical analgesia, but after decades of research, it remains unclear whether placebo treatments mainly affect nociceptive processes or other processes associated with pain evaluation.

Objective

We conducted a systematic, participant-level meta-analysis to test the effect of placebo treatments on pain-associated functional neuroimaging responses in the neurologic pain signature (NPS), a multivariate brain pattern tracking nociceptive pain.

Data Sources

Medline (PubMed) was searched from inception to May 2015; the search was augmented with results from previous meta-analyses and expert recommendations.

Study Selection

Eligible studies were original investigations that were published in English in peer-reviewed journals and that involved functional neuroimaging of the human brain with evoked pain delivered under stimulus intensity-matched placebo and control conditions. The authors of all eligible studies were contacted and asked to provide single-participant data.

Data Extraction and Synthesis

Data were collected between December 2015 and November 2017 following the Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data guidelines. Results were summarized across participants and studies in a random-effects model.

Main Outcomes and Measures

The main, a priori outcome was NPS response; pain reports were assessed as a secondary outcome.

Results

We obtained data from 20 of 28 identified eligible studies, resulting in a total sample size of 603 healthy individuals. The NPS responses to painful stimulation compared with baseline conditions were positive in 575 participants (95.4%), with a very large effect size (g = 2.30 [95% CI, 1.92 to 2.69]), confirming its sensitivity to nociceptive pain in this sample. Placebo treatments showed significant behavioral outcomes on pain ratings in 17 of 20 studies (85%) and in the combined sample (g = -0.66 [95% CI, -0.80 to -0.53]). However, placebo effects on the NPS response were significant in only 3 of 20 studies (15%) and were very small in the combined sample (g = -0.08 [95% CI, -0.15 to -0.01]). Similarly, analyses restricted to studies with low risk of bias (g = -0.07 [95% CI, -0.15 to 0.00]) indicated very small effects, and analyses of just placebo responders (g = -0.22 [95% CI, -0.34 to -0.11]) indicated small effects, as well.

Conclusions and Relevance

Placebo treatments have moderate analgesic effects on pain reports. The very small effects on NPS, a validated measure that tracks levels of nociceptive pain, indicate that placebo treatments affect pain via brain mechanisms largely independent of effects on bottom-up nociceptive processing.

Evaluation of Postsurgical Hyperalgesia and Sensitization After Open Inguinal Hernia Repair: A Useful Model for Neuropathic Pain?

Cutaneous mechanical hyperalgesia can be induced in healthy volunteers in early phase analgesic studies to model central sensitization, a key mechanism of persistent pain. However, such hyperalgesia is short-lived (a matter of hours), and is used only for assessing only single drug doses. In contrast, postsurgical peri-incisional hyperalgesia may be more persistent and hence be a more useful model for the assessment of the efficacy of new analgesics. We undertook quantitative sensory testing in 18 patients at peri-incisional and nonoperated sites before open inguinal hernia repair and up to the 24th postsurgical week. The spatial extent of punctate hyperalgesia and brush allodynia at the peri-incisional site were greatest at weeks 2 and 4, but had resolved by week 24. Heat allodynia, suggestive of local inflammation or peripheral sensitization, was not observed; instead, there were deficits in cold and heat sensory detection that persisted until week 24. The findings suggest that central sensitization contributes significantly to mechanical hyperalgesia at the peri-incisional site. The prolonged duration of hyperalgesia would be advantageous as a pain model, but there was considerable variability of mechanical hyperalgesia in the cohort; the challenges of recruitment may limit its use to small, early phase analgesic studies. PERSPECTIVE: Peri-incisional mechanical hyperalgesia persists for ≥4 weeks after open inguinal hernia repair and reflects central sensitization; this may have usefulness as a model of chronic pain to assess the potential of antineuropathic analgesics.

Neuroimaging-based pain biomarkers: definitions, clinical and research applications, and evaluation frameworks to achieve personalized pain medicine

One of the key ambitions of neuroimaging-based pain biomarker research is to augment patient and clinician reporting of clinically relevant phenomena with neural measures for prediction, prognosis, and detection of pain. Despite years of productive research on the neuroimaging of pain, such applications have seen little advancement. However, recent developments in identifying brain-based biomarkers of pain through advances in technology and multivariate pattern analysis provide some optimism. Here, we (1) define and review the different types of potential neuroimaging-based biomarkers, their clinical and research applications, and their limitations and (2) describe frameworks for evaluation of pain biomarkers used in other fields (eg, genetics, cancer, cardiovascular disease, immune system disorders, and rare diseases) to achieve broad clinical and research utility and minimize the risks of misapplication of this emerging technology. To conclude, we discuss future directions for neuroimaging-based biomarker research to achieve the goal of personalized pain medicine.

Nociception and the neonatal brain

Measuring brain activity in infants provides an objective surrogate approach with which to infer pain perception following noxious events. Here we discuss different approaches which can be used to measure noxious-evoked brain activity, and discuss how these measures can be used to assess the analgesic efficacy of pharmacological and non-pharmacological interventions. We review factors that can modulate noxious-evoked brain activity, which may impact infant pain experience, including gestational age, sex, prior pain, stress, and illness.

Statistical Challenges in "Big Data" Human Neuroimaging

Smith and Nichols discuss "big data" human neuroimaging studies, with very large subject numbers and amounts of data. These studies provide great opportunities for making new discoveries about the brain but raise many new analytical challenges and interpretational risks.

Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment

Pain is a subjective sensory experience that can, mostly, be reported but cannot be directly measured or quantified. Nevertheless, a suite of biomarkers related to mechanisms, neural activity, and susceptibility offer the possibility-especially when used in combination-to produce objective pain-related indicators with the specificity and sensitivity required for diagnosis and for evaluation of risk of developing pain and of analgesic efficacy. Such composite biomarkers will also provide improved understanding of pain pathophysiology.

The emotional brain: Fundamental questions and strategies for future research

Emotions play a central role in human experience. Over time, methods for manipulating emotion have become increasingly refined and techniques for making sense of the underlying neurobiology have become ever more powerful and precise, enabling new insights into the organization of emotions in the brain. Yet recent years have witnessed a remarkably vigorous debate about the nature and origins of emotion, with leading scientists raising compelling concerns about the canon of facts and principles that has inspired and guided the field for the past quarter century. Here, we consider ways in which recent neuroimaging research informs this dialogue. By focusing attention on the most important outstanding questions about the nature of emotion and the architecture of the emotional brain, we hope to stimulate the kinds of work that will be required to move the field forward. Addressing these questions is critical, not just for understanding the mind, but also for elucidating the root causes of many of its disorders.

Genome-wide association studies of brain imaging phenotypes in UK Biobank

The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable. We identify 148 clusters of associations between single nucleotide polymorphisms and imaging phenotypes that replicate at P < 0.05, when we would expect 21 to replicate by chance. Notable significant, interpretable associations include: iron transport and storage genes, related to magnetic susceptibility of subcortical brain tissue; extracellular matrix and epidermal growth factor genes, associated with white matter micro-structure and lesions; genes that regulate mid-line axon development, associated with organization of the pontine crossing tract; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide insights into the genetic architecture of the brain that are relevant to neurological and psychiatric disorders, brain development and ageing.

Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants

Background

Clinically approved antidepressants modulate the brain's emotional valence circuits, suggesting that the response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary that these modulations can be reliably detected. Here, we apply a cross-validated predictive model to classify emotional valence and pharmacologic effect across eleven task-based fMRI datasets (n = 306) exploring the effect of antidepressant administration on emotional face processing.

Methods

We created subject-level contrast of parameter estimates of the emotional faces task and used the Shen whole-brain parcellation scheme to define 268 subject-level features that trained a cross-validated gradient-boosting machine protocol to classify emotional valence (fearful vs happy face visual conditions) and pharmacologic effect (drug vs placebo administration) within and across studies.

Results

We found patterns of brain activity that classify emotional valence with a statistically significant level of accuracy (70% across-all-subjects; range from 50 to 87% across-study). Our classifier failed to consistently discriminate drug from placebo. Subject population (healthy or unhealthy), treatment group (drug or placebo), and drug administration protocol (dose and duration) affected this accuracy with similar populations better predicting one another.

Conclusions

We found limited evidence that antidepressants modulated brain response in a consistent manner, however found a consistent signature for emotional valence. Variable functional patterns across studies suggest that predictive modeling can inform biomarker development in mental health and in pharmacotherapy development. Our results suggest that case-controlled designs and more standardized protocols are required for functional imaging to provide robust biomarkers for drug development.

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The emotional faces task can evaluate the brain's fMRI response to antidepressants.

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We found a consistent signature for emotional valence across 11 such datasets.

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We found limited evidence for consistent antidepressant response.

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Case-controlled designs and more standardized protocols could increase this yield.

Pain Neuroimaging in Humans: A Primer for Beginners and Non-Imagers

Human pain neuroimaging has exploded in the past 2 decades. During this time, the broader neuroimaging community has continued to investigate and refine methods. Another key to progress is exchange with clinicians and pain scientists working with other model systems and approaches. These collaborative efforts require that non-imagers be able to evaluate and assess the evidence provided in these reports. Likewise, new trainees must design rigorous and reliable pain imaging experiments. In this article we provide a guideline for designing, reading, evaluating, analyzing, and reporting results of a pain neuroimaging experiment, with a focus on functional and structural magnetic resonance imaging. We focus in particular on considerations that are unique to neuroimaging studies of pain in humans, including study design and analysis, inferences that can be drawn from these studies, and the strengths and limitations of the approach.

Improving the treatment of infant pain

Purpose of review

Pain management presents a major challenge in neonatal care. Newborn infants who require medical treatment can undergo frequent invasive procedures during a critical period of neurodevelopment. However, adequate analgesic provision is infrequently and inconsistently provided for acute noxious procedures because of limited and conflicting evidence regarding analgesic efficacy and safety of most commonly used pharmacological agents. Here, we review recent advances in the measurement of infant pain and discuss clinical trials that assess the efficacy of pharmacological analgesia in infants.

Recent findings

Recently developed measures of noxious-evoked brain activity are sensitive to analgesic modulation, providing an objective quantitative outcome measure that can be used in clinical trials of analgesics.

Summary

Noxious stimulation evokes changes in activity across all levels of the infant nervous system, including reflex activity, altered brain activity and behaviour, and long-lasting changes in infant physiological stability. A multimodal approach is needed if we are to identify efficacious and well tolerated analgesic treatments. Well designed clinical trials are urgently required to improve analgesic provision in the infant population.

Nociceptive brain activity as a measure of analgesic efficacy in infants

Pain in infants is undertreated and poorly understood, representing a major clinical problem. In part, this is due to our inability to objectively measure pain in nonverbal populations. We present and validate an electroencephalography-based measure of infant nociceptive brain activity that is evoked by acute noxious stimulation and is sensitive to analgesic modulation. This measure should be valuable both for mechanistic investigations and for testing analgesic efficacy in the infant population.

Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.

The role of fMRI in drug development

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.

A critical evaluation of validity and utility of translational imaging in pain and analgesia: Utilizing functional imaging to enhance the process

Assessing clinical pain and metrics related to function or quality of life predominantly relies on patient reported subjective measures. These outcome measures are generally not applicable to the preclinical setting where early signs pointing to analgesic value of a therapy are sought, thus introducing difficulties in animal to human translation in pain research. Evaluating brain function in patients and respective animal model(s) has the potential to characterize mechanisms associated with pain or pain-related phenotypes and thereby provide a means of laboratory to clinic translation. This review summarizes the progress made towards understanding of brain function in clinical and preclinical pain states elucidated using an imaging approach as well as the current level of validity of translational pain imaging. We hypothesize that neuroimaging can describe the central representation of pain or pain phenotypes and yields a basis for the development and selection of clinically relevant animal assays. This approach may increase the probability of finding meaningful new analgesics that can help satisfy the significant unmet medical needs of patients.

Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations

Chronic pain is the greatest source of disability globally and claims related to chronic pain feature in many insurance and medico-legal cases. Brain imaging (for example, functional MRI, PET, EEG and magnetoencephalography) is widely considered to have potential for diagnosis, prognostication, and prediction of treatment outcome in patients with chronic pain. In this Consensus Statement, a presidential task force of the International Association for the Study of Pain examines the capabilities of brain imaging in the diagnosis of chronic pain, and the ethical and legal implications of its use in this way. The task force emphasizes that the use of brain imaging in this context is in a discovery phase, but has the potential to increase our understanding of the neural underpinnings of chronic pain, inform the development of therapeutic agents, and predict treatment outcomes for use in personalized pain management. The task force proposes standards of evidence that must be satisfied before any brain imaging measure can be considered suitable for clinical or legal purposes. The admissibility of such evidence in legal cases also strongly depends on laws that vary between jurisdictions. For these reasons, the task force concludes that the use of brain imaging findings to support or dispute a claim of chronic pain - effectively as a pain lie detector - is not warranted, but that imaging should be used to further our understanding of the mechanisms underlying pain.

Clinical Concepts Emerging from fMRI Functional Connectomics

Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

The Potential Role of Sensory Testing, Skin Biopsy, and Functional Brain Imaging as Biomarkers in Chronic Pain Clinical Trials: IMMPACT Considerations

Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the U.S. Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: 1) sensory testing, 2) skin punch biopsy, and 3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: 1) diagnostic, 2) prognostic, 3) predictive, and 4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials.

PERSPECTIVE

The applicability of sensory testing, skin biopsy, and brain imaging as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers for use in analgesic treatment trials is considered. Evidence in support of their use and outlining problems is presented, as well as a call for further standardization and demonstrations of validity and reliability.

Imaging pain relief in osteoarthritis (IPRO): protocol of a double-blind randomised controlled mechanistic study assessing pain relief and prediction of duloxetine treatment outcome

INTRODUCTION

Osteoarthritis (OA) pain is a major cause of long-term disability and chronic pain in the adult population. One in five patients does not receive satisfactory pain relief, which reflects the complexity of chronic pain and the current lack of understanding of mechanisms of chronic pain. Recently, duloxetine has demonstrated clinically relevant pain relief, but only in half of treated patients with OA. Here, the aim is to investigate the neural mechanisms of pain relief and neural signatures that may predict treatment response to duloxetine in chronic knee OA pain.

METHODS AND ANALYSIS

This is an ongoing single-centre randomised placebo-controlled mechanistic study (2:1 (placebo) allocation), using a multimodal neuroimaging approach, together with psychophysiological (quantitative sensory testing), genetics and questionnaire assessments. Eighty-one subjects with chronic knee OA pain are planned to power for between-group comparisons (placebo, duloxetine responder and duloxetine non-responder). Participants have a baseline assessment and, following 6 weeks of duloxetine (30 mg for 2 weeks, then 60 mg for 4 weeks), a follow-up evaluation. Brain imaging is performed at 3T with blood-oxygen-level dependent functional MRI at rest and during pin-prick nociceptive stimulation for main outcome assessment; arterial spin labelling and structural imaging (T1-weighted) for secondary outcome assessment. Questionnaires evaluate pain, negative affect, quality of sleep and cognition.

ETHICS AND DISSEMINATION

The study has been approved by the East Midlands, Nottingham and is being carried out under the principles of the Declaration of Helsinki (64th, 2013) and Good Clinical Practice standards. Results will be disseminated in peer-reviewed journals and at scientific conferences.

TRIAL REGISTRATION NUMBER

This trial is registered at ClinicalTrials.gov (NCT02208778).This work was supported by Arthritis Research UK (Grant 18769).

How to Perform and Interpret Functional Magnetic Resonance Imaging Studies in Functional Gastrointestinal Disorders

Functional neuroimaging studies have revealed the importance of the role of cognitive and psychological factors and the dysregulation of the brain-gut axis in functional gastrointestinal disorder patients. Although only a small number of neuroimaging studies have been conducted in functional gastrointestinal disorder patients, and despite the fact that the neuroimaging technique requires a high level of knowledge, the technique still has a great deal of potential. The application of functional magnetic resonance imaging (fMRI) technique in functional gastrointestinal disorders should provide novel methods of diagnosing and treating patients. In this review, basic knowledge and technical/practical issues of fMRI will be introduced to clinicians.

Abnormal structural connectivity between the basal ganglia, thalamus, and frontal cortex in patients with disorders of consciousness

Consciousness loss in patients with severe brain injuries is associated with reduced functional connectivity of the default mode network (DMN), fronto-parietal network, and thalamo-cortical network. However, it is still unclear if the brain white matter connectivity between the above mentioned networks is changed in patients with disorders of consciousness (DOC). In this study, we collected diffusion tensor imaging (DTI) data from 13 patients and 17 healthy controls, constructed whole-brain white matter (WM) structural networks with probabilistic tractography. Afterward, we estimated and compared topological properties, and revealed an altered structural organization in the patients. We found a disturbance in the normal balance between segregation and integration in brain structural networks and detected significantly decreased nodal centralities primarily in the basal ganglia and thalamus in the patients. A network-based statistical analysis detected a subnetwork with uniformly significantly decreased structural connections between the basal ganglia, thalamus, and frontal cortex in the patients. Further analysis indicated that along the WM fiber tracts linking the basal ganglia, thalamus, and frontal cortex, the fractional anisotropy was decreased and the radial diffusivity was increased in the patients compared to the controls. Finally, using the receiver operating characteristic method, we found that the structural connections within the NBS-derived component that showed differences between the groups demonstrated high sensitivity and specificity (>90%). Our results suggested that major consciousness deficits in DOC patients may be related to the altered WM connections between the basal ganglia, thalamus, and frontal cortex.

Pharmacologic attenuation of cross-modal sensory augmentation within the chronic pain insula

Supplemental Digital Content is Available in the Text.

Sensitivity to visual stimuli is increased in patients with fibromyalgia and improved with administration of pregabalin.

Pain can be elicited through all mammalian sensory pathways yet cross-modal sensory integration, and its relationship to clinical pain, is largely unexplored. Centralized chronic pain conditions such as fibromyalgia are often associated with symptoms of multisensory hypersensitivity. In this study, female patients with fibromyalgia demonstrated cross-modal hypersensitivity to visual and pressure stimuli compared with age- and sex-matched healthy controls. Functional magnetic resonance imaging revealed that insular activity evoked by an aversive level of visual stimulation was associated with the intensity of fibromyalgia pain. Moreover, attenuation of this insular activity by the analgesic pregabalin was accompanied by concomitant reductions in clinical pain. A multivariate classification method using support vector machines (SVM) applied to visual-evoked brain activity distinguished patients with fibromyalgia from healthy controls with 82% accuracy. A separate SVM classification of treatment effects on visual-evoked activity reliably identified when patients were administered pregabalin as compared with placebo. Both SVM analyses identified significant weights within the insular cortex during aversive visual stimulation. These data suggest that abnormal integration of multisensory and pain pathways within the insula may represent a pathophysiological mechanism in some chronic pain conditions and that insular response to aversive visual stimulation may have utility as a marker for analgesic drug development.

Quantifying cerebral contributions to pain beyond nociception

Cerebral processes contribute to pain beyond the level of nociceptive input and mediate psychological and behavioural influences. However, cerebral contributions beyond nociception are not yet well characterized, leading to a predominant focus on nociception when studying pain and developing interventions. Here we use functional magnetic resonance imaging combined with machine learning to develop a multivariate pattern signature-termed the stimulus intensity independent pain signature-1 (SIIPS1)-that predicts pain above and beyond nociceptive input in four training data sets (Studies 1-4, N=137). The SIIPS1 includes patterns of activity in nucleus accumbens, lateral prefrontal and parahippocampal cortices, and other regions. In cross-validated analyses of Studies 1-4 and in two independent test data sets (Studies 5-6, N=46), SIIPS1 responses explain variation in trial-by-trial pain ratings not captured by a previous fMRI-based marker for nociceptive pain. In addition, SIIPS1 responses mediate the pain-modulating effects of three psychological manipulations of expectations and perceived control. The SIIPS1 provides an extensible characterization of cerebral contributions to pain and specific brain targets for interventions.