Pain interventions with no active ingredient, placebo, are sometimes effective in treating chronic pain conditions. Prior studies on the neurobiological underpinnings of placebo analgesia indicate endogenous opioid release and changes in brain responses and functional connectivity during pain anticipation and pain experience in healthy subjects. Here, we investigated placebo analgesia in healthy subjects and in interictal migraine patients (n = 9) and matched healthy controls (n = 9) using 11C-diprenoprhine Positron Emission Tomography (PET) and simultaneous functional Magnetic Resonance Imaging (fMRI). Intravenous saline injections (the placebo) led to lower pain ratings, but we did not find evidence for an altered placebo response in interictal migraine subjects as compared to healthy subjects.

The basal ganglia (BG) are composed of several nuclei involved in neural processing related to the execution of motor, cognitive and emotional activities. Preclinical and clinical data have implicated a role for these structures in pain processing. Recently neuroimaging has added important information on BG activation in conditions of acute pain, chronic pain and as a result of drug effects. Our current understanding of alterations in cortical and sub-cortical regions in pain suggests that the BG are uniquely involved in thalamo-cortico-BG loops to integrate many aspects of pain. These include the integration of motor, emotional, autonomic and cognitive responses to pain.

We compared brain activations in response to acute noxious thermal stimuli in controls and chronic back pain (CBP) patients. Pain perception and related cortical activation patterns were similar in the two groups. However, nucleus accumbens (NAc) activity differentiated the groups at a very high accuracy, exhibiting phasic and tonic responses with distinct properties. Positive phasic NAc activations at stimulus onset and offset tracked stimulus salience and, in normal subjects, predicted reward (pain relief) magnitude at stimulus offset. In CBP, NAc activity correlated with different cortical circuitry from that of normals and phasic activity at stimulus offset was negative in polarity, suggesting that the acute pain relieves the ongoing back pain. The relieving effect was confirmed in a separate psychophysical study in CBP. Therefore, in contrast to somatosensory pathways, which reflect sensory properties of acute noxious stimuli, NAc activity in humans encodes its predicted value and anticipates its analgesic potential on chronic pain.

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects.

To date, the blood oxygenated-level dependent (BOLD) functional magnetic resonance imaging (fMRI) technique has enabled an objective and deeper understanding of pain processing mechanisms embedded within the human central nervous system (CNS). In order to further comprehend the benefits and limitations of BOLD fMRI in the context of pain as well as the corresponding subjective pain ratings, we evaluated the univariate response, test-retest reliability and confidence intervals (CIs) at the 95% level of both data types collected during evoked stimulation of 40°C (non-noxious), 44°C (mildly noxious) and a subject-specific temperature eliciting a 7/10 pain rating. The test-retest reliability between two scanning sessions was determined by calculating group-level interclass correlation coefficients (ICCs) and at the single-subject level. Across the three stimuli, we initially observed a graded response of increasing magnitude for both VAS (visual analog score) pain ratings and fMRI data. Test-retest reliability was observed to be highest for VAS pain ratings obtained during the 7/10 pain stimulation (ICC=0.938), while ICC values of pain fMRI data for a distribution of CNS structures ranged from 0.5 to 0.859 (p<0.05). Importantly, the upper and lower confidence interval CI bounds reported herein could be utilized in subsequent trials involving healthy volunteers to hypothesize the magnitude of effect required to overcome inherent variability of either VAS pain ratings or BOLD responses evoked during innocuous or noxious thermal stimulation.

A typical fMRI data analysis proceeds via the generalized linear model (GLM) with Gaussian noise using a model based on the experimental paradigm. This analysis ultimately results in the production of z-statistic images corresponding to the contrasts of interest. Thresholding such z-statistic images at uncorrected thresholds suitable for testing activation at a single voxel results in the problem of multiple comparisons. A number of methods which account for the problem of multiple comparisons have been proposed including Gaussian random field theory, mixture modeling and false discovery rate (FDR). The focus of this paper is on the development of a generalized version of FDR (GFDR) in an empirical Bayesian framework, specially adapted for fMRI thresholding, that is more robust to modeling violations as compared to traditional FDR. We show theoretically as well as by simulation that for real fMRI data various factors lead to a mixture of Gaussians (MOG) density for the "null" distribution. Artificial data was used to systematically study the bias of FDR and GFDR under varying intensity of modeling violations, signal to noise ratios and activation fractions for a range of q values. GFDR was able to handle modeling violations and produce good results when FDR failed. Real fMRI data was also used to confirm GFDR capabilities. Our results indicate that it is very important to account for the form and fraction of the "null" hypothesis adaptively from the data in order to obtain valid inference.

The hypothalamus has been implicated in migraine based on the manifestation of autonomic symptoms with the disease, as well as neuroimaging evidence of hypothalamic activation during attacks. Our objective was to determine functional connectivity (FC) changes between the hypothalamus and the rest of the brain in migraine patients vs. control subjects. This study uses fMRI (functional magnetic resonance imaging) to acquire resting state scans in 12 interictal migraine patients and 12 healthy matched controls. Hypothalamic connectivity seeds were anatomically defined based on high-resolution structural scans, and FC was assessed in the resting state scans. Migraine patients had increased hypothalamic FC with a number of brain regions involved in regulation of autonomic functions, including the locus coeruleus, caudate, parahippocampal gyrus, cerebellum, and the temporal pole. Stronger functional connections between the hypothalamus and brain areas that regulate sympathetic and parasympathetic functions may explain some of the hypothalamic-mediated autonomic symptoms that accompany or precede migraine attacks.

This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region.

Evaluation of pain-induced changes in functional connectivity was performed in pediatric complex regional pain syndrome (CRPS) patients. High field functional magnetic resonance imaging was done in the symptomatic painful state and at follow up in the asymptomatic pain free/recovered state. Two types of connectivity alterations were defined: (1) Transient increases in functional connectivity that identified regions with increased cold-induced functional connectivity in the affected limb vs. unaffected limb in the CRPS state, but with normalized connectivity patterns in the recovered state; and (2) Persistent increases in functional connectivity that identified regions with increased cold-induced functional connectivity in the affected limb as compared to the unaffected limb that persisted also in the recovered state (recovered affected limb versus recovered unaffected limb). The data support the notion that even after symptomatic recovery, alterations in brain systems persist, particularly in amygdala and basal ganglia systems. Connectivity analysis may provide a measure of temporal normalization of different circuits/regions when evaluating therapeutic interventions for this condition. The results add emphasis to the importance of early recognition and management in improving outcome of pediatric CRPS.

Resting state networks (RSNs) have been studied extensively with functional MRI in humans in health and disease to reflect brain function in the un-stimulated state as well as reveal how the brain is altered with disease. Rodent models of disease have been used comprehensively to understand the biology of the disease as well as in the development of new therapies. RSN reported studies in rodents, however, are few, and most studies are performed with anesthetized rodents that might alter networks and differ from their non-anesthetized state. Acquiring RSN data in the awake rodent avoids the issues of anesthesia effects on brain function. Using high field fMRI we determined RSNs in awake rats using an independent component analysis (ICA) approach, however, ICA analysis can produce a large number of components, some with biological relevance (networks). We further have applied a novel method to determine networks that are robust and reproducible among all the components found with ICA. This analysis indicates that 7 networks are robust and reproducible in the rat and their putative role is discussed.

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies.

Development and maintenance of chronic pain is associated with structural and functional brain reorganization. However, few studies have explored the impact of drug treatments on such changes. The extent to which long-term analgesia is related to brain adaptations and its effects on the reversibility of brain reorganization remain unclear. In a randomized placebo-controlled clinical trial, we contrasted pain relief (3-month treatment period), and anatomical (gray matter density [GMD], assessed by voxel-based morphometry) and functional connectivity (resting state fMRI nodal degree count [DC]) adaptations, in 39 knee osteoarthritis (OA) patients (22 females), randomized to duloxetine (DLX, 60 mg once daily) or placebo. Pain relief was equivalent between treatment types. However, distinct circuitry (GMD and DC) could explain pain relief in each group: up to 85% of variance for placebo analgesia and 49% of variance for DLX analgesia. No behavioral measures (collected at entry into the study) could independently explain observed analgesia. Identified circuitry were outside of nociceptive circuitry and minimally overlapped with OA-abnormal or placebo response predictive brain regions. Mediation analysis revealed that changes in GMD and DC can influence each other across remote brain regions to explain observed analgesia. Therefore, we can conclude that distinct brain mechanisms underlie DLX and placebo analgesia in OA. The results demonstrate that even in the absence of differences in subjective pain relief, pharmacological treatments can be differentiated from placebo based on objective brain biomarkers. This is a crucial step to untangling mechanisms and advancing personalized therapy approaches for chronic pain.

Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo's effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active treatment in some patients diminishes modeled placebo-related analgesia. Trial Registration ClinicalTrials.gov NCT02903238 ClinicalTrials.gov NCT01558700.

Nalbuphine, an agonist-antagonist kappa-opioid, produces brief analgesia followed by enhanced pain/hyperalgesia in male postsurgical patients. However, it produces profound analgesia without pain enhancement when co-administration with low dose naloxone. To examine the effect of nalbuphine or nalbuphine plus naloxone on activity in brain regions that may explain these differences, we employed pharmacological magnetic resonance imaging (phMRI) in a double blind cross-over study with 13 healthy male volunteers. In separate imaging sessions subjects were administered nalbuphine (5 mg/70 kg) preceded by either saline (Sal-Nalb) or naloxone 0.4 mg (Nalox-Nalb). Blood oxygen level-dependent (BOLD) activation maps followed by contrast and connectivity analyses revealed marked differences. Sal-Nalb produced significantly increased activity in 60 brain regions and decreased activity in 9; in contrast, Nalox-Nalb activated only 14 regions and deactivated only 3. Nalbuphine, like morphine in a previous study, attenuated activity in the inferior orbital cortex, and, like noxious stimulation, increased activity in temporal cortex, insula, pulvinar, caudate, and pons. Co-administration/pretreatment of naloxone selectively blocked activity in pulvinar, pons and posterior insula. Nalbuphine induced functional connectivity between caudate and regions in the frontal, occipital, temporal, insular, middle cingulate cortices, and putamen; naloxone co-admistration reduced all connectivity to non-significant levels, and, like phMRI measures of morphine, increased activation in other areas (e.g., putamen). Naloxone pretreatment to nalbuphine produced changes in brain activity possess characteristics of both analgesia and algesia; naloxone selectively blocks activity in areas associated with algesia. Given these findings, we suggest that nalbuphine interacts with a pain salience system, which can modulate perceived pain intensity.

Catheter radiofrequency (RF) ablation for cardiac arrhythmias is a painful procedure. Prior work using functional near-infrared spectroscopy (fNIRS) in patients under general anesthesia has indicated that ablation results in activity in pain-related cortical regions, presumably due to inadequate blockade of afferent nociceptors originating within the cardiac system. Having an objective brain-based measure for nociception and analgesia may in the future allow for enhanced analgesic control during surgical procedures. Hence, the primary aim of this study is to demonstrate that the administration of remifentanil, an opioid widely used during surgery, can attenuate the fNIRS cortical responses to cardiac ablation.

Use of opioid analgesics for pain management has increased dramatically over the past decade, with corresponding increases in negative sequelae including overdose and death. There is currently no well-validated objective means of accurately identifying patients likely to experience good analgesia with low side effects and abuse risk prior to initiating opioid therapy. This paper discusses the concept of data-based personalized prescribing of opioid analgesics as a means to achieve this goal. Strengths, weaknesses, and potential synergism of traditional randomized placebo-controlled trial (RCT) and practice-based evidence (PBE) methodologies as means to acquire the clinical data necessary to develop validated personalized analgesic-prescribing algorithms are overviewed. Several predictive factors that might be incorporated into such algorithms are briefly discussed, including genetic factors, differences in brain structure and function, differences in neurotransmitter pathways, and patient phenotypic variables such as negative affect, sex, and pain sensitivity. Currently available research is insufficient to inform development of quantitative analgesic-prescribing algorithms. However, responder subtype analyses made practical by the large numbers of chronic pain patients in proposed collaborative PBE pain registries, in conjunction with follow-up validation RCTs, may eventually permit development of clinically useful analgesic-prescribing algorithms.