Brain mediators of the effects of noxious heat on pain

Neural responses to stress and alcohol cues in individuals with pain with and without alcohol use disorder

Pain and alcohol use disorder (AUD) frequently co-occur, but the underlying neurobiology is not well-understood. Although many studies have reported disruptions in stress and reward cue-elicited neural reactivity and heightened alcohol craving in individuals with AUD, little is known about these constructs among patients who experience pain. Here, individuals with pain (Pain+, n = 31) and without pain (Pain-, n = 37) completed a well-validated functional magnetic resonance imaging (fMRI) paradigm involving stress (S), alcohol (A) and neutral (N) cue exposure with repeated alcohol craving assessments. Using whole-brain, voxel-based analyses (p < 0.001, whole-brain cluster correction at α < .05), the Pain+ versus Pain- group evidenced greater dorsal anterior cingulate cortex and left amygdala hyperactivation during N, but hypoactivation during the S-N contrast. Additionally, Pain+ exhibited blunted right anterior insular cortex (AIC) during S-N and blunted anteromedial thalamus and left AIC with hyperactive orbitofrontal cortex (OFC) during A-N. Exploratory analyses further revealed that individuals with pain and AUD (n = 17) relative to pain alone (n = 14) showed hyperactive bilateral AIC and hypoactive right dorsal caudate during A-N. Alcohol cue-induced craving, significantly higher in Pain+ (p = 0.03), correlated with blunted right AIC and OFC responses during A-N. In sum, these results provide first evidence of heightened alcohol cue-elicited craving and disrupted stress- and alcohol cue-reactivity within corticostriatal-limbic regions implicated in negative affect and preoccupation/anticipation stages of AUD in those with pain and with comorbid pain and AUD. Future investigations of pain-AUD interaction are needed that include systematic pain assessment and longitudinal designs with larger sample sizes.

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 neurofunctional signature of subjective disgust generalizes to oral distaste and socio-moral contexts

While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to socio-moral contexts. Here, in a series of studies, we combined functional magnetic resonance imaging with machine-learning-based predictive modelling to establish a comprehensive neurobiological model of subjective disgust. The developed neurofunctional signature accurately predicted momentary self-reported subjective disgust across discovery (n = 78) and pre-registered validation (n = 30) cohorts and generalized across core disgust (n = 34 and n = 26), gustatory distaste (n = 30) and socio-moral (unfair offers; n = 43) contexts. Disgust experience was encoded in distributed cortical and subcortical systems, and exhibited distinct and shared neural representations with subjective fear or negative affect in interoceptive-emotional awareness and conscious appraisal systems, while the signatures most accurately predicted the respective target experience. We provide an accurate functional magnetic resonance imaging signature for disgust with a high potential to resolve ongoing evolutionary debates.

A noradrenergic pathway for the induction of pain by sleep loss

An epidemic of sleep loss currently affects modern societies worldwide and is implicated in numerous physiological disorders, including pain sensitization, although few studies have explored the brain pathways affected by active sleep deprivation (ASD; e.g., due to recreation). Here, we describe a neural circuit responsible for pain sensitization in mice treated with 9-h non-stress ASD. Using a combination of advanced neuroscience methods, we found that ASD stimulates noradrenergic inputs from locus coeruleus (LCNA) to glutamatergic neurons of the hindlimb primary somatosensory cortex (S1HLGlu). Moreover, artificial inhibition of this LCNA→S1HLGlu pathway alleviates ASD-induced pain sensitization in mice, while chemogenetic activation of this pathway recapitulates the pain sensitization observed following ASD. Our study thus implicates activation of the LCNA→S1HLGlu pathway in ASD-induced pain sensitization, expanding our fundamental understanding of the multisystem interplay involved in pain processing.

Entangled brains and the experience of pains

The International Association for the Study of Pain (IASP) revised its definition of pain to "an unpleasant sensory and emotional experience." Three recent recommendations for understanding pain if there are no clear brain correlates include eliminativism, multiple realizability, and affordance-based approaches. I adumbrate a different path forward. Underlying each of the proposed approaches and the new IASP definition is the suspicion that there are no specific correlates for pain. I suggest that this basic assumption is misguided. As we learn more about brain function, it is becoming clear that many areas process many different types of information at the same time. In this study, I analogize how animal brains navigate in three-dimensional space with how the brain creates pain. Underlying both cases is a large-scale combinatorial system that feeds back on itself through a diversity of convergent and divergent bi-directional connections. Brains are not like combustion engines, with energy driving outputs via the structure of the machine, but are instead more like whirlpools, which are essentially dynamic patterns in some substrates. We should understand pain experiences as context-dependent, spatiotemporal trajectories that reflect heterogeneous, multiplex, and dynamically adaptive brain cells.

Threat impairs flexible use of a cognitive map

Goal-directed behavior requires adaptive systems that respond to environmental demands. In the absence of threat (or presence of reward), individuals can explore many behavioral trajectories, effectively interrogating the environment across multiple dimensions. This leads to flexible, relational memory encoding and retrieval. In the presence of danger, motivation shifts to an imperative state characterized by a narrow focus of attention on threatening information. This impairs flexible, relational memory. We test how these motivational shifts (Murty & Adcock, 2017) affect behavioral flexibility in an ecologically valid setting. Participants learned the structure of maze-like environments and navigated to the location of objects in both safe and threatening contexts. The latter contained a predator that could 'capture' participants, leading to electric shock. After learning, the path to some objects was unpredictably blocked. forcing a detour for which one route was significantly shorter. We predicted that threat would push participants toward an imperative state, leading to less efficient and less flexible navigation. Threat caused participants to take longer paths to goal objects and less efficient detours when obstacles were encountered. Threat-related impairments in detour navigation persisted after controlling for non-detour navigation performance. and non-detour navigation was not a reliable predictor of detour navigation, This suggests a specific impairment in flexible navigation during detours, an impairment unlikely to be explained by more general processes like predator avoidance or divided attention that may be present during non-detour navigation. These results provide ecologically valid evidence that dynamic, observable threats reduce flexible use of cognitive maps to guide behavior.

Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach

ABSTRACT

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

Chronic pain, chronic stress and substance use: overlapping mechanisms and implications

Chronic pain is among the most common reasons adults in the U.S. seek medical care. Despite chronic pain's substantial impact on individuals' physical, emotional, and financial wellness, the biologic underpinnings of chronic pain remain incompletely understood. Such deleterious impact on an individuals' wellness is also manifested in the substantial co-occurrence of chronic stress with chronic pain. However, whether chronic stress and adversity and related alcohol and substance misuse increases risk of developing chronic pain, and, if so, what the overlapping psychobiological processes are, is not well understood. Individuals suffering with chronic pain find alleviation through prescription opioids as well as non-prescribed cannabis, alcohol, and other drugs to control pain, and use of these substances have grown significantly. Substance misuse also increases experience of chronic stress. Thus, given the evidence showing a strong correlation between chronic stress and chronic pain, we aim to review and identify overlapping factors and processes. We first explore the predisposing factors and psychologic features common to both conditions. This is followed by examining the overlapping neural circuitry of pain and stress in order to trace a common pathophysiologic processes for the development of chronic pain and its link to substance use. Based on the previous literature and our own findings, we propose a critical role for ventromedial prefrontal cortex dysfunction, an overlapping brain area associated with the regulation of both pain and stress that is also affected by substance use, as key in the risk of developing chronic pain. Finally, we identify the need for future research in exploring the role of medial prefrontal circuits in chronic pain pathology. Critically, in order to alleviate the enormous burden of chronic pain without exacerbating the co-occurring substance misuse crisis, we emphasize the need to find better approaches to treat and prevent chronic pain.

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.

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.

Adaptive neuroplasticity in the default mode network contributing to absence of central sensitization in primary dysmenorrhea

Introduction

Primary dysmenorrhea (PDM), the most prevalent gynecological problem among women of reproductive age, presents as a regular pattern of cyclic menstrual pain. The presence or absence of central sensitization (i.e., pain hypersensitivity) in cases of PDM is a contentious issue. Among Caucasians, the presence of dysmenorrhea is associated with pain hypersensitivity throughout the menstrual cycle, indicating pain amplification mediated by the central nervous system. We previously reported on the absence of central sensitization to thermal pain among Asian PDM females. In this study, functional magnetic resonance imaging was used to reveal mechanisms underlying pain processing with the aim of explaining the absence of central sensitization in this population.

Methods

Brain responses to noxious heat applied to the left inner forearm of 31 Asian PDM females and 32 controls during their menstrual and periovulatory phases were analyzed.

Results and discussion

Among PDM females experiencing acute menstrual pain, we observed a blunted evoked response and de-coupling of the default mode network from the noxious heat stimulus. The fact that a similar response was not observed in the non-painful periovulatory phase indicates an adaptive mechanism aimed at reducing the impact of menstrual pain on the brain with an inhibitory effect on central sensitization. Here we propose that adaptive pain responses in the default mode network may contribute to the absence of central sensitization among Asian PDM females. Variations in clinical manifestations among different PDM populations can be attributed to differences in central pain processing.

Effects of intranasal oxytocin on pain perception among human subjects: A systematic literature review and meta-analysis

INTRODUCTION

Oxytocin (OXT) is a peptide hormone produced in the hypothalamus that plays a neuromodulatory role in emotion, stress, and anxiety. Due to its multidimensional role, OXT is a promising target for therapeutic interventions to treat pain.

OBJECTIVE

Perform a systematic literature review, followed by a meta-analysis to identify the effects of intranasal OXT on the self-perception of clinical and experimental pain among human subjects.

METHOD

A systematic review was conducted in the PubMed, PsycINFO, Scielo, Lilacs, and Web of Science databases, using the keywords Oxytocin, Pain, Analgesia, and Nociception.

RESULTS

Fifteen papers were included in the meta-analysis. None of the outcomes presented statistical significance in terms of the interventions' effect size: pain intensity (SMD = -0.02 (CI 95 %: -0.14 to 0.10; p = 0.76)) and pain unpleasantness (SMD = -0.15 (CI 95 %: -0.34 to 0.04; p = 0.12)). No meta-analysis was performed for pain threshold or tolerance because few papers address these outcomes.

CONCLUSION

There was no statistically significant effect of intranasal OXT administration on pain perception, considering equivalence limits between (-0.2 and 0.2). However, it must be considered that the study designs may not have been sensitive enough to detect minor analgesic effects of OXT, which, being weak, may also not be perceived at a conscious level. Additionally, OXT effects possibly depend on specific characteristics of the painful condition, such as pain complexity, intensity, and duration, contextual variables like the presence of social and affective support, and individual characteristics.

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.

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.

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.

Dissociation between individual differences in self-reported pain intensity and underlying fMRI brain activation

Pain is an individual experience. Previous studies have highlighted changes in brain activation and morphology associated with within- and interindividual pain perception. In this study we sought to characterize brain mechanisms associated with between-individual differences in pain in a sample of healthy adolescent and adult participants (N = 101). Here we show that pain ratings varied widely across individuals and that individuals reported changes in pain evoked by small differences in stimulus intensity in a manner congruent with their pain sensitivity, further supporting the utility of subjective reporting as a measure of the true individual experience. Furthermore, brain activation related to interindividual differences in pain was not detected, despite clear sensitivity of the Blood Oxygenation Level-Dependent (BOLD) signal to small differences in noxious stimulus intensities within individuals. These findings suggest fMRI may not be a useful objective measure to infer reported pain intensity.

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.

Sex Differences of Periaqueductal Grey Matter Functional Connectivity in Migraine

The existence of “sex phenotype” in migraine is a long-standing scientific question. Fluctuations of female sex hormones contribute to migraine attacks, and women also have enhanced brain activity during emotional processing and their functional brain networks seem to be more vulnerable to migraine-induced disruption compared to men. Periaqueductal grey matter (PAG) is a core region of pain processing and modulation networks with possible sex-related implications in migraine. In our study, sex differences of PAG functional resting-state connectivity were investigated in the interictal state in 32 episodic migraines without aura patients (16 women and 16 men). A significant main effect of sex was detected in PAG connectivity with postcentral, precentral, and inferior parietal gyri, and further differences were found between right PAG and visual areas (superior occipital gyrus, calcarine, and cuneus), supplementary motor area, and mid-cingulum connectivity. In all cases, PAG functional connectivity was stronger in female migraineurs compared to males. However, higher average pain intensity of migraine attacks correlated with stronger connectivity of PAG and middle temporal, superior occipital, and parietal gyri in male migraineurs compared to females. Migraine-related disability is also associated with PAG connectivity but without sex differences. Our results indicate that sex differences in PAG connectivity with brain regions involved in sensory and emotional aspects of pain might contribute to the “sex-phenotype” in migraine. The stronger functional connectivity between PAG and pain processing areas may be a sign of increased excitability of pain pathways even in resting-state in females compared to male migraineurs, which could contribute to female vulnerability for migraine. However, pain intensity experienced by male migraineurs correlated with increased connectivity between PAG and regions involved in the subjective experience of pain and pain-related unpleasantness. The demonstrated sex differences of PAG functional connectivity may support the notion that the female and male brain is differently affected by migraine.

Neural processes responsible for the translation of sustained nociceptive inputs into subjective pain experience

Tracking and predicting the temporal structure of nociceptive inputs is crucial to promote survival, as proper and immediate reactions are necessary to avoid actual or potential bodily injury. Neural activities elicited by nociceptive stimuli with different temporal structures have been described, but the neural processes responsible for translating nociception into pain perception are not fully elucidated. To tap into this issue, we recorded electroencephalographic signals from 48 healthy participants receiving thermo-nociceptive stimuli with 3 different durations and 2 different intensities. We observed that pain perception and several brain responses are modulated by stimulus duration and intensity. Crucially, we identified 2 sustained brain responses that were related to the emergence of painful percepts: a low-frequency component (LFC, < 1 Hz) originated from the insula and anterior cingulate cortex, and an alpha-band event-related desynchronization (α-ERD, 8-13 Hz) generated from the sensorimotor cortex. These 2 sustained brain responses were highly coupled, with the α-oscillation amplitude that fluctuated with the LFC phase. Furthermore, the translation of stimulus duration into pain perception was serially mediated by α-ERD and LFC. The present study reveals how brain responses elicited by nociceptive stimulation reflect the complex processes occurring during the translation of nociceptive information into pain perception.

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.

Altered Functional Connectivity and Sensory Processing in Blepharospasm and Hemifacial Spasm: Coexistence and Difference

Background: Blepharospasm (BSP) and hemifacial spasm (HFS) are both facial hyperkinesia however BSP is thought to be caused by maladaptation in multiple brain regions in contrast to the peripherally induced cause in HFS. Plausible coexisting pathophysiologies between these two distinct diseases have been proposed.

Objectives: In this study, we compared brain resting state functional connectivity (rsFC) and quantitative thermal test (QTT) results between patients with BSP, HFS and heathy controls (HCs).

Methods: This study enrolled 12 patients with BSP, 11 patients with HFS, and 15 HCs. All subjects received serial neuropsychiatric evaluations, questionnaires determining disease severity and functional impairment, QTT, and resting state functional MRI. Image data were acquired using seed-based analyses using the CONN toolbox.

Results: A higher cold detection threshold was found in the BSP and HFS patients compared to the HCs. The BSP and HFS patients had higher rsFC between the anterior cerebellum network and left occipital regions compared to the HCs. In all subjects, impaired cold detection threshold in the QTT of lower extremities had a correlation with higher rsFC between the anterior cerebellar network and left lingual gyrus. Compared to the HCs, increased rsFC in right postcentral gyrus in the BSP patients and decreased rsFC in the right amygdala and frontal orbital cortex in the HFS subjects were revealed when the anterior cerebellar network was used as seed.

Conclusions: Dysfunction of sensory processing detected by the QTT is found in the BSP and HSP patients. Altered functional connectivity between the anterior cerebellar network and left occipital region, especially the Brodmann area 19, may indicate the possibility of shared pathophysiology among BSP, HFS, and impaired cold detection threshold. Further large-scale longitudinal study is needed for testing this theory in the future.

Multiple Functional Brain Networks Related to Pain Perception Revealed by fMRI

The rise of functional magnetic resonance imaging (fMRI) has led to a deeper understanding of cortical processing of pain. Central to these advances has been the identification and analysis of "functional networks", often derived from groups of pre-selected pain regions. In this study our main objective was to identify functional brain networks related to pain perception by examining whole-brain activation, avoiding the need for a priori selection of regions. We applied a data-driven technique-Constrained Principal Component Analysis for fMRI (fMRI-CPCA)-that identifies networks without assuming their anatomical or temporal properties. Open-source fMRI data collected during a thermal pain task (33 healthy participants) were subjected to fMRI-CPCA for network extraction, and networks were associated with pain perception by modelling subjective pain ratings as a function of network activation intensities. Three functional networks emerged: a sensorimotor response network, a salience-mediated attention network, and the default-mode network. Together, these networks constituted a brain state that explained variability in pain perception, both within and between individuals, demonstrating the potential of data-driven, whole-brain functional network techniques for the analysis of pain imaging data.

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.

Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution

Predictive processing approaches to brain function are increasingly delivering promise for illuminating the computational underpinnings of a wide range of phenomenological states. It remains unclear, however, whether predictive processing is equipped to accommodate a theory of consciousness itself. Furthermore, objectors have argued that without specification of the core computational mechanisms of consciousness, predictive processing is unable to inform the attribution of consciousness to other non-human (biological and artificial) systems. In this paper, I argue that an account of consciousness in the predictive brain is within reach via recent accounts of phenomenal self-modelling in the active inference framework. The central claim here is that phenomenal consciousness is underpinned by 'subjective valuation'-a deep inference about the precision or 'predictability' of the self-evidencing ('fitness-promoting') outcomes of action. Based on this account, I argue that this approach can critically inform the distribution of experience in other systems, paying particular attention to the complex sensory attenuation mechanisms associated with deep self-models. I then consider an objection to the account: several recent papers argue that theories of consciousness that invoke self-consciousness as constitutive or necessary for consciousness are undermined by states (or traits) of 'selflessness'; in particular the 'totally selfless' states of ego-dissolution occasioned by psychedelic drugs. Drawing on existing work that accounts for psychedelic-induced ego-dissolution in the active inference framework, I argue that these states do not threaten to undermine an active inference theory of consciousness. Instead, these accounts corroborate the view that subjective valuation is the constitutive facet of experience, and they highlight the potential of psychedelic research to inform consciousness science, computational psychiatry and computational phenomenology.

Pathway Lasso: Pathway Estimation and Selection with High-Dimensional Mediators

In many scientific studies, it becomes increasingly important to delineate the pathways through a large number of mediators, such as genetic and brain mediators. Structural equation modeling (SEM) is a popular technique to estimate the pathway effects, commonly expressed as the product of coefficients. However, it becomes unstable and computationally challenging to fit such models with high-dimensional mediators. This paper proposes a sparse mediation model using a regularized SEM approach, where sparsity means that a small number of mediators have a nonzero mediation effect between a treatment and an outcome. To address the model selection challenge, we innovate by introducing a new penalty called Pathway Lasso. This penalty function is a convex relaxation of the non-convex product function for the mediation effects, and it enables a computationally tractable optimization criterion to estimate and select pathway effects simultaneously. We develop a fast ADMM-type algorithm to compute the model parameters, and we show that the iterative updates can be expressed in closed form. We also prove the asymptotic consistency of our Pathway Lasso estimator for the mediation effect. On both simulated data and an fMRI data set, the proposed approach yields higher pathway selection accuracy and lower estimation bias than competing methods.

Effect of odor pleasantness on heat-induced pain: An fMRI study

Odor modulates the experience of pain, but the neural basis of how the two sensory modalities, olfaction and pain, are linked in the central nervous system is far from clear. In this study, we investigated the mechanisms by which the brain modulates the pain experience under concurrent odorant stimulation. We conducted an fMRI study using a 2 × 3 factorial design, in which one of two temperatures (warm, hot) and one of three types of odors (pleasant, unpleasant, no odor) were presented simultaneously. "Hot" temperatures were individually determined as those perceived as painful (mean temperature = 46.9 °C). The non-painful "warm" temperature was set to 40 °C. Participants rated hot compared to warm stimuli as more intense and unpleasant, especially in the presence of an unpleasant odor. Parametric modeling on the intensity ratings activated the pain network, covering brain regions activated by the hot stimuli. The presence of an odor, irrespective of its valence, activated the amygdalae. In addition, the amygdalae showed stimulus-dependent functional couplings with the right supramarginal gyrus and with the left superior frontal gyrus. The coupling between the right amygdala and the left superior frontal gyrus was related to the intensity and unpleasantness ratings of the pain experience. Our results suggest that these functional connections may reflect the integrating process of the two sensory modalities, enabling olfactory influence on the pain experience.

The Automatization of a New Thermography Method Using Invasive Nociceptive Stimulation to Confirm an Autonomic Phenomenon within a Trigger Point Referred Pain Zone

The trigger points (TrPs) related to chronic low back pain that mimic sciatica have been lately recognized and included in the International Classification of Diseases, 11th Revision. This study examined the MATLAB software utility for the objective stratification of low back pain patients using the Minimally Invasive Procedure (MIP). The two diagnostic MIP parameters were: average temperature (ΔTavr) and autonomic referred pain (AURP). Chronic sciatica patients with TrPs (n = 20) and without TrPs (n = 20) were examined using the MIP. A significant increase in both parameters was confirmed for the thigh ROI of the TrP-positive patients, with ΔTavr being the leading parameter (p = 0.016, Exp(β) = 2.603). A continued significance of both parameters was confirmed from 6′00″ to 15′30″ (p < 0.05). The maximum AURP value was confirmed at 13′30″ (p < 0.05) (TrPs(+) 20.4 ± 19.9% vs. TrPs(-) 3.77 ± 9.14%; p = 0.000; CI (0.347,0.348)).

How Self-Appraisal Is Mediated by the Brain

Self-appraisal is a process that leads to the formation of self-esteem, which contributes to subjective well-being and mental health. Neuroimaging studies link self-esteem with the activity of the medial prefrontal cortex (MPFC), right temporoparietal junction (rTPJ), posterior cingulate cortex (PCC), anterior insula (AIns), and dorsolateral prefrontal cortex. It is not known, however, how the process of self-appraisal itself is mediated by the brain and how different nodes of the self-appraisal network interact with each other. In this study, we used multilevel mediation analysis of functional MRI data recorded during the trait adjective judgment task, treating the emotional valence of adjectives as the predictor, behavioral response as the dependent variable, and brain activity as the mediator. The mediation effect was revealed in the rTPJ. Dynamic causal modeling showed that positive self-descriptions trigger communication within the network, with the rTPJ exerting the strongest excitatory output and MPFC receiving the strongest excitatory input. rAIns receives the strongest inhibitory input and sends exclusively inhibitory connections to other regions pointing out to its role in the processing of negative self-descriptions. Analysis of individual differences showed that in some individuals, self-appraisal is mostly driven by the endorsement of positive self-descriptions and is accompanied by increased activation and communication between rTPJ, MPFC, and PCC. In others, self-appraisal is driven by the rejection of negative self-descriptions and is accompanied by increased activation of rAIns and inhibition of PCC and MPFC. Membership of these groups was predicted by different personality variables. This evidence uncovers different mechanisms of positive self-bias, which may contribute to different facets of self-esteem and are associated with different personality profiles.

Mathematical and computational models for pain: a systematic review

OBJECTIVE

There is no single prevailing theory of pain that explains its origin, qualities, and alleviation. Although many studies have investigated various molecular targets for pain management, few have attempted to examine the etiology or working mechanisms of pain through mathematical or computational model development. In this systematic review, we identified and classified mathematical and computational models for characterizing pain.

METHODS

The databases queried were Science Direct and PubMed, yielding 560 articles published prior to January 1st, 2020. After screening for inclusion of mathematical or computational models of pain, 31 articles were deemed relevant.

RESULTS

Most of the reviewed articles utilized classification algorithms to categorize pain and no-pain conditions. We found the literature heavily focused on the application of existing models or machine learning algorithms to identify the presence or absence of pain, rather than to explore features of pain that may be used for diagnostics and treatment.

CONCLUSIONS

Although understudied, the development of mathematical models may augment the current understanding of pain by providing directions for testable hypotheses of its underlying mechanisms. Additional focus is needed on developing models that seek to understand the underlying mechanisms of pain, as this could potentially lead to major breakthroughs in its treatment.

White matter microstructure varies with post-traumatic stress severity following medical trauma

The prefrontal cortex, amygdala, hippocampus, and hypothalamus are important components of the neural network that mediates the healthy learning, expression, and regulation of emotion. These brain regions are connected by white matter pathways that include the cingulum bundle, uncinate fasciculus, and fornix/stria terminalis. Individuals with trauma and stress-related disorders show dysfunction of the cognitive-affective processes supported by the brain regions these white matter tracts connect. Therefore, variability in the microstructure of these white matter pathways may play an important role in the cognitive-affective dysfunction related to post-traumatic stress disorder. Thus, the current study used diffusion weighted imaging to assess the white matter microstructure of the cingulum bundle, uncinate fasciculus, and fornix/stria terminalis acutely (< 1 month) following trauma. Further, we assessed both acute (i.e., < 1 month) and subacute (i.e., 3 months post-trauma) post-traumatic stress symptom severity. White matter microstructure (assessed < 1 month post-trauma) of the uncinate fasciculus and fornix/stria terminalis varied with acute post-traumatic stress severity (assessed < 1 month post-trauma). Further, white matter microstructure (assessed < 1 month post-trauma) of the cingulum bundle and fornix/stria terminalis varied with subacute post-traumatic stress severity (assessed 3 months post-trauma). The current results suggest white matter architecture of the prefrontal cortex - amygdala network plays an important role in the development of trauma and stress-related disorders.

Modeling neural and self-reported factors of affective distress in the relationship between pain and working memory in healthy individuals

The relationship between pain and cognition has primarily been investigated in patients with chronic pain and healthy participants undergoing experimental pain. Recently, there has been interest in understanding the disruptive effects of non-experimental pain in otherwise healthy individuals. Recent studies suggest that healthy individuals reporting pain also demonstrate decrements in working memory (WM) performance, however factors contributing to this relationship remain poorly understood. The present study examined the association between pain and WM in a large community-based sample of healthy individuals and investigated whether self-reported affective distress and medial frontal cortex activity might help to explain this relationship. To address these research questions, a large publicly available dataset from the Human Connectome Project (N = 416) was sourced and structural equation modeling was utilized to examine relationships between pain intensity experienced over the past 7 days, self-reported affective distress, performance on a WM (n-back) task, and task-related activation in the medial frontal cortex. Examining participants who reported non-zero pain intensity in the past 7 days (n = 228), we found a direct negative association between pain intensity and performance on the WM n-back task, consistent with prior findings. Self-reported affective distress was not associated with WM performance. Additionally, pain intensity was indirectly associated with WM performance via WM task-related activity in the ventromedial prefrontal cortex (vmPFC). Our findings suggest that pain experienced in everyday life by otherwise healthy individuals may directly impact WM performance. Furthermore, WM task-related increases in vmPFC activity may be a factor contributing to this relationship.

Neural Mechanisms of Acceptance and Commitment Therapy for Chronic Pain: A Network-Based fMRI Approach

Over 100 million Americans suffer from chronic pain (CP), which causes more disability than any other medical condition in the United States at a cost of $560-$635 billion per year (Institute of Medicine, 2011). Opioid analgesics are frequently used to treat CP. However, long term use of opioids can cause brain changes such as opioid-induced hyperalgesia that, over time, increase pain sensation. Also, opioids fail to treat complex psychological factors that worsen pain-related disability, including beliefs about and emotional responses to pain. Cognitive behavioral therapy (CBT) can be efficacious for CP. However, CBT generally does not focus on important factors needed for long-term functional improvement, including attainment of personal goals and the psychological flexibility to choose responses to pain. Acceptance and Commitment Therapy (ACT) has been recognized as an effective, non-pharmacologic treatment for a variety of CP conditions (Gutierrez et al., 2004). However, little is known about the neurologic mechanisms underlying ACT. We conducted an ACT intervention in women (n = 9) with chronic musculoskeletal pain. Functional magnetic resonance imaging (fMRI) data were collected pre- and post-ACT, and changes in functional connectivity (FC) were measured using Network-Based Statistics (NBS). Behavioral outcomes were measured using validated assessments such as the Acceptance and Action Questionnaire (AAQ-II), the Chronic Pain Acceptance Questionnaire (CPAQ), the Center for Epidemiologic Studies Depression Scale (CES-D), and the NIH Toolbox Neuro-QoLTM (Quality of Life in Neurological Disorders) scales. Results suggest that, following the 4-week ACT intervention, participants exhibited reductions in brain activation within and between key networks including self-reflection (default mode, DMN), emotion (salience, SN), and cognitive control (frontal parietal, FPN). These changes in connectivity strength were correlated with changes in behavioral outcomes including decreased depression and pain interference, and increased participation in social roles. This study is one of the first to demonstrate that improved function across the DMN, SN, and FPN may drive the positive outcomes associated with ACT. This study contributes to the emerging evidence supporting the use of neurophysiological indices to characterize treatment effects of alternative and complementary mind-body therapies.

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

OBJECTIVE

Dispositional mindfulness is associated with reduced pain in clinical and experimental settings. However, researchers have neglected the type of pain assessment, as dispositional mindfulness may have unique benefits for reduced pain sensitivity when relying on summary pain assessments, in contrast to assessing the pain of each noxious stimulus. Here, we test the association between dispositional mindfulness and pain using both trial-by-trial pain assessments and overall summary ratings after acute pain tasks.

METHODS

One hundred thirty-one healthy adult volunteers (mean age = 29.09 [8.00] years, 55.7% female) underwent two experimental thermal pain paradigms. We tested whether dispositional mindfulness measured with the Mindful Attention Awareness Scale was related to a) heat-evoked pain sensitivity, as measured by pain threshold, pain tolerance, average pain, trial-by-trial ratings, and heat-evoked skin conductance response, and b) summary judgments of sensory and affective pain assessed using the McGill Pain Questionnaire (MPQ).

RESULTS

Mindful Attention Awareness Scale ratings were associated with decreased pain on the MPQ sensory (B = -0.18, SE = 0.05, 95% confidence interval = -0.29 to -0.07, t = -3.28, p = .001) and affective (B = -0.11, SE = 0.03, 95% confidence interval = -0.18 to -0.05, t = -3.32, p = .001) dimensions but not with experimental thermal pain assessments, including threshold, tolerance, heat-evoked pain, or skin conductance response (p values ≥ .29).

CONCLUSIONS

In this study, dispositional mindfulness mitigated acute thermal pain only when pain was assessed using the MPQ. These findings may reflect differences in immediate versus retrospective judgments or the type of pain assessed by each measure. Future research should examine regulation processes that may explain these differential analgesic benefits, such as attention, rumination, or reappraisal.

Activation of the cognitive control network associated with information uncertainty

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.

Confidence in subjective pain is predicted by reaction time during decision making

Self-report is the gold standard for measuring pain. However, decisions about pain can vary substantially within and between individuals. We measured whether self-reported pain is accompanied by metacognition and variations in confidence, similar to perceptual decision-making in other modalities. Eighty healthy volunteers underwent acute thermal pain and provided pain ratings followed by confidence judgments on continuous visual analogue scales. We investigated whether eye fixations and reaction time during pain rating might serve as implicit markers of confidence. Confidence varied across trials and increased confidence was associated with faster pain rating reaction times. The association between confidence and fixations varied across individuals as a function of the reliability of individuals’ association between temperature and pain. Taken together, this work indicates that individuals can provide metacognitive judgments of pain and extends research on confidence in perceptual decision-making to pain.

Forced choices reveal a trade-off between cognitive effort and physical pain

Cognitive effort is described as aversive, and people will generally avoid it when possible. This aversion to effort is believed to arise from a cost-benefit analysis of the actions available. The comparison of cognitive effort against other primary aversive experiences, however, remains relatively unexplored. Here, we offered participants choices between performing a cognitively demanding task or experiencing thermal pain. We found that cognitive effort can be traded off for physical pain and that people generally avoid exerting high levels of cognitive effort. We also used computational modelling to examine the aversive subjective value of effort and its effects on response behaviours. Applying this model to decision times revealed asymmetric effects of effort and pain, suggesting that cognitive effort may not share the same basic influences on avoidance behaviour as more primary aversive stimuli such as physical pain.

Noxious pressure stimulation demonstrates robust, reliable estimates of brain activity and self-reported pain

Functional neuroimaging techniques have provided great insight in the field of pain. Utilising these techniques, we have characterised pain-induced responses in the brain and improved our understanding of key pain-related phenomena. Despite the utility of these methods, there remains a need to assess the test retest reliability of pain modulated blood-oxygen-level-dependant (BOLD) MR signal across repeated sessions. This is especially the case for more novel yet increasingly implemented stimulation modalities, such as noxious pressure, and it is acutely important for multi-session studies considering treatment efficacy. In the present investigation, BOLD signal responses were estimated for noxious-pressure stimulation in a group of healthy participants, across two separate sessions. Test retest reliability of functional magnetic resonance imaging (fMRI) data and self-reported visual analogue scale measures were determined by the intra-class correlation coefficient. High levels of reliability were observed in several key brain regions known to underpin the pain experience, including in the thalamus, insula, somatosensory cortices, and inferior frontal regions, alongside "excellent" reliability of self-reported pain measures. These data demonstrate that BOLD-fMRI derived signals are a valuable tool for quantifying noxious responses pertaining to pressure stimulation. We further recommend the implementation of pressure as a stimulation modality in experimental applications.

Non-specific analgesia during a clinical trial in fibromyalgia

BACKGROUND

When patients suffering from fibromyalgia undergo a therapeutic trial, a non-negligible part of analgesia is not explained by the drug itself. The mechanisms of this non-specific effect need to be understood.

MATERIALS AND METHODS

We undertook secondary analyses of a double-blind randomized trial in fibromyalgia patients in which 100 mg/day milnacipran was not found superior to placebo. Data from 49 patients belonging to both groups were pooled. Both before treatment and one month after treatment, all patients underwent a CaNTAB^® neuropsychological test (related to spatial planning, reaction time, decision-making and risk-taking, and ability to name objects), and measurements of sensation and pain thresholds to heat and cold, supraliminal heat pain threshold, punctuate mechanical pain threshold and temporal summation, mechanical allodynia to skin brushing, and response to conditioned pain modulation. We studied the baseline predictors of analgesia and the indicators of change associated to analgesia separately. A stepwise approach was used to select the factors to enter into the final ANCOVAs, in which age, body mass index, treatment group and pain at baseline were covariates.

RESULTS

No baseline predictor of non-specific analgesia other than pain at baseline was found to be predictive. Conversely, several neuropsychological (higher performance) or psychophysical (lower sensitivity) changes correlated with analgesia in unadjusted analyses. Multivariable analyses identified increases in warm/heat thermal thresholds and an increased ability to name objects, as factors associated with analgesia.

CONCLUSIONS

The changes observed concomitantly to non-specific pain analgesia might be related to mild changes in brain functioning, based on convergent literature data.

Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data

Background

Multivoxel pattern analysis has provided new evidence on somatotopic representation in the human brain. However, the effects of stimulus modality (e.g., penetrating needle versus non-penetrating touch) and level of classification (e.g., multiclass versus binary classification) on patterns of brain activity encoding spatial information of body parts have not yet been studied. We hypothesized that performance of brain-based prediction models may vary across the types of stimuli, and neural patterns of voxels in the SI and parietal cortex would significantly contribute to the prediction of stimulated locations.

Objective

We aimed to (1) test whether brain responses to tactile stimuli could distinguish among stimulated locations on the body surface, (2) investigate whether the stimulus modality and number of classes affect classification performance, and (3) localize brain regions encoding the spatial information of somatosensory stimuli.

Methods

Fifteen healthy participants completed two functional magnetic resonance imaging (MRI) scans and were stimulated via the insertion of acupuncture needles or by non-invasive touch stimuli (5.46-sized von Frey filament). Participants received the stimuli at four different locations on the upper and lower limbs (two sites each) for 5 min while blood-oxygen-level-dependent activity (BOLD) was measured using 3-Tesla MRI. We performed multivariate pattern analysis (MVPA) using parameter estimate images of each trial for each participant and the support vector classifier (SVC) function, and the prediction accuracy and other MVPA outcomes were evaluated using stratified five-fold cross validation. We estimated the significance of the classification accuracy using a permutation test with randomly labeled training data (n = 10,000). Searchlight analysis was conducted to identify brain regions associated with significantly higher accuracy compared to predictions based on chance as obtained from a random classifier.

Results

For the four-class classification (classifying four stimulated points on the body), SVC analysis of whole-brain beta values in response to acupuncture stimulation was able to discriminate among stimulated locations (mean accuracy, 0.31; q < 0.01). The searchlight analysis found that values related to the right primary somatosensory cortex (SI) and intraparietal sulcus were significantly more accurate than those due to chance (p < 0.01). On the other hand, the same classifier did not predict stimulated locations accurately for touch stimulation (mean accuracy, 0.25; q = 0.66). For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q < 0.001) and touch stimulation (mean accuracy, 0.60; q < 0.01). Searchlight analysis revealed that predictions based on the right SI, primary motor cortex (MI), paracentral gyrus, and superior frontal gyrus were significantly more accurate compared to predictions based on chance (p < 0.05).

Conclusion

Our findings suggest that the SI, as well as the MI, intraparietal sulcus, paracentral gyrus, and superior frontal gyrus, is responsible for the somatotopic representation of body parts stimulated by tactile stimuli. The MVPA approach for identifying neural patterns encoding spatial information of somatosensory stimuli may be affected by the stimulus type (penetrating needle versus non-invasive touch) and the number of classes (classification of four small points on the body versus two large body parts). Future studies with larger samples will identify stimulus-specific neural patterns representing stimulated locations, independent of subjective tactile perception and emotional responses. Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.

Let it be: mindful acceptance down-regulates pain and negative emotion

Mindfulness training ameliorates clinical and self-report measures of depression and chronic pain, but its use as an emotion regulation strategy—in individuals who do not meditate—remains understudied. As such, whether it (i) down-regulates early affective brain processes or (ii) depends on cognitive control systems remains unclear. We exposed meditation-naïve participants to two kinds of stimuli: negative vs. neutral images and painful vs. warm temperatures. On alternating blocks, we asked participants to either react naturally or exercise mindful acceptance. Emotion regulation using mindful acceptance was associated with reductions in reported pain and negative affect, reduced amygdala responses to negative images and reduced heat-evoked responses in medial and lateral pain systems. Critically, mindful acceptance significantly reduced activity in a distributed, a priori neurologic signature that is sensitive and specific to experimentally induced pain. In addition, these changes occurred in the absence of detectable increases in prefrontal control systems. The findings support the idea that momentary mindful acceptance regulates emotional intensity by changing initial appraisals of the affective significance of stimuli, which has consequences for clinical treatment of pain and emotion.

Pain-modulating effects of oxytocin in patients with chronic low back pain

The neuropeptide oxytocin (OT) has been shown to play a modulatory role in nociception. However, analgesic effects of OT in chronic pain conditions remain elusive and the neural underpinnings have not yet been investigated in humans. Here, we conducted an exploratory, randomized, placebo-controlled, cross-over study to examine effects of intranasal OT in male patients suffering from chronic low back pain (CBP) versus healthy controls (HC). N = 22 participants with CBP and 22 HCs were scanned using functional magnetic resonance imaging (fMRI) while they continuously rated either spontaneously occurring back pain or acute thermal pain stimuli applied to the lower back. During heat pain processing we found that OT versus PL attenuated pain intensity ratings and increased BOLD responses in the caudate nucleus of the striatum in CBP versus HCs. Spontaneously experienced pain in contrast to heat pain was associated with activation changes in the medial frontal cortex (MFC) and the anterior cingulate cortex (ACC) as reported in previous studies. However, we did not observe OT effects on spontaneously experienced pain in CBP patients. Overall, our preliminary data may suggest that the striatum is a key structure underlying the pain-modulating effects of OT in patients with chronic pain and adds to the growing evidence linking the neuropeptide to pain modulation in humans. Further studies on neuronal OT effects in larger samples of chronic back pain patients are needed to understand probable mechanisms of OT effects in chronic pain. This article is part of the special issue on Neuropeptides.

Multiple Brain Networks Mediating Stimulus-Pain Relationships in Humans

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

Noninvasive vagus nerve stimulation and the trigeminal autonomic reflex

Objective

The trigeminal autonomic reflex is a physiologic reflex that plays a crucial role in primary headache and particularly in trigeminal autonomic cephalalgias, such as cluster headache. Previous studies have shown that this reflex can be modulated by the vagus nerve, leading to an inhibition of the parasympathetic output of the reflex in healthy participants. The aim of the present study was to characterize neural correlates of the modulatory effect of noninvasive vagus nerve stimulation (nVNS) on the trigeminal autonomic reflex.

Methods

Twenty-one healthy participants were included in a 2-day, randomized, single-blind, within-subject design. The reflex was activated inside the MRI scanner using kinetic oscillation stimulation placed in the left nostril, resulting in an increase in lacrimation. After the first fMRI session, the participants received either sham vagus nerve stimulation or nVNS outside the scanner and underwent a subsequent fMRI session.

Results

nVNS prompted an increase in activation of the left pontine nucleus and a decreased activation of the right parahippocampal gyrus. Psychophysiologic interaction analyses revealed an increased functional connectivity between the left pontine nucleus and the right hypothalamus and a decreased functional connectivity between the right parahippocampal gyrus and the bilateral spinal trigeminal nuclei (sTN).

Conclusions

These findings indicate a complex network involved in the modulatory effect of nVNS including the hypothalamus, the sTN, the pontine nucleus, and the parahippocampal gyrus.

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

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

Pain-Evoked Reorganization in Functional Brain Networks

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

Negative life experiences contribute to racial differences in the neural response to threat

Threat-related emotional function is supported by a neural circuit that includes the prefrontal cortex (PFC), hippocampus, and amygdala. The function of this neural circuit is altered by negative life experiences, which can potentially affect threat-related emotional processes. Notably, Black-American individuals disproportionately endure negative life experiences compared to White-American individuals. However, the relationships among negative life experiences, race, and the neural substrates that support threat-related emotional function remains unclear. Therefore, the current study investigated whether the brain function that supports threat-related emotional processes varies with racial differences in negative life experiences. In the present study, adolescent violence exposure, family income, and neighborhood disadvantage were measured prospectively (i.e., at 11-19 years of age) for Black-American and White-American volunteers. Participants then, as young adults (i.e., 18-23 years of age), completed a Pavlovian fear conditioning task during functional magnetic resonance imaging (fMRI). Cued and non-cued threats were presented during the conditioning task and behavioral (threat expectancy) and psychophysiological responses (skin conductance response; SCR) were recorded simultaneously with fMRI. Racial differences were observed in neural (fMRI activity), behavioral (threat expectancy), and psychophysiological (SCR) responses to threat. These threat-elicited responses also varied with negative life experiences (violence exposure, family income, and neighborhood disadvantage). Notably, racial differences in brain activity to threat were smaller after accounting for negative life experiences. The present findings suggest that racial differences in the neural and behavioral response to threat are due, in part, to exposure to negative life experiences and may provide new insight into the mechanisms underlying racial disparities in mental health.

Sparse Principal Component based High-Dimensional Mediation Analysis

Causal mediation analysis aims to quantify the intermediate effect of a mediator on the causal pathway from treatment to outcome. When dealing with multiple mediators, which are potentially causally dependent, the possible decomposition of pathway effects grows exponentially with the number of mediators. An existing approach incorporated the principal component analysis (PCA) to address this challenge based on the fact that the transformed mediators are conditionally independent given the orthogonality of the principal components (PCs). However, the transformed mediator PCs, which are linear combinations of original mediators, can be difficult to interpret. A sparse high-dimensional mediation analysis approach is proposed which adopts the sparse PCA method to the mediation setting. The proposed approach is applied to a task-based functional magnetic resonance imaging study, illustrating its ability to detect biologically meaningful results related to an identified mediator.

Endogenous fluctuations in the dopaminergic midbrain drive behavioral choice variability

Humans are surprisingly inconsistent in their behavior, often making different choices under identical conditions. Previous research suggests that intrinsic fluctuations in brain activity can influence low-level processes, such as the amount of force applied in a motor response. Here, we show that intrinsic prestimulus brain activity in the dopaminergic midbrain influences how we choose between risky and safe options. Using computational modeling, we demonstrate that endogenous fluctuations alter phasic responses in a decision network and thereby modulate risk taking. Our findings demonstrate that higher-order cognition is influenced by fluctuations in internal brain states, providing a physiological basis for variability in complex human behavior.

Human behavior is surprisingly variable, even when facing the same problem under identical circumstances. A prominent example is risky decision making. Economic theories struggle to explain why humans are so inconsistent. Resting-state studies suggest that ongoing endogenous fluctuations in brain activity can influence low-level perceptual and motor processes, but it remains unknown whether endogenous fluctuations also influence high-level cognitive processes including decision making. Here, using real-time functional magnetic resonance imaging, we tested whether risky decision making is influenced by endogenous fluctuations in blood oxygenation level-dependent (BOLD) activity in the dopaminergic midbrain, encompassing ventral tegmental area and substantia nigra. We show that low prestimulus brain activity leads to increased risky choice in humans. Using computational modeling, we show that increased risk taking is explained by enhanced phasic responses to offers in a decision network. Our findings demonstrate that endogenous brain activity provides a physiological basis for variability in complex human behavior.

Catastrophizing Interferes with Cognitive Modulation of Pain in Women with Fibromyalgia

Background

Pain modulation is a critical function of the nociceptive system that includes the ability to engage descending pain control systems to maintain a functional balance between facilitation and inhibition of incoming sensory stimuli. Dysfunctional pain modulation is associated with increased risk for chronic pain and is characteristic of fibromyalgia (FM). Catastrophizing is also common in FM. However, its influence on pain modulation is poorly understood.

Objective

To determine the role of catastrophizing on central nervous system processing during pain modulation in FM via examining brain responses and pain sensitivity during an attention-distraction paradigm.

Methods

Twenty FM patients and 18 healthy controls (CO) underwent functional magnetic resonance imaging while receiving pain stimuli, administered alone and during distracting cognitive tasks. Pain ratings were assessed after each stimulus. Catastrophizing was assessed with the Pain Catastrophizing Scale (PCS).

Results

The ability to modulate pain during distraction varied among FM patients and was associated with catastrophizing. This was demonstrated by significant positive relationships between PCS scores and pain ratings (P < 0.05) and brain responses in the dorsolateral prefrontal cortex (P < 0.01). Relationships between catastrophizing and pain modulation did not differ between FM and CO (P > 0.05).

Conclusions

FM patients with higher levels of catastrophizing were less able to distract themselves from pain, indicative of catastrophizing-related impairments in pain modulation. These results suggest that the tendency to catastrophize interacts with attention-resource allocation and may represent a mechanism of chronic pain exacerbation and/or maintenance. Reducing catastrophizing may improve FM symptoms via improving central nervous system regulation of pain.