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

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

A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems.

Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical-subcortical systems developed from prior literature ("multisystem models"); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains.

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.

Dispositional Mindfulness and Acute Heat Pain: Comparing Stimulus-Evoked Pain With Summary Pain Assessment.

OBJECTIVE: Dispositional mindfulness is associated with reduced pain in clinical and experimental settings. However, researchers have neglected the type of pain assessment, as dispositional mindfulness may have unique benefits for reduced pain sensitivity when relying on summary pain assessments, in contrast to assessing the pain of each noxious stimulus. Here, we test the association between dispositional mindfulness and pain using both trial-by-trial pain assessments and overall summary ratings after acute pain tasks. METHODS: One hundred thirty-one healthy adult volunteers (mean age = 29.09 [8.00] years, 55.7% female) underwent two experimental thermal pain paradigms. We tested whether dispositional mindfulness measured with the Mindful Attention Awareness Scale was related to a) heat-evoked pain sensitivity, as measured by pain threshold, pain tolerance, average pain, trial-by-trial ratings, and heat-evoked skin conductance response, and b) summary judgments of sensory and affective pain assessed using the McGill Pain Questionnaire (MPQ). RESULTS: Mindful Attention Awareness Scale ratings were associated with decreased pain on the MPQ sensory (B = -0.18, SE = 0.05, 95% confidence interval = -0.29 to -0.07, t = -3.28, p = .001) and affective (B = -0.11, SE = 0.03, 95% confidence interval = -0.18 to -0.05, t = -3.32, p = .001) dimensions but not with experimental thermal pain assessments, including threshold, tolerance, heat-evoked pain, or skin conductance response (p values ≥ .29). CONCLUSIONS: In this study, dispositional mindfulness mitigated acute thermal pain only when pain was assessed using the MPQ. These findings may reflect differences in immediate versus retrospective judgments or the type of pain assessed by each measure. Future research should examine regulation processes that may explain these differential analgesic benefits, such as attention, rumination, or reappraisal.

Threat-anticipatory psychophysiological response is enhanced in youth with anxiety disorders and correlates with prefrontal cortex neuroanatomy.

Background: Threat anticipation engages neural circuitry that has evolved to promote defensive behaviours; perturbations in this circuitry could generate excessive threat-anticipation response, a key characteristic of pathological anxiety. Research into such mechanisms in youth faces ethical and practical limitations. Here, we use thermal stimulation to elicit pain-anticipatory psychophysiological response and map its correlates to brain structure among youth with anxiety and healthy youth. Methods: Youth with anxiety (n = 25) and healthy youth (n = 25) completed an instructed threat-anticipation task in which cues predicted nonpainful or painful thermal stimulation; we indexed psychophysiological response during the anticipation and experience of pain using skin conductance response. High-resolution brain-structure imaging data collected in another visit were available for 41 participants. Analyses tested whether the 2 groups differed in their psychophysiological cue-based pain-anticipatory and pain-experience responses. Analyses then mapped psychophysiological response magnitude to brain structure. Results: Youth with anxiety showed enhanced psychophysiological response specifically during anticipation of painful stimulation (b = 0.52, p = 0.003). Across the sample, the magnitude of psychophysiological anticipatory response correlated negatively with the thickness of the dorsolateral prefrontal cortex (pFWE < 0.05); psychophysiological response to the thermal stimulation correlated positively with the thickness of the posterior insula (pFWE < 0.05). Limitations: Limitations included the modest sample size and the cross-sectional design. Conclusion: These findings show that threat-anticipatory psychophysiological response differentiates youth with anxiety from healthy youth, and they link brain structure to psychophysiological response during pain anticipation and experience. A focus on threat anticipation in research on anxiety could delineate relevant neural circuitry.

What Should Clinicians Tell Patients about Placebo and Nocebo Effects? Practical Considerations Based on Expert Consensus.

INTRODUCTION: Clinical and laboratory studies demonstrate that placebo and nocebo effects influence various symptoms and conditions after the administration of both inert and active treatments. OBJECTIVE: There is an increasing need for up-to-date recommendations on how to inform patients about placebo and nocebo effects in clinical practice and train clinicians how to disclose this information. METHODS: Based on previous clinical recommendations concerning placebo and nocebo effects, a 3-step, invitation-only Delphi study was conducted among an interdisciplinary group of internationally recognized experts. The study consisted of open- and closed-ended survey questions followed by a final expert meeting. The surveys were subdivided into 3 parts: (1) informing patients about placebo effects, (2) informing patients about nocebo effects, and (3) training clinicians how to communicate this information to the patients. RESULTS: There was consensus that communicating general information about placebo and nocebo effects to patients (e.g., explaining their role in treatment) could be beneficial, but that such information needs to be adjusted to match the specific clinical context (e.g., condition and treatment). Experts also agreed that training clinicians to communicate about placebo and nocebo effects should be a regular and integrated part of medical education that makes use of multiple formats, including face-to-face and online modalities. CONCLUSIONS: The current 3-step Delphi study provides consensus-based recommendations and practical considerations for disclosures about placebo and nocebo effects in clinical practice. Future research is needed on how to optimally tailor information to specific clinical conditions and patients' needs, and on developing standardized disclosure training modules for clinicians.

Multiple Brain Networks Mediating Stimulus-Pain Relationships in Humans.

The brain transforms nociceptive input into a complex pain experience comprised of sensory, affective, motivational, and cognitive components. However, it is still unclear how pain arises from nociceptive input and which brain networks coordinate to generate pain experiences. We introduce a new high-dimensional mediation analysis technique to estimate distributed, network-level patterns that formally mediate the relationship between stimulus intensity and pain. We applied the model to a large-scale analysis of functional magnetic resonance imaging data (N = 284), focusing on brain mediators of the relationship between noxious stimulus intensity and trial-to-trial variation in pain reports. We identify mediators in both traditional nociceptive pathways and in prefrontal, midbrain, striatal, and default-mode regions unrelated to nociception in standard analyses. The whole-brain mediators are specific for pain versus aversive sounds and are organized into five functional networks. Brain mediators predicted pain ratings better than previous brain measures, including the neurologic pain signature (Wager et al. 2013). Our results provide a broader view of the networks underlying pain experience, as well as novel brain targets for interventions.

Pain-Evoked Reorganization in Functional Brain Networks.

Recent studies indicate that a significant reorganization of cerebral networks may occur in patients with chronic pain, but how immediate pain experience influences the organization of large-scale functional networks is not yet well characterized. To investigate this question, we used functional magnetic resonance imaging in 106 participants experiencing both noxious and innocuous heat. Painful stimulation caused network-level reorganization of cerebral connectivity that differed substantially from organization during innocuous stimulation and standard resting-state networks. Noxious stimuli increased somatosensory network connectivity with (a) frontoparietal networks involved in context representation, (b) "ventral attention network" regions involved in motivated action selection, and (c) basal ganglia and brainstem regions. This resulted in reduced "small-worldness," modularity (fewer networks), and global network efficiency and in the emergence of an integrated "pain supersystem" (PS) whose activity predicted individual differences in pain sensitivity across 5 participant cohorts. Network hubs were reorganized ("hub disruption") so that more hubs were localized in PS, and there was a shift from "connector" hubs linking disparate networks to "provincial" hubs connecting regions within PS. Our findings suggest that pain reorganizes the network structure of large-scale brain systems. These changes may prioritize responses to painful events and provide nociceptive systems privileged access to central control of cognition and action during pain.

Distinguishing pain from nociception, salience, and arousal: How autonomic nervous system activity can improve neuroimaging tests of specificity.

Pain is a subjective, multidimensional experience that is distinct from nociception. A large body of work has focused on whether pain processing is supported by specific, dedicated brain circuits. Despite advances in human neuroscience and neuroimaging analysis, dissociating acute pain from other sensations has been challenging since both pain and non-pain stimuli evoke salience and arousal responses throughout the body and in overlapping brain circuits. In this review, we discuss these challenges and propose that brain-body interactions in pain can be leveraged in order to improve tests for pain specificity. We review brain and bodily responses to pain and nociception and extant efforts toward identifying pain-specific brain networks. We propose that autonomic nervous system activity should be used as a surrogate measure of salience and arousal to improve these efforts and enable researchers to parse out pain-specific responses in the brain, and demonstrate the feasibility of this approach using example fMRI data from a thermal pain paradigm. This new approach will improve the accuracy and specificity of functional neuroimaging analyses and help to overcome current difficulties in assessing pain specific responses in the human brain.

The neuroscience of placebo effects: connecting context, learning and health.

Placebo effects are beneficial effects that are attributable to the brain-mind responses to the context in which a treatment is delivered rather than to the specific actions of the drug. They are mediated by diverse processes--including learning, expectations and social cognition--and can influence various clinical and physiological outcomes related to health. Emerging neuroscience evidence implicates multiple brain systems and neurochemical mediators, including opioids and dopamine. We present an empirical review of the brain systems that are involved in placebo effects, focusing on placebo analgesia, and a conceptual framework linking these findings to the mind-brain processes that mediate them. This framework suggests that the neuropsychological processes that mediate placebo effects may be crucial for a wide array of therapeutic approaches, including many drugs.

Prepared stimuli enhance aversive learning without weakening the impact of verbal instructions.

Fear-relevant stimuli such as snakes and spiders are thought to capture attention due to evolutionary significance. Classical conditioning experiments indicate that these stimuli accelerate learning, while instructed extinction experiments suggest they may be less responsive to instructions. We manipulated stimulus type during instructed aversive reversal learning and used quantitative modeling to simultaneously test both hypotheses. Skin conductance reversed immediately upon instruction in both groups. However, fear-relevant stimuli enhanced dynamic learning, as measured by higher learning rates in participants conditioned with images of snakes and spiders. Results are consistent with findings that dissociable neural pathways underlie feedback-driven and instructed aversive learning.

The Neuroscience of Pain: Biobehavioral, Developmental, and Psychosocial Mechanisms Relevant to Intervention Targets.

Chronic pain is a major problem in clinical medicine and public health, affecting approximately one in five adults, and is associated with significant societal and familial burden. Early-life adversities, psychological, and biobehavioral factors are associated with an elevated risk of the subsequent development of chronic pain. In this special issue of Psychosomatic Medicine, articles address the neuroscientific, psychological, and biobehavioral processes involved in acute and chronic pain. We focus on the following themes that emerged in this special issue: (a) risk factors and early adversity as related to chronic pain; (b) the role of expectations in shaping pain perception; and (c) mechanisms of interventions targeting pain modulation. This article concludes by outlining important new targets for research, including the neurobiology of pain, important methodological challenges, and targets for personalized pain interventions.

Anticipatory Effects on Perceived Pain: Associations With Development and Anxiety.

OBJECTIVE: Naturalistic studies suggest that expectation of adverse experiences such as pain exerts particularly strong effects on anxious youth. In healthy adults, expectation influences the experience of pain. The current study uses experimental methods to compare the effects of expectation on pain among adults, healthy youth, and youth with an anxiety disorder. METHODS: Twenty-three healthy adults, 20 healthy youth, and 20 youth with an anxiety disorder underwent procedures in which auditory cues were paired with noxious thermal stimulation. Through instructed conditioning, one cue predicted low-pain stimulation and the other predicted high-pain stimulation. At test, each cue was additionally followed by a single temperature calibrated to elicit medium pain ratings. We compared cue-based expectancy effects on pain across the three groups, based on cue effects on pain elicited on medium heat trials. RESULTS: Across all groups, as expected, participants reported greater pain with increasing heat intensity (ß = 2.29, t(41) = 29.94, p < .001). Across all groups, the critical medium temperature trials were rated as more painful in the high- relative to low-expectancy condition (ß = 1.72, t(41) = 10.48, p < .001). However, no evidence of between-group differences or continuous associations with age or anxiety was observed. CONCLUSIONS: All participants showed strong effects of expectancy on pain. No influences of development or anxiety arose. Complex factors may influence associations among anxiety, development, and pain reports in naturalistic studies. Such factors may be identified using experiments that employ more complex, yet controlled manipulations of expectancy or assess neural correlates of expectancy.

Implications of Placebo and Nocebo Effects for Clinical Practice: Expert Consensus.

BACKGROUND: Placebo and nocebo effects occur in clinical or laboratory medical contexts after administration of an inert treatment or as part of active treatments and are due to psychobiological mechanisms such as expectancies of the patient. Placebo and nocebo studies have evolved from predominantly methodological research into a far-reaching interdisciplinary field that is unravelling the neurobiological, behavioural and clinical underpinnings of these phenomena in a broad variety of medical conditions. As a consequence, there is an increasing demand from health professionals to develop expert recommendations about evidence-based and ethical use of placebo and nocebo effects for clinical practice. METHODS: A survey and interdisciplinary expert meeting by invitation was organized as part of the 1st Society for Interdisciplinary Placebo Studies (SIPS) conference in 2017. Twenty-nine internationally recognized placebo researchers participated. RESULTS: There was consensus that maximizing placebo effects and minimizing nocebo effects should lead to better treatment outcomes with fewer side effects. Experts particularly agreed on the importance of informing patients about placebo and nocebo effects and training health professionals in patient-clinician communication to maximize placebo and minimize nocebo effects. CONCLUSIONS: The current paper forms a first step towards developing evidence-based and ethical recommendations about the implications of placebo and nocebo research for medical practice, based on the current state of evidence and the consensus of experts. Future research might focus on how to implement these recommendations, including how to optimize conditions for educating patients about placebo and nocebo effects and providing training for the implementation in clinical practice.

Group-regularized individual prediction: theory and application to pain.

Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study.

An fMRI-based neurologic signature of physical pain.

BACKGROUND: Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified. METHODS: In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions--a neurologic signature--that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil. RESULTS: In study 1, the neurologic signature showed sensitivity and specificity of 94% or more (95% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93% sensitivity and specificity (95% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85% sensitivity (95% CI, 76 to 94) and 73% specificity (95% CI, 61 to 84) and with 95% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered. CONCLUSIONS: It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.).

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity.