Brain mediators of predictive cue effects on perceived pain

Expectation of pain and relief: A dynamical model of the neural basis for pain-trauma co-morbidity

Posttraumatic Stress Disorder (PTSD) is highly co-morbid with chronic pain conditions. When present, PTSD significantly worsens chronic pain outcomes. Likewise, pain contributes to a more severe PTSD as evidenced by greater disability, more frequent use of harmful opioid analgesics and increased pain severity. The biomechanism behind this comorbidity is incompletely understood, however recent work strongly supports the widely-accepted role of expectation, in the entanglement of chronic pain and trauma symptoms. This work has shown that those with trauma have a maladaptive brain response while expecting stress and pain, whereas those with chronic pain may have a notable impairment in brain response while expecting pain relief. This dynamical expectation model of the interaction between neural systems underlying expectation of pain onset (traumatic stress) and pain offset (chronic pain) is biologically viable and may provide a biomechanistic insight into pain-trauma comorbidity. These predictive mechanisms work through interoceptive pathways in the brain critically the insula cortex. Here we highlight how the neural expectation-related mechanisms augment the existing models of pain and trauma to better understand the dynamics of pain and trauma comorbidity. These ideas will point to targeted complementary clinical approaches, based on mechanistically separable neural biophenotypes for the entanglement of chronic pain and trauma symptoms.

Could relationship-based learnt beliefs and expectations contribute to physiological vulnerability of chronic pain? Making a case to consider attachment in pain research

Pain is an interpersonal and inherently social experience. Pain perception and administration of medical treatment all occur in a particular environmental and social context. Early environmental influences, and early learning experiences and interactions, condition the body's response to different threats (like pain), ultimately shaping the underlying neurophysiology. These early interactions and experiences also determine what situations are perceived as threatening, as well as our belief in our own ability to self-manage, and our belief in others to offer support, during perceived threats. These beliefs intrinsically drive the combination of behaviours that emerge in response to perceived threats, including pain. Such behaviours can be categorised into attachment styles. In this interdisciplinary review, we synthesise and summarise evidence from the neurobiological, psychobiological, psychosocial and psychobehavioural fields, to describe how these beliefs are embedded in the brain's prediction models to generate a series of expectations/perceptions around the level of safety/threat in different contexts. As such, these beliefs may predict how one experiences, and responds to, pain; with potentially significant implications for the development and management of chronic pain. Little attention has been directed to the effect of adult attachment style on pain in research studies and in the clinical setting. Using interdisciplinary evidence, we argue why we think this interaction merits further consideration and research. PERSPECTIVE: This review explores the influence of attachment styles on pain perception, suggesting a link between social connections and chronic pain development. It aligns with recent calls to emphasise the social context in pain research and advocates for increased focus on adult attachment styles in research and clinical practice.

The psychophysiology of music-based interventions and the experience of pain

In modern times there is increasing acceptance that music-based interventions are useful aids in the clinical treatment of a range of neurological and psychiatric conditions, including helping to reduce the perception of pain. Indeed, the belief that music, whether listening or performing, can alter human pain experiences has a long history, dating back to the ancient Greeks, and its potential healing properties have long been appreciated by indigenous cultures around the world. The subjective experience of acute or chronic pain is complex, influenced by many intersecting physiological and psychological factors, and it is therefore to be expected that the impact of music therapy on the pain experience may vary from one situation to another, and from one person to another. Where pain persists and becomes chronic, aberrant central processing is a key feature associated with the ongoing pain experience. Nonetheless, beneficial effects of exposure to music on pain relief have been reported across a wide range of acute and chronic conditions, and it has been shown to be effective in neonates, children and adults. In this comprehensive review we examine the various neurochemical, physiological and psychological factors that underpin the impact of music on the pain experience, factors that potentially operate at many levels - the periphery, spinal cord, brainstem, limbic system and multiple areas of cerebral cortex. We discuss the extent to which these factors, individually or in combination, influence how music affects both the quality and intensity of pain, noting that there remains controversy about the respective roles that diverse central and peripheral processes play in this experience. Better understanding of the mechanisms that underlie music's impact on pain perception together with insights into central processing of pain should aid in developing more effective synergistic approaches when music therapy is combined with clinical treatments. The ubiquitous nature of music also facilitates application from the therapeutic environment into daily life, for ongoing individual and social benefit.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a region near the posterior inferior frontal sulcus of the right dorsolateral prefrontal cortex (piDLPFC) in migraine patients during acute pain and cognitive task performance. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this piDLPFC region, and diffusion weighted imaging verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Integration of Prior Expectations and Suppression of Prediction Errors During Expectancy-Induced Pain Modulation: The Influence of Anxiety and Pleasantness

Pain perception arises from the integration of prior expectations with sensory information. Although recent work has demonstrated that treatment expectancy effects (e.g., placebo hypoalgesia) can be explained by a Bayesian integration framework incorporating the precision level of expectations and sensory inputs, the key factor modulating this integration in stimulus expectancy-induced pain modulation remains unclear. In a stimulus expectancy paradigm combining emotion regulation in healthy male and female adults, we found that participants' voluntary reduction in anticipatory anxiety and pleasantness monotonically reduced the magnitude of pain modulation by negative and positive expectations, respectively, indicating a role of emotion. For both types of expectations, Bayesian model comparisons confirmed that an integration model using the respective emotion of expectations and sensory inputs explained stimulus expectancy effects on pain better than using their respective precision. For negative expectations, the role of anxiety is further supported by our fMRI findings that (1) functional coupling within anxiety-processing brain regions (amygdala and anterior cingulate) reflected the integration of expectations with sensory inputs and (2) anxiety appeared to impair the updating of expectations via suppressed prediction error signals in the anterior cingulate, thus perpetuating negative expectancy effects. Regarding positive expectations, their integration with sensory inputs relied on the functional coupling within brain structures processing positive emotion and inhibiting threat responding (medial orbitofrontal cortex and hippocampus). In summary, different from treatment expectancy, pain modulation by stimulus expectancy emanates from emotion-modulated integration of beliefs with sensory evidence and inadequate belief updating.

The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP.

Identification of group differences in predictive anticipatory biasing of pain during uncertainty: preparing for the worst but hoping for the best

ABSTRACT

Pain anticipation during conditions of uncertainty can unveil intrinsic biases, and understanding these biases can guide pain treatment interventions. This study used machine learning and functional magnetic resonance imaging to predict anticipatory responses in a pain anticipation experiment. One hundred forty-seven participants that included healthy controls (n = 57) and individuals with current and/or past mental health diagnosis (n = 90) received cues indicating upcoming pain stimuli: 2 cues predicted high and low temperatures, while a third cue introduced uncertainty. Accurate differentiation of neural patterns associated with specific anticipatory conditions was observed, involving activation in the anterior short gyrus of the insula and the nucleus accumbens. Three distinct response profiles emerged: subjects with a negative bias towards high pain anticipation, those with a positive bias towards low pain anticipation, and individuals whose predictions during uncertainty were unbiased. These profiles remained stable over one year, were consistent across diagnosed psychopathologies, and correlated with cognitive coping styles and underlying insula anatomy. The findings suggest that individualized and stable pain anticipation occurs in uncertain conditions.

Spatial summation of pain is associated with pain expectations: Results from a home-based paradigm

The purpose of this study was to reproduce the previously observed spatial summation of pain effect (SSp) using non-laboratory procedures and commercial equipment. An additional aim was to explore the association between expectations and SSp. The Cold Pressor Task (CPT) was used to induce SSp. Healthy participants (N = 68) immersed their non-dominant hands (divided into 5 segments) into cold water (CPT). Two conditions were used 1) gradual hand immersion (ascending condition) and 2) gradual hand withdrawal (descending condition). Pain intensity was measured on a Visual Analogue Scale (VAS). Psychological factors, such as the participants' expectations of pain intensity were also measured on a VAS. Results showed significant SSp (χ2(4) = 116.90, p < 0.001), reproduced with non-laboratory equipment in a home-based set-up. Furthermore, two novel findings were observed: i) there was a significant correlation between expectations and perceived pain, indicating a link between pain expectations and SSp, ii) spatial summation increased with the increase in duration exposure to the noxious stimulus (Wald χ2(8) = 80.80, p < 0.001). This study suggests that SSp is associated with pain expectations and can be formed by a mixture of excitatory and inhibitory mechanisms potentially driven by temporal characteristics of neural excitation. Moreover, this study proposes a new feasible way to induce SSp using a home-based set-up.

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review

Electroencephalographic (EEG) alterations have been demonstrated in acute, chronic, and experimentally induced musculoskeletal (MSK) pain conditions. However, there is no cumulative evidence on the associated EEG characteristics differentiating acute, chronic, and experimentally induced musculoskeletal pain states, especially compared to healthy controls. The present systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines (PRISMA) to review and summarize available evidence for cortical brain activity and connectivity alterations in acute, chronic, and experimentally induced MSK pain states. Five electronic databases were systematically searched from their inception to 2022. A total of 3471 articles were screened, and 26 full articles (five studies on chronic pain and 21 studies on experimentally induced pain) were included for the final synthesis. Using the Downs and Black risk of assessment tool, 92% of the studies were assessed as low to moderate quality. The review identified a 'very low' level of evidence for the changes in EEG and subjective outcome measures for both chronic and experimentally induced MSK pain based on the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Overall, the findings of this review indicate a trend toward decreased alpha and beta EEG power in evoked chronic clinical pain conditions and increased theta and alpha power in resting-state EEG recorded from chronic MSK pain conditions. EEG characteristics are unclear under experimentally induced pain conditions.

Reduced neural encoding of utility prediction errors in cocaine addiction

Influential accounts of addiction posit alterations in adaptive behavior driven by deficient dopaminergic prediction errors (PEs), signaling the discrepancy between actual and expected reward. Dopamine neurons encode these error signals in subjective terms, calibrated by individual risk preferences, as "utility" PEs. It remains unclear, however, whether people with drug addiction have PE deficits or their computational source. Here, using an analogous task to prior single-unit studies with known expectancies, we show that fMRI-measured PEs similarly reflect utility PEs. Relative to control participants, people with chronic cocaine addiction demonstrate reduced utility PEs in the dopaminoceptive ventral striatum, with similar trends in orbitofrontal cortex. Dissecting this PE signal into its subcomponent terms attributed these reductions to weaker striatal responses to received reward/utility, whereas suppression of activity with reward expectation was unchanged. These findings support that addiction may fundamentally disrupt PE signaling and reveal an underappreciated role for perceived reward value in this mechanism.

The analgesic effects and neural oscillatory mechanisms of virtual reality scenes based on distraction and mindfulness strategies in human volunteers

BACKGROUND

Virtual reality (VR) has been widely used as a non-pharmacological adjunct to pain management. However, there is no consensus on what type of VR content is the best for pain alleviation and by what means VR modulates pain perception. We used three experiments to explore the analgesic effect of VR scenes in healthy adult volunteers.

METHODS

We first compared the effect of immersive VR on pain perception with active (i.e. non-immersive, two-dimensional video) and passive (i.e. no VR or audiovisual input) controls at both subjective perceptual (Experiment 1) and electrophysiological (electroencephalography) levels (Experiment 2), and then explored possible analgesic mechanisms responsible for VR scenes conveying different strategies (e.g. exploration or mindfulness; Experiment 3).

RESULTS

The multisensory experience of the VR environment lowered pain intensity and unpleasantness induced by contact heat stimuli when compared with two control conditions (P=0.001 and P<0.001, respectively). The reduced pain intensity rating correlated with decreased P2 amplitude (r=0.433, P<0.001) and increased pre-stimulus spontaneous gamma oscillations (r=-0.339, P=0.004) by 32-channel electroencephalography. A VR exploration scene induced a strong sense of immersion that was associated with increased pre-stimulus gamma oscillations (r=0.529, P<0.001), whereas a VR mindfulness meditation scene had a minor effect on immersive feelings but induced strong pre-stimulus alpha oscillations (r=-0.550, P<0.001), which led to a comparable analgesic effect.

CONCLUSIONS

Distinct neural mechanisms are responsible for VR-induced analgesia, deepening our understanding of the analgesic benefits of VR and its neural electrophysiological correlates. These findings support further development of digital healthcare.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a lateral aspect of the right dorsolateral prefrontal cortex (latDLPFC) in migraine patients. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this latDLPFC region, and diffusion weighted imaging (DWI) verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

How Do Expectations Modulate Pain? A Motivational Perspective

Expectations can profoundly modulate pain experience, during which the periaqueductal gray (PAG) plays a pivotal role. In this article, we focus on motivationally evoked neural activations in cortical and brainstem regions both before and during stimulus administration, as has been demonstrated by experimental studies on pain-modulatory effects of expectations, in the hope of unraveling how the PAG is involved in descending and ascending nociceptive processes. This motivational perspective on expectancy effects on the perception of noxious stimuli sheds new light on psychological and neuronal substrates of pain and its modulation, thus having important research and clinical implications.

Augmented pain-evoked primary sensorimotor cortex activation in adolescent girls with juvenile fibromyalgia

ABSTRACT

Juvenile fibromyalgia (JFM) is a chronic widespread pain condition that primarily affects adolescent girls. Previous studies have found increased sensitivity to noxious pressure in adolescents with JFM. However, the underlying changes in brain systems remain unclear. The aim of this study was to characterize pain-evoked brain responses and identify brain mediators of pain hypersensitivity in adolescent girls with JFM. Thirty-three adolescent girls with JFM and 33 healthy adolescent girls underwent functional magnetic resonance imaging scans involving noxious pressure applied to the left thumbnail at an intensity of 2.5 or 4 kg/cm 2 and rated pain intensity and unpleasantness on a computerized Visual Analogue Scale. We conducted standard general linear model analyses and exploratory whole-brain mediation analyses. The JFM group reported significantly greater pain intensity and unpleasantness than the control group in response to noxious pressure stimuli at both intensities ( P < 0.05). The JFM group showed augmented right primary somatosensory cortex (S1) activation to 4 kg/cm 2 (Z > 3.1, cluster-corrected P < 0.05), and the peak S1 activation magnitudes significantly correlated with the scores on the Widespread Pain Index ( r = 0.35, P = 0.048) with higher activation associated with more widespread pain. We also found that greater primary sensorimotor cortex activation in response to 4 kg/cm 2 mediated the between-group differences in pain intensity ratings ( P < 0.001). In conclusion, we found heightened sensitivity to noxious pressure stimuli and augmented pain-evoked sensorimotor cortex responses in adolescent girls with JFM, which could reflect central sensitization or amplified nociceptive input.

The Placebo Effect in Psychosis: Why It Matters and How to Measure It

Psychosis is characterized by unusual percepts and beliefs in the form of hallucinations and delusions. Antipsychotic medication, the primary treatment for psychosis, is often ineffective and accompanied by severe side effects, but research has not identified an effective alternative in several decades. One reason that clinical trials fail is that patients with psychosis tend to show a significant therapeutic response to inert control treatments, known as the placebo effect, which makes it difficult to distinguish drug effects from placebo effects. Conversely, in clinical practice, a strong placebo effect may be useful because it could enhance the overall treatment response. Identifying factors that predict large placebo effects could improve the future outlook of psychosis treatment. Biomarkers of the placebo effect have already been suggested in pain and depression, but not in psychosis. Quantifying markers of the placebo effect would have the potential to predict placebo effects in psychosis clinical trials. Furthermore, the placebo effect and psychosis may represent a shared neurocognitive mechanism in which prior beliefs are weighted against new sensory information to make inferences about reality. Examining this overlap could reveal new insights into the mechanisms underlying psychosis and indicate novel treatment targets. We provide a narrative review of the importance of the placebo effect in psychosis and propose a novel method to assess it.

Human ventromedial prefrontal cortex lesions enhance the effect of expectations on pain perception

Pain is strongly modulated by expectations and beliefs. Across species, subregions of ventromedial prefrontal cortex (VMPFC) are implicated in a variety of functions germane to pain, predictions, and learning. Human fMRI studies show that VMPFC activity tracks expectations about pain and mediates expectancy effects on pain-related activity in other brain regions. Prior lesion studies suggest that VMPFC may instead play a more general role in generating affective responses to painful stimuli. To test whether VMPFC is required to generate affective responses to pain or is more specifically involved in expectancy-based pain modulation, we studied responses to heat stimuli in five adults with bilateral surgical lesions of VMPFC and twenty healthy adults without brain damage. All participants underwent a quantitative sensory testing procedure followed by a pain expectancy task in which cues predicting either low or high pain were followed by intermittent medium intensity heat stimuli. Compared to adults without brain damage, individuals with VMPFC lesions reported larger differences in expected pain based on predictive cues and failed to update expectations following the covert introduction of unexpected medium temperature stimuli. Consistent with observed expectancy differences, subjective pain unpleasantness ratings in the VMPFC lesion group were more strongly modulated by cue during thermal stimulation. We found no group differences in overall pain sensitivity, nor in relationships between pain and autonomic arousal, suggesting that VMPFC damage specifically enhances the effect of expectations on pain processing, likely driven by impaired integration of new sensory feedback to update expectations about pain. These results provide essential new data regarding the specific functional contribution of VMPFC to pain modulation.

A mesocorticolimbic signature of pleasure in the human brain

Pleasure is a fundamental driver of human behaviour, yet its neural basis remains largely unknown. Rodent studies highlight opioidergic neural circuits connecting the nucleus accumbens, ventral pallidum, insula and orbitofrontal cortex as critical for the initiation and regulation of pleasure, and human neuroimaging studies exhibit some translational parity. However, whether activation in these regions conveys a generalizable representation of pleasure regulated by opioidergic mechanisms remains unclear. Here we use pattern recognition techniques to develop a human functional magnetic resonance imaging signature of mesocorticolimbic activity unique to states of pleasure. In independent validation tests, this signature is sensitive to pleasant tastes and affect evoked by humour. The signature is spatially co-extensive with mu-opioid receptor gene expression, and its response is attenuated by the opioid antagonist naloxone. These findings provide evidence for a basis of pleasure in humans that is distributed across brain systems.

Network targets for therapeutic brain stimulation: towards personalized therapy for pain

Precision neuromodulation of central brain circuits is a promising emerging therapeutic modality for a variety of neuropsychiatric disorders. Reliably identifying in whom, where, and in what context to provide brain stimulation for optimal pain relief are fundamental challenges limiting the widespread implementation of central neuromodulation treatments for chronic pain. Current approaches to brain stimulation target empirically derived regions of interest to the disorder or targets with strong connections to these regions. However, complex, multidimensional experiences like chronic pain are more closely linked to patterns of coordinated activity across distributed large-scale functional networks. Recent advances in precision network neuroscience indicate that these networks are highly variable in their neuroanatomical organization across individuals. Here we review accumulating evidence that variable central representations of pain will likely pose a major barrier to implementation of population-derived analgesic brain stimulation targets. We propose network-level estimates as a more valid, robust, and reliable way to stratify personalized candidate regions. Finally, we review key background, methods, and implications for developing network topology-informed brain stimulation targets for chronic pain.

Associations of Empathy with Teacher-Student Interactions: A Potential Ternary Model

Empathy has garnered increasing recognition as a pivotal component of teacher-student interactions and a notable determinant of student achievement. Nevertheless, the exact impact of empathy on teacher-student interactions remains elusive, despite research endeavors into the neural mechanisms of teacher empathy. Our article examines the cognitive neural processes of teacher empathy during various forms of teacher-student interactions. To this end, we first present a concise review of theoretical considerations related to empathy and interactions, followed by an extensive discussion of teacher-student interactions and teacher empathy through both "single-brain" and "dual-brain" perspectives. Drawing on these discussions, we propose a potential model of empathy that integrates the affective contagion, cognitive evaluation, and behavior prediction aspects of teacher-student interactions. Finally, future research directions are discussed.

Learned Nocebo Effects on Cutaneous Sensations of Pain and Itch: A Systematic Review and Meta-analysis of Experimental Behavioral Studies on Healthy Humans

OBJECTIVE

In past decades, the field of nocebo research has focused on studying how sensory perception can be shaped by learning. Nocebo effects refer to aggravated sensory experiences or increased sensitivity to sensations such as pain and itch resulting from treatment-related negative experiences. Behavioral conditioning and verbal suggestions of a negative treatment outcome may aggravate pain and itch perception. Gaining a comprehensive view of the magnitude of nocebo effects and contributing factors will help steer nocebo research toward fruitful directions for understanding complex sensory phenomena.

METHODS

We conducted a systematic review and meta-analysis of a total of 37 distinct experimental nocebo studies on healthy participants (all published in English between 2008 and 2021), with four separate meta-analyses for nocebo effects on pain or itch. We conducted subgroup analyses and meta-regression on factors such as type and intensity of sensory stimuli, and length of conditioning paradigms.

RESULTS

This meta-analysis showed that, on average, effect sizes of nocebo effects were moderate to large (Hedges g between 0.26 and 0.71 for the four primary outcomes). The combination of conditioning and verbal suggestions yielded stronger nocebo responses on pain in particular. Subgroup analyses, including factors such as the type of sensory stimulation, did not explain the moderate heterogeneity in nocebo magnitudes between different studies. Risk of bias was generally low and was not related to nocebo magnitudes either.

CONCLUSIONS

We discuss these results in relation to the role of conditioning and aversive learning, and we recommend more consistency in designing and reporting nocebo experiments.

Differences in the Default Mode Network of Temporal Lobe Epilepsy Patients Detected by Hilbert-Huang Transform Based Dynamic Functional Connectivity

Resting-state functional connectivity, constructed via functional magnetic resonance imaging, has become an essential tool for exploring brain functions. Aside from the methods focusing on the static state, investigating dynamic functional connectivity can better uncover the fundamental properties of brain networks. Hilbert-Huang transform (HHT) is a novel time-frequency technique that can adapt to both non-linear and non-stationary signals, which may be an effective tool for investigating dynamic functional connectivity. To perform the present study, we investigated time-frequency dynamic functional connectivity among 11 brain regions of the default mode network by first projecting the coherence into the time and frequency domains, and subsequently by identifying clusters in the time-frequency domain using k-means clustering. Experiments on 14 temporal lobe epilepsy (TLE) patients and 21 age and sex-matched healthy controls were performed. The results show that functional connections in the brain regions of the hippocampal formation, parahippocampal gyrus, and retrosplenial cortex (Rsp) were reduced in the TLE group. However, the connections in the brain regions of the posterior inferior parietal lobule, ventral medial prefrontal cortex, and the core subsystem could hardly be detected in TLE patients. The findings not only demonstrate the feasibility of utilizing HHT in dynamic functional connectivity for epilepsy research, but also indicate that TLE may cause damage to memory functions, disorders of processing self-related tasks, and impairment of constructing a mental scene.

Hippocampal spatio-predictive cognitive maps adaptively guide reward generalization

The brain forms cognitive maps of relational knowledge-an organizing principle thought to underlie our ability to generalize and make inferences. However, how can a relevant map be selected in situations where a stimulus is embedded in multiple relational structures? Here, we find that both spatial and predictive cognitive maps influence generalization in a choice task, where spatial location determines reward magnitude. Mirroring behavior, the hippocampus not only builds a map of spatial relationships but also encodes the experienced transition structure. As the task progresses, participants' choices become more influenced by spatial relationships, reflected in a strengthening of the spatial map and a weakening of the predictive map. This change is driven by orbitofrontal cortex, which represents the degree to which an outcome is consistent with the spatial rather than the predictive map and updates hippocampal representations accordingly. Taken together, this demonstrates how hippocampal cognitive maps are used and updated flexibly for inference.

Doctor trustworthiness influences pain and its neural correlates in virtual medical interactions

Trust is an important component of the doctor-patient relationship and is associated with improved patient satisfaction and health outcomes. Previously, we reported that patient feelings of trust and similarity toward their clinician predicted reductions in evoked pain in response to painful heat stimulations. In the present study, we investigated the brain mechanisms underlying this effect. We used face stimuli previously developed using a data-driven computational modeling approach that differ in perceived trustworthiness and superimposed them on bodies dressed in doctors' attire. During functional magnetic resonance imaging, participants (n = 42) underwent a series of virtual medical interactions with these doctors during which they received painful heat stimulation as an analogue of a painful diagnostic procedure. Participants reported increased pain when receiving painful heat stimulations from low-trust doctors, which was accompanied by increased activity in pain-related brain regions and a multivariate pain-predictive neuromarker. Findings suggest that patient trust in their doctor may have tangible impacts on pain and point to a potential brain basis for trust-related reductions in pain through the modulation of brain circuitry associated with the sensory-discriminative and affective-motivational dimensions of pain.

Transcranial random noise stimulation over the left dorsolateral prefrontal cortex attenuates pain expectation and perception

OBJECTIVE

The dorsolateral prefrontal cortex (DLPFC) has been increasingly used as a neuromodulatory target in pain management. Transcranial random noise stimulation (tRNS) was shown to effectively elevate cortical excitability. Hence, this study aimed to characterize how tRNS over the left DLPFC affects pain expectation and perception, as well as the efficacy of conditioned-pain modulation (CPM) that reflects the function of the endogenous pain-inhibitory pathway.

METHODS

Using a randomized, double-blinded, and sham-controlled design, healthy participants were randomly recruited to receive tRNS with a direct current offset or sham stimulation. Their expectations and perceptions of painful electrocutaneous stimuli, as well as CPM efficacy were assessed before, immediately after, and 30 min after tRNS.

RESULTS

Compared with sham stimulation, perceived-pain ratings to the painful stimuli, and expected-pain ratings before painful stimuli, attenuated immediately after tRNS, whereas this analgesic effect was ineffective 30 min after tRNS. Importantly, the immediate analgesia induced by tRNS could be accounted for by tRNS effect on attenuating expected-pain ratings before certain painful stimuli. However, CPM efficacy was not significantly affected by tRNS.

CONCLUSIONS

These results demonstrate analgesia immediately after applying tRNS over the left DLPFC.

SIGNIFICANCE

This study provides evidence for analgesia of DLPFC-tRNS on an experimental pain model.

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.

Confidence of probabilistic predictions modulates the cortical response to pain

Pain typically evolves over time, and the brain needs to learn this temporal evolution to predict how pain is likely to change in the future and orient behavior. This process is termed temporal statistical learning (TSL). Recently, it has been shown that TSL for pain sequences can be achieved using optimal Bayesian inference, which is encoded in somatosensory processing regions. Here, we investigate whether the confidence of these probabilistic predictions modulates the EEG response to noxious stimuli, using a TSL task. Confidence measures the uncertainty about the probabilistic prediction, irrespective of its actual outcome. Bayesian models dictate that the confidence about probabilistic predictions should be integrated with incoming inputs and weight learning, such that it modulates the early components of the EEG responses to noxious stimuli, and this should be captured by a negative correlation: when confidence is higher, the early neural responses are smaller as the brain relies more on expectations/predictions and less on sensory inputs (and vice versa). We show that participants were able to predict the sequence transition probabilities using Bayesian inference, with some forgetting. Then, we find that the confidence of these probabilistic predictions was negatively associated with the amplitude of the N2 and P2 components of the vertex potential: the more confident were participants about their predictions, the smaller the vertex potential. These results confirm key predictions of a Bayesian learning model and clarify the functional significance of the early EEG responses to nociceptive stimuli, as being implicated in confidence-weighted statistical learning.

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.

Neurocomputational mechanisms of confidence in self and others

Computing confidence in one’s own and others’ decisions is critical for social success. While there has been substantial progress in our understanding of confidence estimates about oneself, little is known about how people form confidence estimates about others. Here, we address this question by asking participants undergoing fMRI to place bets on perceptual decisions made by themselves or one of three other players of varying ability. We show that participants compute confidence in another player’s decisions by combining distinct estimates of player ability and decision difficulty – allowing them to predict that a good player may get a difficult decision wrong and that a bad player may get an easy decision right. We find that this computation is associated with an interaction between brain systems implicated in decision-making (LIP) and theory of mind (TPJ and dmPFC). These results reveal an interplay between self- and other-related processes during a social confidence computation.

Computational and neural mechanisms of statistical pain learning

Pain invariably changes over time. These fluctuations contain statistical regularities which, in theory, could be learned by the brain to generate expectations and control responses. We demonstrate that humans learn to extract these regularities and explicitly predict the likelihood of forthcoming pain intensities in a manner consistent with optimal Bayesian inference with dynamic update of beliefs. Healthy participants received probabilistic, volatile sequences of low and high-intensity electrical stimuli to the hand during brain fMRI. The inferred frequency of pain correlated with activity in sensorimotor cortical regions and dorsal striatum, whereas the uncertainty of these inferences was encoded in the right superior parietal cortex. Unexpected changes in stimulus frequencies drove the update of internal models by engaging premotor, prefrontal and posterior parietal regions. This study extends our understanding of sensory processing of pain to include the generation of Bayesian internal models of the temporal statistics of pain.

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.

Test-Retest Reliability of an Adaptive Thermal Pain Calibration Procedure in Healthy Volunteers

Quantitative sensory testing (QST) allows researchers to evaluate associations between noxious stimuli and acute pain in clinical populations and healthy participants. Despite its widespread use, our understanding of QST’s reliability is limited, as reliability studies have used small samples and restricted time windows. We examined the reliability of pain ratings in response to noxious thermal stimulation in 171 healthy volunteers (n = 99 female, n = 72 male) who completed QST on multiple visits ranging from 1 day to 952 days between visits. On each visit, participants underwent an adaptive pain calibration in which they experienced 24 heat trials and rated pain intensity after stimulus offset on a 0 to 10 Visual Analog Scale. We used linear regression to determine pain threshold, pain tolerance, and the correlation between temperature and pain for each session and examined the reliability of these measures. Threshold and tolerance were moderately reliable (Intra-class correlation = .66 and .67, respectively; P < .001), whereas temperature-pain correlations had low reliability (Intra-class correlation = .23). In addition, pain tolerance was significantly more reliable in female participants than male participants, and we observed similar trends for other pain sensitive measures. Our findings indicate that threshold and tolerance are largely consistent across visits, whereas sensitivity to changes in temperature vary over time and may be influenced by contextual factors.

Processing of pain by the developing brain: evidence of differences between adolescent and adult females

ABSTRACT

Adolescence is a sensitive period for both brain development and the emergence of chronic pain particularly in females. However, the brain mechanisms supporting pain perception during adolescence remain unclear. This study compares perceptual and brain responses to pain in female adolescents and adults to characterize pain processing in the developing brain. Thirty adolescent (ages 13-17 years) and 30 adult (ages 35-55 years) females underwent a functional magnetic resonance imaging scan involving acute pain. Participants received 12 ten-second noxious pressure stimuli that were applied to the left thumbnail at 2.5 and 4 kg/cm 2 , and rated pain intensity and unpleasantness on a visual analogue scale. We found a significant group-by-stimulus intensity interaction on pain ratings. Compared with adults, adolescents reported greater pain intensity and unpleasantness in response to 2.5 kg/cm 2 but not 4 kg/cm 2 . Adolescents showed greater medial-lateral prefrontal cortex and supramarginal gyrus activation in response to 2.5 kg/cm 2 and greater medial prefrontal cortex and rostral anterior cingulate responses to 4 kg/cm 2 . Adolescents showed greater pain-evoked responses in the neurologic pain signature and greater activation in the default mode and ventral attention networks. Also, the amygdala and associated regions played a stronger role in predicting pain intensity in adolescents, and activity in default mode and ventral attention regions more strongly mediated the relationship between stimulus intensity and pain ratings. This study provides first evidence of greater low-pain sensitivity and pain-evoked brain responses in female adolescents (vs adult women) in regions important for nociceptive, affective, and cognitive processing, which may be associated with differences in peripheral nociception.

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.

Altered resting-state functional connectivity within corticostriatal and subcortical-striatal circuits in chronic pain

Brain corticostriatal circuits are important for understanding chronic pain and highly relevant to motivation and cognitive processes. It has been demonstrated that in patients with chronic back pain, altered nucleus accumbens (NAcc)-medial prefrontal cortex (MPFC) circuit fMRI-based activity is predictive of patient outcome. We evaluated the NAcc-MPFC circuit in patients with another chronic pain condition, fibromyalgia, to extend these important findings. First, we compared fMRI-based NAcc-MPFC resting-state functional connectivity in patients with fibromyalgia (N = 32) vs. healthy controls (N = 37). Compared to controls, the NAcc-MPFC circuit's connectivity was significantly reduced in fibromyalgia. In addition, within the fibromyalgia group, NAcc-MPFC connectivity was significantly correlated with trait anxiety. Our expanded connectivity analysis of the NAcc to subcortical brain regions showed reduced connectivity of the right NAcc with mesolimbic circuit regions (putamen, thalamus, and ventral pallidum) in fibromyalgia. Lastly, in an exploratory analysis comparing our fibromyalgia and healthy control cohorts to a separate publicly available dataset from patients with chronic back pain, we identified reduced NAcc-MPFC connectivity across both the patient groups with unique alterations in NAcc-mesolimbic connectivity. Together, expanding upon prior observed alterations in brain corticostriatal circuits, our results provide novel evidence of altered corticostriatal and mesolimbic circuits in chronic pain.

Individual variability in brain representations of pain

Characterizing cerebral contributions to individual variability in pain processing is crucial for personalized pain medicine, but has yet to be done. In the present study, we address this problem by identifying brain regions with high versus low interindividual variability in their relationship with pain. We trained idiographic pain-predictive models with 13 single-trial functional MRI datasets (n = 404, discovery set) and quantified voxel-level importance for individualized pain prediction. With 21 regions identified as important pain predictors, we examined the interindividual variability of local pain-predictive weights in these regions. Higher-order transmodal regions, such as ventromedial and ventrolateral prefrontal cortices, showed larger individual variability, whereas unimodal regions, such as somatomotor cortices, showed more stable pain representations across individuals. We replicated this result in an independent dataset (n = 124). Overall, our study identifies cerebral sources of individual differences in pain processing, providing potential targets for personalized assessment and treatment 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.

The human insula processes both modality-independent and pain-selective learning signals

Prediction errors (PEs) are generated when there are differences between an expected and an actual event or sensory input. The insula is a key brain region involved in pain processing, and studies have shown that the insula encodes the magnitude of an unexpected outcome (unsigned PEs). In addition to signaling this general magnitude information, PEs can give specific information on the direction of this deviation-i.e., whether an event is better or worse than expected. It is unclear whether the unsigned PE responses in the insula are selective for pain or reflective of a more general processing of aversive events irrespective of modality. It is also unknown whether the insula can process signed PEs at all. Understanding these specific mechanisms has implications for understanding how pain is processed in the brain in both health and in chronic pain conditions. In this study, 47 participants learned associations between 2 conditioned stimuli (CS) with 4 unconditioned stimuli (US; painful heat or loud sound, of one low and one high intensity each) while undergoing functional magnetic resonance imaging (fMRI) and skin conductance response (SCR) measurements. We demonstrate that activation in the anterior insula correlated with unsigned intensity PEs, irrespective of modality, indicating an unspecific aversive surprise signal. Conversely, signed intensity PE signals were modality specific, with signed PEs following pain but not sound located in the dorsal posterior insula, an area implicated in pain intensity processing. Previous studies have identified abnormal insula function and abnormal learning as potential causes of pain chronification. Our findings link these results and suggest that a misrepresentation of learning relevant PEs in the insular cortex may serve as an underlying factor in chronic pain.

Cortico-Brainstem Mechanisms of Biased Perceptual Decision-Making in the Context of Pain

Prior expectations can bias how we perceive pain. Using a drift diffusion model, we recently showed that this influence is primarily based on changes in perceptual decision-making (indexed as shift in starting point). Only during unexpected application of high-intensity noxious stimuli, altered information processing (indexed as increase in drift rate) explained the expectancy effect on pain processing. Here, we employed functional magnetic resonance imaging to investigate the neural basis of both these processes in healthy volunteers. On each trial, visual cues induced the expectation of high- or low-intensity noxious stimulation or signaled equal probability for both intensities. Participants categorized a subsequently applied electrical stimulus as either low- or high-intensity pain. A shift in starting point towards high pain correlated negatively with right dorsolateral prefrontal cortex activity during cue presentation underscoring its proposed role of "keeping pain out of mind". This anticipatory right dorsolateral prefrontal cortex signal increase was positively correlated with periaqueductal gray (PAG) activity when the expected high-intensity stimulation was applied. A drift rate increase during unexpected high-intensity pain was reflected in amygdala engagement and increased functional connectivity between amygdala and PAG. Our findings suggest involvement of the PAG in both decision-making bias and altered information processing to implement expectancy effects on pain. PERSPECTIVE: Modulation of pain through expectations has been linked to changes in perceptual decision-making and altered processing of afferent information. Our results suggest involvement of the dorsolateral prefrontal cortex, amygdala, and periaqueductal gray in these processes.

The Effect of Uncertainty on Pain Decisions for Self and Others

Background

Estimating others’ pain is a challenging inferential process, associated with a high degree of uncertainty. While much is known about uncertainty’s effect on self‐regarding actions, its impact on other‐regarding decisions for pain have yet to be characterized.

Aim

The present study exploited models of probabilistic decision‐making to investigate how uncertainty influences the valuation and assessment of another’s pain.

Materials & Methods

We engaged 63 dyads (43 strangers and 20 romantic couples) in a task where individual choices affected the pain delivered to either oneself (the agent) or the other member of the dyad. At each trial, agents were presented with cues predicting a given pain intensity with an associated probability of occurrence. Agents either chose a sure (mild decrease of pain) or risky (50% chance of avoiding pain altogether) management option, before bidding on their choice. A heat stimulation was then issued to the target (self or other). Decision‐makers were then asked to rate the pain administered to the target.

Results

We found that the higher the expected pain, the more risk‐averse agents became, in line with findings in value‐based decision‐making. Furthermore, agents gambled less on another individual’s pain (especially strangers) and placed higher bids on pain relief than they did for themselves. Most critically, the uncertainty associated with expected pain dampened ratings made for strangers’ pain. This contrasted with the effect on an agent’s own pain, for which risk had a marginal hyperalgesic effect.

Discussion & Conclusion

Overall, our results suggested that risk selectively affects decision‐making on a stranger’s suffering, both at the level of assessment and treatment selection, by (1) leading to underestimation, (2) privileging sure options and (3) altruistically allocating more money to insure the treatment’s success.

Significance

Uncertainty biases decision‐making but it is unclear if it affects choice behavior on pain for others. In examining this question, we found individuals were generally risk‐seeking when faced with looming pain, but more so for self; and assigned higher monetary values and subjective ratings on another’s pain. However, uncertainty dampened agents’ assessment of a stranger’s pain, suggesting latent variables may contradict overt altruism. This bias may underlie pain underestimation in clinical settings.

Prediction and action in cortical pain processing

Predicting that a stimulus is painful facilitates action to avoid harm. But how distinct are the neural processes underlying the prediction of upcoming painful events vis-à-vis those taking action to avoid them? Here, we investigated brain activity as a function of current and predicted painful or nonpainful thermal stimulation, as well as the ability of voluntary action to affect the duration of upcoming stimulation. Participants performed a task which involved the administration of a painful or nonpainful stimulus (S1), which predicted an immediately subsequent very painful or nonpainful stimulus (S2). Pressing a response button within a specified time window during S1 either reduced or did not reduce the duration of the upcoming stimulation. Predicted pain increased activation in several regions, including anterior cingulate cortex (ACC), midcingulate cortex (MCC), and insula; however, activation in ACC and MCC depended on whether a meaningful action was performed, with MCC activation showing a direct relationship with motor output. Insula's responses for predicted pain were also modulated by potential action consequences, albeit without a direct relationship with motor output. These findings suggest that cortical pain processing is not specifically tied to the sensory stimulus, but instead, depends on the consequences of that stimulus for sensorimotor control of behavior.

Altered Pain Processing Associated with Administration of Dopamine Agonist and Antagonist in Healthy Volunteers

Striatal dopamine dysfunction is associated with the altered top-down modulation of pain processing. The dopamine D2-like receptor family is a potential substrate for such effects due to its primary expression in the striatum, but evidence for this is currently lacking. Here, we investigated the effect of pharmacologically manipulating striatal dopamine D2 receptor activity on the anticipation and perception of acute pain stimuli in humans. Participants received visual cues that induced either certain or uncertain anticipation of two pain intensity levels delivered via a CO₂ laser. Rating of the pain intensity and unpleasantness was recorded. Brain activity was recorded with EEG and analysed via source localisation to investigate neural activity during the anticipation and receipt of pain. Participants completed the experiment under three conditions, control (Sodium Chloride), D2 receptor agonist (Cabergoline), and D2 receptor antagonist (Amisulpride), in a repeated-measures, triple-crossover, double-blind study. The antagonist reduced an individuals’ ability to distinguish between low and high pain following uncertain anticipation. The EEG source localisation showed that the agonist and antagonist reduced neural activations in specific brain regions associated with the sensory integration of salient stimuli during the anticipation and receipt of pain. During anticipation, the agonist reduced activity in the right mid-temporal region and the right angular gyrus, whilst the antagonist reduced activity within the right postcentral, right mid-temporal, and right inferior parietal regions. In comparison to control, the antagonist reduced activity within the insula during the receipt of pain, a key structure involved in the integration of the sensory and affective aspects of pain. Pain sensitivity and unpleasantness were not changed by D2R modulation. Our results support the notion that D2 receptor neurotransmission has a role in the top-down modulation of pain.

Late responses in the anterior insula reflect the cognitive component of pain: evidence of nonpain processing

Supplemental Digital Content is Available in the Text.

Distinguishing sensory and cognitive aspects of pain-related insular activity and the temporal profile of anterior insula activity suggested a key role of cognitive modulation.

Introduction:

Pain is a complex experience influenced by sensory and psychological factors. The insula is considered to be a core part of the pain network in the brain. Previous studies have suggested a relationship between the posterior insula (PI) and sensory processing, and between the anterior insula (AI) and cognitive–affective factors.

Objectives:

Our aim was to distinguish sensory and cognitive responses in pain-related insular activities.

Methods:

We recorded spatiotemporal insular activation patterns of healthy participants (n = 20) during pain or tactile processing with painful or nonpainful movie stimuli, using a magnetoencephalography. We compared the peak latency between PI and AI activities in each stimulus condition, and between pain and tactile processing in each response. The peak latency and amplitude between different movies were then examined to explore the effects of cognitive influence. A visual analogue scale was used to assess subjective perception.

Results:

The results revealed one clear PI activity and 2 AI activities (early and late) in insular responses induced by pain/tactile stimulation. The early response transmitted from the PI to AI was observed during sensory-associated brain activity, whereas the late AI response was observed during cognitive-associated activity. In addition, we found that painful movie stimuli had a significant influence on both late AI activity and subjective perception, caused by nonpainful actual stimulation.

Conclusions:

The current findings suggested that late AI activation reflects the processing of cognitive pain information, whereas the PI and early AI responses reflect sensory processing.

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

Supplemental Digital Content is Available in the Text.

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

Introduction:

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

Objectives:

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

Methods:

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

Results:

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

Conclusion:

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

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

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

Distinct networks of periaqueductal gray columns in pain and threat processing

Noxious events that can cause physical damage to the body are perceived as threats. In the brainstem, the periaqueductal gray (PAG) ensures survival by generating an appropriate response to these threats. Hence, the experience of pain is coupled with threat signaling and interfaces in the dl/l and vlPAG columns. In this study, we triangulate the functional circuits of the dl/l and vlPAG by using static and time-varying functional connectivity (FC) in multiple fMRI scans in healthy participants (n=37, 21 female). The dl/l and vlPAG were activated during cue, heat, and rating periods when the cue signaled a high threat of experiencing heat pain and the incoming intensity of heat pain was low; responses were significantly lower after low threat cues. The two regions responded similarly to the cued conditions but showed prominent distinctions in the extent of FC with other brain regions. Thus, both static and time-varying FC showed significant differences in the functional circuits of dl/l and vlPAG in rest and task scans. The dl/lPAG consistently synchronized with the salience network, suggesting a role in threat detection, while the vlPAG exhibited more widespread synchronization and frequently connected with memory/language and sensory regions. Hence, these two PAG regions process heat pain when stronger pain is expected or when it is uncertain, and preferentially synchronize with distinct brain circuits in a reproducible manner. The dl/lPAG seems more directly involved in salience detection, while the vlPAG seems engaged in contextualizing threats.

Individually unique dynamics of cortical connectivity reflect the ongoing intensity of chronic pain

ABSTRACT

Chronic pain diseases are characterised by an ongoing and fluctuating endogenous pain, yet it remains to be elucidated how this is reflected by the dynamics of ongoing functional cortical connections.Here, we investigated the cortical encoding of 20 chronic back pain patients and 20 chronic migraineurs in four repeated fMRI sessions. A brain parcellation approach subdivided the whole brain into 408 regions. Linear mixed effects models were fitted for each pair of brain regions to explore the relationship between the dynamic cortical connectivity and the observed trajectory of the patients' ratings of fluctuating endogenous pain.Overall, we found that periods of high and increasing pain were predominantly related to low cortical connectivity. The change of pain intensity in chronic back pain was subserved by connections in left parietal opercular regions, right insular regions, as well as large parts of the parietal, cingular and motor cortices. The change of pain intensity direction in chronic migraine was reflected by decreasing connectivity between the anterior insular cortex and orbitofrontal areas, as well as between the PCC and frontal and ACC regions.Interestingly, the group results were not mirrored by the individual patterns of pain-related connectivity, which is suggested to deny the idea of a common neuronal core problem for chronic pain diseases. The diversity of the individual cortical signatures of chronic pain encoding results adds to the understanding of chronic pain as a complex and multifaceted disease. The present findings support recent developments for more personalised medicine.

Intrinsic Network Activity Reflects the Fluctuating Experience of Tonic Pain

Although we know sensation is continuous, research on long-lasting and continuously changing stimuli is scarce and the dynamic nature of ongoing cortical processing is largely neglected. In a longitudinal study, 38 participants across four sessions were asked to continuously rate the intensity of an applied tonic heat pain for 20 min. Using group-independent component analysis and dual regression, we extracted the subjects' time courses of intrinsic network activity. The relationship between the dynamic fluctuation of network activity with the varying time courses of three pain processing entities was computed: pain intensity, the direction of pain intensity changes, and temperature. We were able to dissociate the spatio-temporal patterns of objective (temperature) and subjective (pain intensity/changes of pain intensity) aspects of pain processing in the human brain. We found two somatosensory networks with distinct functions: one network that encodes the small fluctuations in temperature and consists mainly of bilateral primary somatosensory cortex (SI), and a second right-lateralized network that encodes the intensity of the subjective experience of pain consisting of SI, secondary somatosensory cortex, the posterior cingulate cortex, and the thalamus. We revealed the somatosensory dynamics that build up toward a current subjective percept of pain. The timing suggests a cascade of subsequent processing steps toward the current pain percept.

Threat imminence reveals links among unfolding of anticipatory physiological response, cortical-subcortical intrinsic functional connectivity, and anxiety

Excessive expression of fear responses in anticipation of threat occurs in anxiety, but understanding of underlying pathophysiological mechanisms is limited. Animal research indicates that threat-anticipatory defensive responses are dynamically organized by threat imminence and rely on conserved circuitry. Insight from basic neuroscience research in animals on threat imminence could guide mechanistic research in humans mapping abnormal function in this circuitry to aberrant defensive responses in pathological anxiety. 50 pediatric anxiety patients and healthy-comparisons (33 females) completed an instructed threat-anticipation task whereby cues signaled delivery of painful (threat) or non-painful (safety) thermal stimulation. Temporal changes in skin-conductance indexed anxiety effects on anticipatory responding as function of threat imminence. Multivariate network analyses of resting-state functional connectivity data from a subsample were used to identify intrinsic-function correlates of anticipatory-response dynamics, within a specific, distributed network derived from translational research on defensive responding. By considering threat imminence, analyses revealed specific anxiety effects. Importantly, pathological anxiety was associated with excessive deployment of anticipatory physiological response as threat, but not safety, outcomes became more imminent. Magnitude of increase in threat-anticipatory physiological responses corresponded with magnitude of intrinsic connectivity within a cortical-subcortical circuit. Moreover, more severe anxiety was associated with stronger associations between anticipatory physiological responding and connectivity that ventromedial prefrontal cortex showed with hippocampus and basolateral amygdala, regions implicated in animal models of anxiety. These findings link basic and clinical research, highlighting variations in intrinsic function in conserved defensive circuitry as a potential pathophysiological mechanism in anxiety.

Inter-individual differences in pain anticipation and pain perception in migraine: Neural correlates of migraine frequency and cortisol-to-dehydroepiandrosterone sulfate (DHEA-S) ratio

Previous studies targeting inter-individual differences in pain processing in migraine mainly focused on the perception of pain. Our main aim was to disentangle pain anticipation and perception using a classical fear conditioning task, and investigate how migraine frequency and pre-scan cortisol-to-dehydroepiandrosterone sulfate (DHEA-S) ratio as an index of neurobiological stress response would relate to neural activation in these two phases. Functional Magnetic Resonance Imaging (fMRI) data of 23 participants (18 females; mean age: 27.61± 5.36) with episodic migraine without aura were analysed. We found that migraine frequency was significantly associated with pain anticipation in brain regions comprising the midcingulate and caudate, whereas pre-scan cortisol-to DHEA-S ratio was related to pain perception in the pre-supplementary motor area (pre-SMA). Both results suggest exaggerated preparatory responses to pain or more general to stressors, which may contribute to the allostatic load caused by stressors and migraine attacks on the brain.