Different brain networks mediate the effects of social and conditioned expectations on pain

Neural correlates of expected and perceived treatment efficacy concerning open-label placebos for reducing emotional distress

BACKGROUND

Treatment expectations for open-label placebos (OLPs) - placebos prescribed transparently - refer to what a person anticipates will happen as a result of taking the placebo. The actual outcome of OLP treatment may deviate from the initial expectation.

METHOD

A total of 108 participants received OLP treatment for reducing visually induced emotional distress during functional magnetic resonance imaging. They rated the expected effect of the OLP before the experiment, and evaluated the perceived effect after the experiment. Ratings reflecting the degree of outcome deviation from expectation were correlated with brain activity in regions of interest (dorsolateral/ventrolateral prefrontal cortex, anterior cingulate cortex (ACC), insula, inferior parietal cortex).

RESULTS

Activity in the ACC, the insula, and parietal regions (region-of-interest findings), as well as the parahippocampus (whole-brain finding) was lower when the perceived treatment outcome met or even exceeded expectations.

CONCLUSIONS

A positive expectation-outcome evaluation for the OLP was associated with reduced activity in brain regions decoding the salience (insula, ACC) and context of stimuli (parahippocampus). These findings shed light on the mechanisms through which OLPs influence emotion regulation.

Spatiotemporal integration of contextual and sensory information within the cortical hierarchy in human pain experience

Pain is not a mere reflection of noxious input. Rather, it is constructed through the dynamic integration of current predictions with incoming sensory input. However, the temporal dynamics of the behavioral and neural processes underpinning this integration remain elusive. In the current study involving 59 human participants, we identified a series of brain mediators that integrated cue-induced expectations with noxious inputs into ongoing pain predictions using a semicircular scale designed to capture rating trajectories. Temporal mediation analysis revealed that during the early-to-mid stages of integration, the frontoparietal and dorsal attention network regions, such as the lateral prefrontal, premotor, and parietal cortex, mediated the cue effects. Conversely, during the mid-to-late stages of integration, the somatomotor network regions mediated the effects of stimulus intensity, suggesting that the integration occurs along the cortical hierarchy from the association to sensorimotor brain systems. Our findings advance the understanding of how the brain integrates contextual and sensory information into pain experience over time.

A computational mechanism of cue-stimulus integration for pain in the brain

The brain integrates information from pain-predictive cues and noxious inputs to construct the pain experience. Although previous studies have identified neural encodings of individual pain components, how they are integrated remains elusive. Here, using a cue-induced pain task, we examined temporal functional magnetic resonance imaging activities within the state space, where axes represent individual voxel activities. By analyzing the features of these activities at the large-scale network level, we demonstrated that overall brain networks preserve both cue and stimulus information in their respective subspaces within the state space. However, only higher-order brain networks, including limbic and default mode networks, could reconstruct the pattern of participants' reported pain by linear summation of subspace activities, providing evidence for the integration of cue and stimulus information. These results suggest a hierarchical organization of the brain for processing pain components and elucidate the mechanism for their integration underlying our pain perception.

Virtual reality-based analgesia: towards a novel framework for the biopsychosocial management of chronic pain

Virtual reality (VR) holds unmeasured potential as a multicomponent tool for managing chronic pain by adapting conventional in-person biopsychosocial pain management strategies into one virtual space. We review recent evidence showcasing the successful integration of cognitive behavioural therapy, mindfulness-based stress reduction, embodiment techniques, and physical therapy into VR environments, demonstrating positive outcomes in patients with chronic pain. We propose that future clinical and basic research build on this by integrating pain neuroscience techniques to help better understand pathophysiological pain mechanisms and treatment response. This could help facilitate early assessment and personalised treatment of chronic pain using a VR-based biopsychosocial approach.

Social Learning of Placebo Effects in Pain: A Critical Review of the Literature and a Proposed Revised Model

Relatively recently, in 2009, experimental studies were undertaken to determine the role of social observational learning in forming hypoalgesic, analgesic and hyperalgesic responses to a placebo. The research findings obtained in studies published before 2018 were integrated and formed the basis of the theoretical model of social learning of placebo effects in pain proposed by Bajcar and Bąbel. This model considered the involvement of different types of modeling (ie, behavioral modeling, symbolic modeling, and verbal modeling) in shaping placebo hypoalgesia/analgesia and nocebo hyperalgesia. The model assumed that pain expectancies might be involved in observationally induced placebo effects in pain and that the effectiveness of observational learning in shaping placebo effects could be moderated by the observer's dispositions, especially empathy. Based on the latest research data, we propose a modified and significantly extended version of this model. The revised model includes the involvement of particular types of modeling in placebo effects and their role in shaping conscious pain-related expectancies. It explains the role of dispositional empathy in shaping observationally induced placebo effects. Notably, the extended version of the model considers the contribution of the characteristics of the observed person to the magnitude of placebo effects induced by social learning. PERSPECTIVE: The paper proposes a comprehensive theoretical approach to explaining the role of observational learning in shaping placebo effects in pain. The proposed model emphasizes the potential of this form of learning in shaping placebo responses and indicates factors that can modify the effectiveness of observational learning.

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

Drug treatments for pain often do not outperform placebo, and a better understanding of placebo mechanisms is needed to improve treatment development and clinical practice. In a large-scale fMRI study (N = 392) with pre-registered analyses, we tested whether placebo analgesic treatment modulates nociceptive processes, and whether its effects generalize from conditioned to unconditioned pain modalities. Placebo treatment caused robust analgesia in conditioned thermal pain that generalized to unconditioned mechanical pain. However, placebo did not decrease pain-related fMRI activity in brain measures linked to nociceptive pain, including the Neurologic Pain Signature (NPS) and spinothalamic pathway regions, with strong support for null effects in Bayes Factor analyses. In addition, surprisingly, placebo increased activity in some spinothalamic regions for unconditioned mechanical pain. In contrast, placebo reduced activity in a neuromarker associated with higher-level contributions to pain, the Stimulus Intensity Independent Pain Signature (SIIPS), and affected activity in brain regions related to motivation and value, in both pain modalities. Individual differences in behavioral analgesia were correlated with neural changes in both modalities. Our results indicate that cognitive and affective processes primarily drive placebo analgesia, and show the potential of neuromarkers for separating treatment influences on nociception from influences on evaluative processes.

Pain Rating is Worth a Thousand Words: Nocebo Hyperalgesia Induced by Verbal Modeling Prevails Over the Effects of Symbolic Modeling and Verbal Suggestion

This study compares the effectiveness of verbal modeling, symbolic modeling, and verbal suggestion in inducing nocebo hyperalgesia. It is the first study to examine the contribution of stress to observationally induced nocebo hyperalgesia. This study's experimental groups represented various sources of social information: a group of people participating in the study (verbal modeling), a single participant (symbolic modeling), and an experimenter (verbal suggestion). During the experiment, participants received electrocutaneous stimuli at the same intensity, some of which were applied with a nocebo (sham device). Participants in the verbal modeling group were acquainted with pain ratings that had allegedly been provided by other participants. The ratings suggested that other participants experienced more pain in the nocebo trials than in the control trials. In the symbolic modeling group, participants observed a videotaped model experiencing more pain in the nocebo than in the control trials. In the verbal suggestion group, participants received a verbal suggestion of hyperalgesia in the nocebo trials and no suggestion in the control trials. No manipulations were used in the control group. To investigate whether nocebo hyperalgesia is stable over time, an additional extinction phase was conducted. Nocebo hyperalgesia was induced by verbal modeling only and was partially mediated by expectancy. Stress was a significant moderator of the induced effect. Nocebo hyperalgesia was extinguished during the extinction phase. The obtained results provide potential implications for minimizing nocebo hyperalgesia in clinical practice by, for instance, controlling patients' expectancies and stress levels. PERSPECTIVE: The study shows the role of pain-related information derived from other people in shaping negative treatment experiences in the individual. Because information from others has a particular impact on individuals experiencing stress, both this information and the stress level of patients should be monitored in the treatment process.

Interpersonal physiological and psychological synchrony predict the social transmission of nocebo hyperalgesia between individuals

Witnessing another's pain can heighten pain in the observer. However, research has focused on the observer's intrapersonal experience. Here, a social transmission-chain explored the spread of socially-acquired nocebo hyperalgesia. Dyads of genuine participants were randomised to 'Generations' (G1-G3). G1-Demonstrators, observed by G2-Observers, experienced high/low thermal pain contingent on supposed activity/inactivity of a sham-treatment. G2 became Demonstrators, witnessed by G3-Observers. They experienced fixed low-temperature stimuli irrespective of sham-treatment 'activity'. G3 then Demonstrated for G4-Observers (a confederate), also experiencing low-temperature stimuli only. Pain ratings, electrodermal activity, and facial action units were measured. G1's treatment-related pain propagated throughout the chain. G2 and G3 participants showed heightened subjective and physiological response to sham-treatment, despite equivalent stimulus temperatures, and G3 never witnessing the initial pain-event. Dyadic interpersonal physiological synchrony (electrodermal activity) and psychological synchrony (Observer's ability to predict the Demonstrator's pain), predicted subsequent socially-acquired pain. Implications relate to the interpersonal spread of maladaptive pain experiences.

The social transmission of empathy relies on observational reinforcement learning

Theories of moral development propose that empathy is transmitted across individuals. However, the mechanisms through which empathy is socially transmitted remain unclear. Here, we combine computational learning models and functional MRI to investigate whether, and if so, how empathic and non-empathic responses observed in others affect the empathy of female observers. The results of three independent studies showed that watching empathic or non-empathic responses generates a learning signal that respectively increases or decreases empathy ratings of the observer. A fourth study revealed that the learning-related transmission of empathy is stronger when observing human rather than computer demonstrators. Finally, we show that the social transmission of empathy alters empathy-related responses in the anterior insula, i.e., the same region that correlated with empathy baseline ratings, as well as its functional connectivity with the temporoparietal junction. Together, our findings provide a computational and neural mechanism for the social transmission of empathy that accounts for changes in individual empathic responses in empathic and non-empathic social environments.

The central renin-angiotensin system: A genetic pathway, functional decoding, and selective target engagement characterization in humans

Accumulating evidence suggests that the brain renin angiotensin system (RAS) plays a pivotal role in the regulation of cognition and behavior as well as in the neuropathology of neurological and mental disorders. The angiotensin II type 1 receptor (AT1R) mediates most functional and neuropathology-relevant actions associated with the central RAS. However, an overarching comprehension to guide translation and utilize the therapeutic potential of the central RAS in humans is currently lacking. We conducted a comprehensive characterization of the RAS using an innovative combination of transcriptomic gene expression mapping, image-based behavioral decoding, and pre-registered randomized controlled discovery-replication pharmacological resting-state functional magnetic resonance imaging (fMRI) trials (N = 132) with a selective AT1R antagonist. The AT1R exhibited a particular dense expression in a subcortical network encompassing the thalamus, striatum, and amygdalo-hippocampal formation. Behavioral decoding of the AT1R gene expression brain map showed an association with memory, stress, reward, and motivational processes. Transient pharmacological blockade of the AT1R further decreased neural activity in subcortical systems characterized by a high AT1R expression, while increasing functional connectivity in the cortico-basal ganglia-thalamo-cortical circuitry. Effects of AT1R blockade on the network level were specifically associated with the transcriptomic signatures of the dopaminergic, opioid, acetylcholine, and corticotropin-releasing hormone signaling systems. The robustness of the results was supported in an independent pharmacological fMRI trial. These findings present a biologically informed comprehensive characterization of the central AT1R pathways and their functional relevance on the neural and behavioral level in humans.

NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

Learning pain from others: a systematic review and meta-analysis of studies on placebo hypoalgesia and nocebo hyperalgesia induced by observational learning

ABSTRACT

Observing someone experience pain relief or exacerbation after an intervention may induce placebo hypoalgesia or nocebo hyperalgesia. Understanding the factors that contribute to these effects could help in the development of strategies for optimizing treatment of chronic pain conditions. We systematically reviewed and meta-analyzed the literature on placebo hypoalgesia and nocebo hyperalgesia induced by observational learning (OL). A systematic literature search was conducted in the databases PubMed, PsycINFO, Web of Science, ScienceDirect, PsycARTICLES, Scopus, and Academic Search Ultimate. Twenty-one studies were included in the systematic review, 17 of which were suitable for meta-analysis (18 experiments; n = 764 healthy individuals). The primary end point was the standardized mean difference (SMD) for pain following placebo cues associated during OL with low vs high pain. Observational learning had a small-to-medium effect on pain ratings (SMD 0.44; 95% confidence interval [CI] 0.21-0.68; P < 0.01) and a large effect on pain expectancy (SMD 1.11; 95% CI 0.49-2.04; P < 0.01). The type of observation (in-person vs videotaped) modulated the magnitude of placebo hypoalgesia/nocebo hyperalgesia ( P < 0.01), whereas placebo type did not ( P = 0.23). Finally, OL was more effective when observers' empathic concern (but no other empathy-related factors) was higher ( r = 0.14; 95% CI 0.01-0.27; P = 0.03). Overall, the meta-analysis demonstrates that OL can shape placebo hypoalgesia and nocebo hyperalgesia. More research is needed to identify predictors of these effects and to study them in clinical populations. In the future, OL could be an important tool to help maximize placebo hypoalgesia in clinical settings.

Brain mediators of biased social learning of self-perception in social anxiety disorder

Social anxiety disorder (SAD) is characterized by an excessive fear of social evaluation and a persistently negative view of the self. Here we test the hypothesis that negative biases in brain responses and in social learning of self-related information contribute to the negative self-image and low self-esteem characteristic of SAD. Adult participants diagnosed with social anxiety (N = 21) and matched controls (N = 23) rated their performance and received social feedback following a stressful public speaking task. We investigated how positive versus negative social feedback altered self-evaluation and state self-esteem and used functional Magnetic Resonance Imaging (fMRI) to characterize brain responses to positive versus negative feedback. Compared to controls, participants with SAD updated their self-evaluation and state self-esteem significantly more based on negative compared to positive social feedback. Responses in the frontoparietal network correlated with and mirrored these behavioral effects, with greater responses to positive than negative feedback in non-anxious controls but not in participants with SAD. Responses to social feedback in the anterior insula and other areas mediated the effects of negative versus positive feedback on changes in self-evaluation. In non-anxious participants, frontoparietal brain areas may contribute to a positive social learning bias. In SAD, frontoparietal areas are less recruited overall and less attuned to positive feedback, possibly reflecting differences in attention allocation and cognitive regulation. More negatively biased brain responses and social learning could contribute to maintaining a negative self-image in SAD and other internalizing disorders, thereby offering important new targets for interventions.

Dysfunctional Activation of the Dorsolateral Prefrontal Cortex During Pain Anticipation Is Associated With Altered Subsequent Pain Experience in Fibromyalgia Patients

The ability to accurately predict pain is an adaptive feature in healthy individuals. However, in chronic pain, this mechanism may be selectively impaired and can lead to increased anxiety and excessive avoidance behavior. Recently, we reported the first data demonstrating brain activation in fibromyalgia (FM) patients during conditioned pain responses, in which FM patients revealed a tendency to form new pain-related associations rather than extinguishing irrelevant ones. The aim of the present study was to extend our previous analysis, to elucidate potential neural divergences between subjects with FM (n = 65) and healthy controls (HCs) (n = 33) during anticipatory information (ie, prior to painful stimulus onset). Using functional magnetic resonance imaging (fMRI), the current analyses include 1) a congruently cued paradigm of low and high pain predictive cues, followed by 2) an incongruently cued paradigm where low and high pain predictive cues were followed by an identical mid-intensity painful pressure. During incongruently cued high-pain associations, FM exhibited reduced left dorsolateral prefrontal cortex (dlPFC) activation compared to HCs, which was followed by an altered subsequent pain experience in FM, as patients continued to rate the following painful stimuli as high, even though the pressure had been lowered. During congruently cued low pain anticipation, FM exhibited decreased right dlPFC activation compared to HCs, as well as decreased brain connectivity between brain regions implicated in cognitive modulation of pain (dlPFC) and nociceptive processing (primary somatosensory cortex/postcentral gyrus [S1] and supplementary motor area [SMA]/midcingulate cortex [MCC]). These results may reflect an important feature of validating low pain expectations in HCs and help elucidate behavioral reports of impaired safety processing in FM patients. PERSPECTIVE: FM exhibited a stronger conditioned pain response for high-pain associations, which was associated with reduced dlPFC activation during the incongruent trial. During (congruent and incongruent) low pain associations, FM dlPFC brain activation remained indifferent. Imbalances in threat and safety pain perception may be an important target for psychotherapeutic interventions.

Implicit, But Not Explicit, Emotion Regulation Relieves Unpleasant Neural Responses Evoked by High-Intensity Negative Images

Evidence suggests that explicit reappraisal has limited regulatory effects on high-intensity emotions, mainly due to the depletion of cognitive resources occupied by the high-intensity emotional stimulus itself. The implicit form of reappraisal has proved to be resource-saving and therefore might be an ideal strategy to achieve the desired regulatory effect in high-intensity situations. In this study, we explored the regulatory effect of explicit and implicit reappraisal when participants encountered low- and high-intensity negative images. The subjective emotional rating indicated that both explicit and implicit reappraisal down-regulated negative experiences, irrespective of intensity. However, the amplitude of the parietal late positive potential (LPP; a neural index of experienced emotional intensity) showed that only implicit reappraisal had significant regulatory effects in the high-intensity context, though both explicit and implicit reappraisal successfully reduced the emotional neural responses elicited by low-intensity negative images. Meanwhile, implicit reappraisal led to a smaller frontal LPP amplitude (an index of cognitive cost) compared to explicit reappraisal, indicating that the implementation of implicit reappraisal consumes limited cognitive control resources. Furthermore, we found a prolonged effect of implicit emotion regulation introduced by training procedures. Taken together, these findings not only reveal that implicit reappraisal is suitable to relieve high-intensity negative experiences as well as neural responses, but also highlight the potential benefit of trained implicit regulation in clinical populations whose frontal control resources are limited.

Peer-to-peer: The Social Transmission of Symptoms Online

BACKGROUND

Social learning can be highly adaptive-for example, avoiding a hotplate your friend just burnt themselves on-but it has also been implicated in symptom transmission. Social learning is particularly pertinent given the rapid increase in the use of online mediums for social interaction. Yet, little is known about the social transmission of symptoms online or social chains extending further than a single model-observer interaction.

PURPOSE

To explore whether socially induced symptoms could be propagated through a three-generation social transmission chain in an online setting.

METHODS

We explored the social transmission of cybersickness following a virtual reality (VR) experience through online webcam interactions. One hundred and seventy-seven adults viewed a VR video in one of four links along a social transmission chain, after: viewing an actor model cybersickness to the VR video (First-Generation); viewing the First-Generation participant undergo VR (Second-Generation); viewing the Second-Generation participant undergo VR (Third-Generation); or naïve (Control).

RESULTS

Cybersickness was strongest in First-Generation participants, indicating social transmission from the model. This was mediated by expectancy and anxiety. Whether or not subsequent generations experienced cybersickness depended on what the observed participant verbally reported, which is consistent with social transmission.

CONCLUSIONS

Results demonstrate that symptoms can be readily transmitted online, and that expectancy and anxiety are involved. Although it is inconclusive as to whether symptoms can propagate along a social transmission chain, there is some evidence of protection from symptoms when a model who does not report any symptoms is observed. As such, this research highlights the role of social transmission in the modulation of symptoms through virtual mediums.

A machine learning based approach towards high-dimensional mediation analysis

Mediation analysis is used to investigate the role of intermediate variables (mediators) that lie in the path between an exposure and an outcome variable. While significant research has focused on developing methods for assessing the influence of mediators on the exposure-outcome relationship, current approaches do not easily extend to settings where the mediator is high-dimensional. These situations are becoming increasingly common with the rapid increase of new applications measuring massive numbers of variables, including brain imaging, genomics, and metabolomics. In this work, we introduce a novel machine learning based method for identifying high dimensional mediators. The proposed algorithm iterates between using a machine learning model to map the high-dimensional mediators onto a lower-dimensional space, and using the predicted values as input in a standard three-variable mediation model. Hence, the machine learning model is trained to maximize the likelihood of the mediation model. Importantly, the proposed algorithm is agnostic to the machine learning model that is used, providing significant flexibility in the types of situations where it can be used. We illustrate the proposed methodology using data from two functional Magnetic Resonance Imaging (fMRI) studies. First, using data from a task-based fMRI study of thermal pain, we combine the proposed algorithm with a deep learning model to detect distributed, network-level brain patterns mediating the relationship between stimulus intensity (temperature) and reported pain at the single trial level. Second, using resting-state fMRI data from the Human Connectome Project, we combine the proposed algorithm with a connectome-based predictive modeling approach to determine brain functional connectivity measures that mediate the relationship between fluid intelligence and working memory accuracy. In both cases, our multivariate mediation model links exposure variables (thermal pain or fluid intelligence), high dimensional brain measures (single-trial brain activation maps or resting-state brain connectivity) and behavioral outcomes (pain report or working memory accuracy) into a single unified model. Using the proposed approach, we are able to identify brain-based measures that simultaneously encode the exposure variable and correlate with the behavioral outcome.

From past pain to future pain through the pain of others: Information about other people's pain ratings can alleviate our subsequent pain

BACKGROUND

Previous studies have shown that pain memories have a profound impact on subsequent pain experiences. This study investigated whether pain ratings derived from other people can modify an individual's memory of past pain. This study also examined whether pain memory modified by others' pain ratings determines subsequent pain experiences.

METHODS

Participants were divided into two groups: an experimental group and a control group. Participants in both groups were exposed to pain stimulation; then, they recalled its intensity twice over a period of time; after a break, they were again exposed to pain stimulation of the same intensity. The final sample consisted of 53 participants. The only difference between the experimental group and the control group was that in the former the pain ratings of other alleged participants were presented between the two consecutive pain recalls. These ratings suggested that other people experienced the same pain as less intense.

RESULTS

The pain ratings derived from other people did not alter the pain memory; nevertheless, they affected an individual's next pain experience even for a certain period of time after their presentation. This type of pain-related information shaped participants' subsequent pain experiences regardless of their empathy, conformity, and susceptibility to social influence.

CONCLUSIONS

Information on pain derived from other people not only shapes the response to a novel stimulation but also substantially modifies the subsequent experience of that stimulation.

SIGNIFICANCE

The study demonstrates the importance of social information on pain and provides evidence that this type of information substantially modifies the subsequent experience of the same pain. These results suggest that social information on pain can be used to alleviate pain associated with recurring medical procedures and thus increase patients' willingness to continue treatment.

An fMRI-Based Brain Marker of Individual Differences in Delay Discounting

Individual differences in delay discounting-how much we discount future compared to immediate rewards-are associated with general life outcomes, psychopathology, and obesity. Here, we use machine learning on fMRI activity during an intertemporal choice task to develop a functional brain marker of these individual differences in human adults. Training and cross-validating the marker in one dataset (Study 1, N = 110 male adults) resulted in a significant prediction-outcome correlation (r = 0.49), generalized to predict individual differences in a completely independent dataset (Study 2: N = 145 male and female adults, r = 0.45), and predicted discounting several weeks later. Out-of-sample responses of the functional brain marker, but not discounting behavior itself, differed significantly between overweight and lean individuals in both studies, and predicted fasting-state blood levels of insulin, c-peptide, and leptin in Study 1. Significant predictive weights of the marker were found in cingulate, insula, and frontoparietal areas, among others, suggesting an interplay among regions associated with valuation, conflict processing, and cognitive control. This new functional brain marker is a step toward a generalizable brain model of individual differences in delay discounting. Future studies can evaluate it as a potential transdiagnostic marker of altered decision-making in different clinical and developmental populations.SIGNIFICANCE STATEMENT People differ substantially in how much they prefer smaller sooner rewards or larger later rewards such as spending money now versus saving it for retirement. These individual differences are generally stable over time and have been related to differences in mental and bodily health. What is their neurobiological basis? We applied machine learning to brain-imaging data to identify a novel brain activity pattern that accurately predicts how much people prefer sooner versus later rewards, and which can be used as a new brain-based measure of intertemporal decision-making in future studies. The resulting functional brain marker also predicts overweight and metabolism-related blood markers, providing new insight into the possible links between metabolism and the cognitive and brain processes involved in intertemporal decision-making.

Pain, from perception to action: A computational perspective

Pain is driven by sensation and emotion, and in turn, it motivates decisions and actions. To fully appreciate the multidimensional nature of pain, we formulate the study of pain within a closed-loop framework of sensory-motor prediction. In this closed-loop cycle, prediction plays an important role, as the interaction between prediction and actual sensory experience shapes pain perception and subsequently, action. In this Perspective, we describe the roles of two prominent computational theories-Bayesian inference and reinforcement learning-in modeling adaptive pain behaviors. We show that prediction serves as a common theme between these two theories, and that each of these theories can explain unique aspects of the pain perception-action cycle. We discuss how these computational theories and models can improve our mechanistic understandings of pain-centered processes such as anticipation, attention, placebo hypoalgesia, and pain chronification.

[Placebo effects in analgesia : Influence of expectations on the efficacy and tolerability of analgesic treatment]

Expectations of patients influence the perception and neuronal processing of acute and chronic pain and modulate the effectiveness of analgesic treatment. The expectation of treatment is not only the most important determinant of placebo analgesia. Expectations of treatment also influence the efficacy and tolerability of "active" pharmacological and non-pharmacological treatment of pain. Recent insights into the psychological and neurobiological mechanisms underlying the clinically relevant effects of treatment expectations enable and call for the systematic integration and modulation of treatment expectations into analgesic treatment concepts. Such a strategy promises to optimize analgesic treatment and to prevent or reduce the burden of unwanted side effects and the misuse of analgesics, particularly of opioids. This review highlights the current concepts, recent achievements and also challenges and key open research questions.

Placebo and nocebo effects: from observation to harnessing and clinical application

Placebo and nocebo effects are salubrious benefits and negative outcomes attributable to non-specific symbolic components. Leveraging advanced experimental and analytical approaches, recent studies have elucidated complicated neural mechanisms that may serve as a solid basis for harnessing the powerful self-healing and self-harming capacities and applying these findings to improve medical practice and minimize the unintended exacerbation of symptoms in medical practice. We review advances in employing psychosocial, pharmacological, and neuromodulation approaches to modulate/harness placebo and nocebo effects. While these approaches show promising potential, translating these research findings into clinical settings still requires careful methodological, technical, and ethical considerations.

Targeting neural correlates of placebo effects

Harnessing the placebo effects would prompt critical ramifications for research and clinical practice. Noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation and multifocal transcranial electric stimulation, could manipulate the placebo response by modulating the activity and excitability of its neural correlates. To identify potential stimulation targets, we conducted a meta-analysis to investigate placebo-associated regions in healthy volunteers, including studies with emotional components and painful stimuli. Using biophysical modeling, we identified NIBS solutions to manipulate placebo effects by targeting either a single key region or multiple connected areas. Moving to a network-oriented approach, we then ran a quantitative network mapping analysis on the functional connectivity profile of clusters emerging from the meta-analysis. As a result, we suggest a multielectrode optimized montage engaging the connectivity patterns of placebo-associated functional brain networks. These NIBS solutions hope to provide a starting point to actively control, modulate or enhance placebo effects in future clinical studies and cognitive enhancement studies.

Instructions and experiential learning have similar impacts on pain and pain-related brain responses but produce dissociations in value-based reversal learning

Recent data suggest that interactions between systems involved in higher order knowledge and associative learning drive responses during value-based learning. However, it is unknown how these systems impact subjective responses, such as pain. We tested how instructions and reversal learning influence pain and pain-evoked brain activation. Healthy volunteers (n=40) were either instructed about contingencies between cues and aversive outcomes or learned through experience in a paradigm where contingencies reversed three times. We measured predictive cue effects on pain and heat-evoked brain responses using functional magnetic resonance imaging. Predictive cues dynamically modulated pain perception as contingencies changed, regardless of whether participants received contingency instructions. Heat-evoked responses in the insula, anterior cingulate, and other regions updated as contingencies changed, and responses in the prefrontal cortex mediated dynamic cue effects on pain, whereas responses in the brainstem's rostroventral medulla (RVM) were shaped by initial contingencies throughout the task. Quantitative modeling revealed that expected value was shaped purely by instructions in the Instructed Group, whereas expected value updated dynamically in the Uninstructed Group as a function of error-based learning. These differences were accompanied by dissociations in the neural correlates of value-based learning in the rostral anterior cingulate, thalamus, and posterior insula, among other regions. These results show how predictions dynamically impact subjective pain. Moreover, imaging data delineate three types of networks involved in pain generation and value-based learning: those that respond to initial contingencies, those that update dynamically during feedback-driven learning as contingencies change, and those that are sensitive to instruction. Together, these findings provide multiple points of entry for therapies designs to impact pain.

Interpreting mental state decoding with deep learning models

In mental state decoding, researchers aim to identify the set of mental states (e.g., experiencing happiness or fear) that can be reliably identified from the activity patterns of a brain region (or network). Deep learning (DL) models are highly promising for mental state decoding because of their unmatched ability to learn versatile representations of complex data. However, their widespread application in mental state decoding is hindered by their lack of interpretability, difficulties in applying them to small datasets, and in ensuring their reproducibility and robustness. We recommend approaching these challenges by leveraging recent advances in explainable artificial intelligence (XAI) and transfer learning, and also provide recommendations on how to improve the reproducibility and robustness of DL models in mental state decoding.

Expectation effects in working memory training

There is a growing body of research focused on developing and evaluating behavioral training paradigms meant to induce enhancements in cognitive function. It has recently been proposed that one mechanism through which such performance gains could be induced involves participants' expectations of improvement. However, no work to date has evaluated whether it is possible to cause changes in cognitive function in a long-term behavioral training study by manipulating expectations. In this study, positive or negative expectations about cognitive training were both explicitly and associatively induced before either a working memory training intervention or a control intervention. Consistent with previous work, a main effect of the training condition was found, with individuals trained on the working memory task showing larger gains in cognitive function than those trained on the control task. Interestingly, a main effect of expectation was also found, with individuals given positive expectations showing larger cognitive gains than those who were given negative expectations (regardless of training condition). No interaction effect between training and expectations was found. Exploratory analyses suggest that certain individual characteristics (e.g., personality, motivation) moderate the size of the expectation effect. These results highlight aspects of methodology that can inform future behavioral interventions and suggest that participant expectations could be capitalized on to maximize training outcomes.

The influence of social signals on the self-experience of pain: A neuroimaging review

Researchers in cognitive neuroscience have investigated extensively how psychological factors shape the processing and perception of pain using behavioral, physiological, and neuroimaging methods. However, social influences of pain, an essential part of biopsychosocial pain models, have received relatively little attention. This is particularly true for the neurobiological mechanisms underlying social modulations on pain. Therefore, this review discusses the findings of recent neuroimaging studies measuring the effects of social manipulations on pain perception (e.g., verbal and non-verbal social signals, social interaction style, conformity, social support, and sociocultural mediators). Finally, a schematic summary of the different social modulatory themes is presented.

Observing treatment outcomes in other patients can elicit augmented placebo effects on pain treatment: a double-blinded randomized clinical trial with patients with chronic low back pain

ABSTRACT

Clinical research on social observational learning (SoL) as an underlying mechanism for inducing expectancy and eliciting analgesic placebo effects is lacking. This double-blinded randomized controlled clinical trial investigated the influence of SoL on medication-augmenting placebo effects in 44 patients with chronic low back pain. Our hypothesis was that observing positive drug effects on pain and mobility in another patient could increase pain reduction and functional capacity. To test this, we compared the effects of observing positive treatment outcomes in a sham patient (the social learning group [SoLG]) vs hearing the same sham patient report neutral effects (the control group). In the SoLG, the sham patient told peers about pain reduction due to amitriptyline and demonstrated his improved mobility by bending forwards and sideways while he told the control group only that he was taking amitriptyline. The primary outcome was a reduction in clinical low back pain self-ratings. The secondary outcome was perceptions of pain-related disability. The exploratory outcome was mood and coping statements. Data collection occurred before and after the intervention and 2 weeks later. After the intervention, pain decreased in both groups (F [1, 41] = 7.16, P < 0.05, d = 0.83), with no difference between groups. However, the SoLG showed a significantly larger decrease in perceived disability (F [1, 41] = 5, P < 0.05, d = 0.63). The direct observation of patient with chronic low back pain of positive treatment outcomes in the sham patient seems to have enhanced the treatment effects while indirect verbal reports of reduced pain did not.

Pain modalities in the body and brain: Current knowledge and future perspectives

Development and validation of pain biomarkers has become a major issue in pain research. Recent advances in multimodal data acquisition have allowed researchers to gather multivariate and multilevel whole-body measurements in patients with pain conditions, and data analysis techniques such as machine learning have led to novel findings in neural biomarkers for pain. Most studies have focused on the development of a biomarker to predict the severity of pain with high precision and high specificity, however, a similar approach to discriminate different modalities of pain is lacking. Identification of more accurate and specific pain biomarkers will require an in-depth understanding of the modality specificity of pain. In this review, we summarize early and recent findings on the modality specificity of pain in the brain, with a focus on distinct neural activity patterns between chronic clinical and acute experimental pain, direct, social, and vicarious pain, and somatic and visceral pain. We also suggest future directions to improve our current strategy of pain management using our knowledge of modality-specific aspects of pain.

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.

Temporal Predictability Modulates Cortical Activity and Functional Connectivity in the Frontoparietal Network in 6-Month-Old Infants

Despite the abundance of behavioral evidence showing the interaction between attention and prediction in infants, the neural underpinnings of this interaction are not yet well-understood. The endogenous attentional function in adults have been largely localized to the frontoparietal network. However, resting-state and neuroanatomical investigations have found that this frontoparietal network exhibits a protracted developmental trajectory and involves weak and unmyelinated long-range connections early in infancy. Can this developmentally nascent network still be modulated by predictions? Here, we conducted the first investigation of infant frontoparietal network engagement as a function of the predictability of visual events. Using functional near-infrared spectroscopy, the hemodynamic response in the frontal, parietal, and occipital lobes was analyzed as infants watched videos of temporally predictable or unpredictable sequences. We replicated previous findings of cortical signal attenuation in the frontal and sensory cortices in response to predictable sequences and extended these findings to the parietal lobe. We also estimated background functional connectivity (i.e., by regressing out task-evoked responses) to reveal that frontoparietal functional connectivity was significantly greater during predictable sequences compared to unpredictable sequences, suggesting that this frontoparietal network may underlie how the infant brain communicates predictions. Taken together, our results illustrate that temporal predictability modulates the activation and connectivity of the frontoparietal network early in infancy, supporting the notion that this network may be functionally available early in life despite its protracted developmental trajectory.

Brain Structural Changes during Juvenile Fibromyalgia: Relationships with Pain, Fatigue and Functional Disability

Objective

Juvenile fibromyalgia (FM) is a prevalent chronic pain condition affecting children and adolescents worldwide during a critical period of brain development. To date, no published studies have addressed the pathophysiology of juvenile FM. This study was undertaken to characterize gray matter volume (GMV) alterations in juvenile FM patients for the first time, and to investigate their functional and clinical relevance.

Methods

Thirty‐four female adolescents with juvenile FM and 38 healthy adolescents underwent a structural magnetic resonance imaging examination and completed questionnaires assessing core juvenile FM symptoms. Using voxel‐based morphometry, we assessed between‐group GMV differences and associations between GMV and functional disability, fatigue, and pain interference in juvenile FM. We also studied whether validated brain patterns predicting pain, cognitive control, or negative emotion were amplified/attenuated in juvenile FM patients and whether structural alterations reported in adult FM were replicated in adolescents with juvenile FM.

Results

Compared to controls, juvenile FM patients showed GMV reductions in the anterior midcingulate cortex (aMCC) region (family‐wise error corrected P [P_FWE‐corr] = 0.04; estimated with threshold‐free cluster enhancement [TFCE]; n = 72) associated with pain. Within the juvenile FM group, patients reporting higher functional disability had larger GMV in inferior frontal regions (P_FWE‐corr = 0.006; TFCE estimated; n = 34) linked to affective, self‐referential, and language‐related processes. Last, GMV reductions in juvenile FM showed partial overlap with findings in adult FM, specifically for the anterior/posterior cingulate cortices (P = 0.02 and P = 0.03, respectively; n = 72).

Conclusion

Pain‐related aMCC reductions may be a structural hallmark of juvenile FM, whereas alterations in regions involved in emotional, self‐referential, and language‐related processes may predict disease impact on patients’ well‐being. The partial overlap between juvenile and adult FM findings strengthens the importance of early symptom identification and intervention to prevent the transition to adult forms of the disease.

Optimising treatment expectations in chronic lower back pain through observing others: a study protocol for a randomised clinical trial

INTRODUCTION

Chronic lower back pain (CLBP) is a frequent cause of medical consultations worldwide, and it results in decreased quality of life and disability. Current treatments for CLBP are often not effective, and alternatives are urgently needed. Three promising possibilities have emerged: (1) open-label placebo treatment reduces chronic pain, (2) placebo treatment is as efficacious as opioid treatment with a high correlation between patient expectation and treatment outcome, and (3) observing positive effects in another patient can improve functional capacity. We hypothesise that treatment expectations can be positively influenced through social observation and improve treatment outcome.

METHODS AND ANALYSIS

In our clinical trial, we will randomise patients with CLBP into five groups. Two groups receive either a 3 week course of treatment with an analgesic (ANA) (metamizole/dipyrone) or with open-label placebos (OLP). For one of each group, we will build treatment expectations through observational learning and assess its impact on the treatment. For this purpose, one group each will watch either a positive or a neutral video. The intervention groups will be compared with a control group that will not be given any medication or observational learning. Participants will be recruited via all institutions in the Hamburg metropolitan area that treat patients with CLBP. Patients are eligible for inclusion if they are at least 18 years or older, have CLBP (of at least 3 months duration), and agree to potentially receive an active ANA or an OLP. Patients with pain-related "red flags" will be excluded. The study requires 150 participants (30 participants per group) to assess the differences in the primary outcome, pain intensity. Secondary outcomes include changes in treatment expectations, anxiety, comorbid depression, stress-related neuroendocrine measures, functional and structural connectivity, functional capacity, and ANA consumption. All outcomes and treatment expectations will be measured before and after the intervention and 3 months post-intervention.

ETHICS AND DISSEMINATION

Ethical approval was obtained in January 2020 from the Hamburg Medical Ethics Council (ref number PV7067). Outcomes will be disseminated through publications in peer-reviewed journals and presentations at national and international conference meetings.

TRIAL REGISTRATION NUMBER

The approved trial protocol was registered at the German Clinical Trials Register (DRKS) and can be found at drks.de (Identifier: DRKS00024418).

Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain

Pain is not only shaped by sensory information but also by an individual’s expectations. Here, we investigated how commonly analyzed electroencephalography (EEG) responses to pain signal sensory information, expectations, and discrepancies thereof (prediction errors) in the processing of pain. Bayesian analysis confirmed that pain perception was shaped by objective sensory information and expectations. In contrast, EEG responses at different latencies (including the N1, N2, and P2 components) and frequencies (including alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Thus, EEG responses to pain are more involved in signaling sensory information than in signaling expectations or prediction errors. Expectation effects are obviously mediated by other brain mechanisms than the effects of sensory information on pain.

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual’s expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.

Expectations: How and when do they contribute to placebo analgesia?

In placebo research, expectations are highlighted as one of the most influential subjective factors. While some studies have shown a relationship between expectations and pain relief, others have not. However, little is known about how methods of assessment of expectations may affect these conclusions. One of the fundamental considerations is that participants in placebo trials rate their expectations when prompted to rate them on scales in advance, but are less likely to report their prior expectations, when asked to report their experience retroactively in an unprompted manner, often expressing, for example, prior hope or wishes of recovery. This article presents previously unpublished data to elucidate and explore the concepts highlighted by individuals in a placebo analgesia trial when assessed in a prompted and unprompted manner. The data corroborates the role of expectations involved in placebo effects, particularly in placebo analgesia. Thus, the question may be a matter of how and when expectations contribute to placebo effects, rather than if.

A distributed fMRI-based signature for the subjective experience of fear

The specific neural systems underlying the subjective feeling of fear are debated in affective neuroscience. Here, we combine functional MRI with machine learning to identify and evaluate a sensitive and generalizable neural signature predictive of the momentary self-reported subjective fear experience across discovery (n = 67), validation (n = 20) and generalization (n = 31) cohorts. We systematically demonstrate that accurate fear prediction crucially requires distributed brain systems, with important contributions from cortical (e.g., prefrontal, midcingulate and insular cortices) and subcortical (e.g., thalamus, periaqueductal gray, basal forebrain and amygdala) regions. We further demonstrate that the neural representation of subjective fear is distinguishable from the representation of conditioned threat and general negative affect. Overall, our findings suggest that subjective fear, which exhibits distinct neural representation with some other aversive states, is encoded in distributed systems rather than isolated 'fear centers'.

Neural mediators of subjective and autonomic responding during threat learning and regulation

Threat learning elicits robust changes across multiple affective domains, including changes in autonomic indices and subjective reports of fear and anxiety. It has been argued that the underlying causes of such changes may be dissociable at a neural level, but there is currently limited evidence to support this notion. To address this, we examined the neural mediators of trial-by-trial skin conductance responses (SCR), and subjective reports of anxious arousal and valence in participants (n = 27; 17 females) performing a threat reversal task during ultra-high field functional magnetic resonance imaging. This allowed us to identify brain mediators during initial threat learning and subsequent threat reversal. Significant neural mediators of anxious arousal during threat learning included the dorsal anterior cingulate, anterior insula cortex (AIC), and ventromedial prefrontal cortex (vmPFC), subcortical regions including the amygdala, ventral striatum, caudate and putamen, and brain-stem regions including the pons and midbrain. By comparison, autonomic changes (SCR) were mediated by a subset of regions embedded within this broader circuitry that included the caudate, putamen and thalamus, and two distinct clusters within the vmPFC. The neural mediators of subjective negative valence showed prominent effects in posterior cortical regions and, with the exception of the AIC, did not overlap with threat learning task effects. During threat reversal, positive mediators of both subjective anxious arousal and valence mapped to the default mode network; this included the vmPFC, posterior cingulate, temporoparietal junction, and angular gyrus. Decreased SCR during threat reversal was positively mediated by regions including the mid cingulate, AIC, two sub-regions of vmPFC, the thalamus, and the hippocampus. Our findings add novel evidence to support distinct underlying neural processes facilitating autonomic and subjective responding during threat learning and threat reversal. The results suggest that the brain systems engaged in threat learning mostly capture the subjective (anxious arousal) nature of the learning process, and that appropriate responding during threat reversal is facilitated by participants engaging self- and valence-based processes. Autonomic changes (SCR) appear to involve distinct facilitatory and regulatory contributions of vmPFC sub-regions.

Recommendations for the Development of Socioeconomically-Situated and Clinically-Relevant Neuroimaging Models of Pain

Pain is a complex, multidimensional experience that emerges from interactions among sensory, affective, and cognitive processes in the brain. Neuroimaging allows us to identify these component processes and model how they combine to instantiate the pain experience. However, the clinical impact of pain neuroimaging models has been limited by inadequate population sampling - young healthy college students are not representative of chronic pain patients. The biopsychosocial approach to pain management situates a person's pain within the diverse socioeconomic environments they live in. To increase the clinical relevance of pain neuroimaging models, a three-fold biopsychosocial approach to neuroimaging biomarker development is recommended. The first level calls for the development of diagnostic biomarkers via the standard population-based (nomothetic) approach with an emphasis on diverse sampling. The second level calls for the development of treatment-relevant models via a constrained person-based (idiographic) approach tailored to unique individuals. The third level calls for the development of prevention-relevant models via a novel society-based (social epidemiologic) approach that combines survey and neuroimaging data to predict chronic pain risk based on one's socioeconomic conditions. The recommendations in this article address how we can leverage pain's complexity in service of the patient and society by modeling not just individuals and populations, but also the socioeconomic structures that shape any individual's expectations of threat, safety, and resource availability.

[Treatment expectations for postoperative pain]

Hintergrund

Präoperative Behandlungserwartungen haben einen deutlichen Einfluss auf die postoperativen Schmerzen und Behandlungsergebnisse. Positive Erwartungen sind ein wichtiger Mechanismus von Placeboeffekten und negative Erwartungen ein wichtiger Mechanismus von Noceboeffekten.

Fragestellung

Welchen Einfluss haben Behandlungserwartungen, wie werden diese im klinischen Setting erhoben und wie können diese Erkenntnisse in der klinischen Praxis umgesetzt werden?

Material und Methoden

Es wurde eine Literatursuche für klinische Studien mit den Schlagwörtern „expectation“ AND („postoperative“ OR „surgery“) durchgeführt. Ausgewählt wurden alle aktuellen englischen und deutschen Artikel. Zusätzlich wurden die Literaturverzeichnisse der gefundenen Artikel untersucht und mit aufgenommen.

Ergebnisse

Insgesamt 158 Artikel wurden gefunden, von denen 49 Artikel Erwartungen erheben und ein postoperatives Behandlungsergebnis einbeziehen. Die meisten Artikel untersuchen Erwartungen in der Baseline-Erhebung, um nachzuweisen, dass sich Gruppen in Gruppenvergleichen präoperativ nicht voneinander unterscheiden. Die Studien, die den Einfluss von Erwartungen prospektiv untersuchen, verwenden sehr unterschiedliche Messverfahren, um das Konstrukt „Erwartung“ zu erheben. Somit ist ein Vergleich zwischen den Studien schwer möglich. Es gibt wenige Studien, die untersuchen, ob und wie die Erwartungen perioperativ beeinflusst werden können, und die praxisrelevante Interventionen zu deren Veränderung entwickelt haben.

Schlussfolgerung

Für eine fundierte Untersuchung der Behandlungserwartung sollten in klinischen Studien valide und reliable Messverfahren verwendet werden. Weitere Studien sollten sich mit Interventionsmöglichkeiten auseinandersetzen, damit Behandlungserwartungen auch in die klinische Standardbehandlung einbezogen werden können.

Associative learning and extinction of conditioned threat predictors across sensory modalities

The formation and persistence of negative pain-related expectations by classical conditioning remain incompletely understood. We elucidated behavioural and neural correlates involved in the acquisition and extinction of negative expectations towards different threats across sensory modalities. In two complementary functional magnetic resonance imaging studies in healthy humans, differential conditioning paradigms combined interoceptive visceral pain with somatic pain (study 1) and aversive tone (study 2) as exteroceptive threats. Conditioned responses to interoceptive threat predictors were enhanced in both studies, consistently involving the insula and cingulate cortex. Interoceptive threats had a greater impact on extinction efficacy, resulting in disruption of ongoing extinction (study 1), and selective resurgence of interoceptive CS-US associations after complete extinction (study 2). In the face of multiple threats, we preferentially learn, store, and remember interoceptive danger signals. As key mediators of nocebo effects, conditioned responses may be particularly relevant to clinical conditions involving disturbed interoception and chronic visceral pain.

The self in context: brain systems linking mental and physical health

Increasing evidence suggests that mental health and physical health are linked by neural systems that jointly regulate somatic physiology and high-level cognition. Key systems include the ventromedial prefrontal cortex and the related default-mode network. These systems help to construct models of the 'self-in-context', compressing information across time and sensory modalities into conceptions of the underlying causes of experience. Self-in-context models endow events with personal meaning and allow predictive control over behaviour and peripheral physiology, including autonomic, neuroendocrine and immune function. They guide learning from experience and the formation of narratives about the self and one's world. Disorders of mental and physical health, especially those with high co-occurrence and convergent alterations in the functionality of the ventromedial prefrontal cortex and the default-mode network, could benefit from interventions focused on understanding and shaping mindsets and beliefs about the self, illness and treatment.

Sexism-Related Stigma Affects Pain Perception

People with stigmatized characteristics tend to be devalued by others in a given society. The negative experiences related to stigma cause individuals to struggle as they would if they were in physical pain and bring various negative outcomes in the way that physical pain does. However, it is unclear whether stigma related to one's identity would affect their perception of physical pain. To address this issue, using sexism-related paradigms, we found that females had reduced pain threshold/tolerance in the Cold Pressor Test (Experiment 1) and an increased rating for nociceptive laser stimuli with fixed intensity (Experiment 2). Additionally, we observed that there was a larger laser-evoked N1, an early laser-evoked P2, and a larger magnitude of low-frequency component in laser-evoked potentials (LEPs) in the stigma condition than in the control condition (Experiment 3). Our study provides behavioral and electrophysiological evidence that sexism-related stigma affects the pain perception of females.

Effects of Patients' Expectation in Dermatology: Evidence from Experimental and Clinical Placebo Studies and Implications for Dermatologic Practice and Research

Patients' expectations towards the benefit of a treatment are key determinants of placebo responses and can affect the development and course of medical conditions and the efficacy and tolerability of active medical treatment. The mechanisms mediating these placebo and nocebo effects have been best described in the field of experimental pain and placebo analgesia. However, also in dermatology experimental and clinical studies demonstrate that various skin diseases such as inflammatory dermatoses and allergic reactions can be modulated by patients' expectations. Dermatologists should consider the important modulatory role of patients' expectations on the efficacy and tolerability of specific treatments and the key role of verbal information, patients' prior treatment experiences (associative learning), and the quality and quantity of doctor-patient communication in shaping treatment expectation. As a consequence, techniques aiming at maximizing patients' expectation effects should be implemented into daily clinical routine. By contrast, in clinical studies expectation effects should be maximally controlled and harmonized to improve the "assay sensitivity" to detect new compounds. Further translational studies, also in dermatoses that have not been investigated yet, are needed to better characterize the mechanisms underlying patients' expectation and to gain further insights into potential clinical implications of these effects in dermatologic conditions. Therefore, in this review, we provide a brief overview on the concept of expectation effects on treatment outcome in general, summarize what is already known about this topic for dermatologic diseases, and finally present the relevance of this topic in clinical dermatology.

Hierarchical models of pain: Inference, information-seeking, and adaptive control

Computational models of pain consider how the brain processes nociceptive information and allow mapping neural circuits and networks to cognition and behaviour. To date, they have generally have assumed two largely independent processes: perceptual inference, typically modelled as an approximate Bayesian process, and action control, typically modelled as a reinforcement learning process. However, inference and control are intertwined in complex ways, challenging the clarity of this distinction. Here, we consider how they may comprise a parallel hierarchical architecture that combines inference, information-seeking, and adaptive value-based control. This sheds light on the complex neural architecture of the pain system, and takes us closer to understanding from where pain 'arises' in the brain.

Empathic pain evoked by sensory and emotional-communicative cues share common and process-specific neural representations

Pain empathy can be evoked by multiple cues, particularly observation of acute pain inflictions or facial expressions of pain. Previous studies suggest that these cues commonly activate the insula and anterior cingulate, yet vicarious pain encompasses pain-specific responses as well as unspecific processes (e.g. arousal) and overlapping activations are not sufficient to determine process-specific shared neural representations. We employed multivariate pattern analyses to fMRI data acquired during observation of noxious stimulation of body limbs (NS) and painful facial expressions (FE) and found spatially and functionally similar cross-modality (NS versus FE) whole-brain vicarious pain-predictive patterns. Further analyses consistently identified shared neural representations in the bilateral mid-insula. The vicarious pain patterns were not sensitive to respond to non-painful high-arousal negative stimuli but predicted self-experienced thermal pain. Finally, a domain-general vicarious pain pattern predictive of self-experienced pain but not arousal was developed. Our findings demonstrate shared pain-associated neural representations of vicarious pain.

Neural Pattern Similarity Unveils the Integration of Social Information and Aversive Learning

Attributing intentions to others' actions is important for learning to avoid their potentially harmful consequences. Here, we used functional magnetic resonance imaging multivariate pattern analysis to investigate how the brain integrates information about others' intentions with the aversive outcome of their actions. In an interactive aversive learning task, participants (n = 33) were scanned while watching two alleged coparticipants (confederates)-one making choices intentionally and the other unintentionally-leading to aversive (a mild shock) or safe (no shock) outcomes to the participant. We assessed the trial-by-trial changes in participants' neural activation patterns related to observing the coparticipants and experiencing the outcome of their choices. Participants reported a higher number of shocks, more discomfort, and more anger to shocks given by the intentional player. Intentionality enhanced responses to aversive actions in the insula, anterior cingulate cortex, inferior frontal gyrus, dorsal medial prefrontal cortex, and the anterior superior temporal sulcus. Our findings indicate that neural pattern similarities index the integration of social and threat information across the cortex.