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Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual's expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

A recent study by Lee et al. showed that a dynamic functional connectivity pattern induced by tonic experimental pain might serve as a biomarker of chronic pain. The study illustrates key topics in translational neuroscience: the differentiation of biomarker functions, the multimodal integration of biomarkers, and the functional relevance of dynamic connectivity., Competing Interests: Declaration of Interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically exploited the potential of electroencephalography to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity, and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4-8 Hz) and gamma (>60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results suggest that increased theta and gamma synchrony in frontal brain areas are involved in the pathophysiology of chronic pain. Although substantial challenges concerning the reproducibility of the findings and the accuracy, specificity, and validity of potential electroencephalography-based disease markers remain to be overcome, our study indicates that abnormal frontal synchrony at theta and gamma frequencies might be promising targets for noninvasive brain stimulation and/or neurofeedback approaches.

Pain is a complex phenomenon involving perceptual, motor, and autonomic responses, but how the brain translates noxious stimuli into these different dimensions of pain is unclear. Here, we assessed perceptual, motor, and autonomic responses to brief noxious heat stimuli and recorded brain activity using electroencephalography (EEG) in humans. Multilevel mediation analysis reveals that each pain dimension is subserved by a distinct pattern of EEG responses and, conversely, that each EEG response differentially contributes to the different dimensions of pain. In particular, the translation of noxious stimuli into autonomic and motor responses involved the earliest N1 wave, whereas pain perception was mediated by later N2 and P2 waves. Gamma oscillations mediated motor responses rather than pain perception. These findings represent progress towards a mechanistic understanding of the brain processes translating noxious stimuli into pain and suggest that perceptual, motor, and autonomic dimensions of pain are partially independent rather than serial processes.

Pain serves the protection of the body by translating noxious stimulus information into a subjective percept and protective responses. Such protective responses rely on autonomic responses that allocate energy resources to protective functions. However, the precise relationship between objective stimulus intensity, subjective pain intensity, autonomic responses, and brain activity is not fully clear yet. Here, we addressed this question by continuously recording pain ratings, skin conductance, heart rate, and electroencephalography during tonic noxious heat stimulation of the hand in 39 healthy human subjects. The results confirmed that pain intensity dissociates from stimulus intensity during 10 minutes of noxious stimulation. Furthermore, skin conductance measures were significantly related to stimulus intensity but not to pain intensity. Correspondingly, skin conductance measures were significantly related to alpha and beta oscillations in contralateral sensorimotor cortex, which have been shown to encode stimulus intensity rather than pain intensity. No significant relationships were found between heart rate and stimulus intensity or pain intensity. The findings were consistent for stimulation of the left and the right hands. These results suggest that sympathetic autonomic responses to noxious stimuli in part directly result from nociceptive rather than from perceptual processes. Beyond, these observations support concepts of pain and emotions in which sensory, motor, and autonomic components are partially independent processes that together shape emotional and painful experiences.

The protective function of pain depends on appropriate motor responses to avoid injury and promote recovery. The preparation and execution of motor responses is thus an essential part of pain. However, it is not yet fully understood how pain and motor processes interact in the brain. Here we used electroencephalography to investigate the effects of pain on motor preparation in the human brain. Twenty healthy human participants performed a motor task in which they performed button presses to stop increasingly painful thermal stimuli when they became intolerable. In another condition, participants performed button presses without concurrent stimulation. The results show that the amplitudes of preparatory event-related desynchronizations at alpha and beta frequencies did not differ between conditions. In contrast, the amplitude of the preparatory readiness potential was reduced when a button press was performed to stop a painful stimulus compared with a button press without concomitant pain. A control experiment with nonpainful thermal stimuli showed a similar reduction of the readiness potential when a button press was performed to stop a nonpainful thermal stimulus. Together, these findings indicate that painful and nonpainful thermal stimuli can similarly influence motor preparation in the human brain. Pain-specific effects on motor preparation in the human brain remain to be demonstrated. NEW & NOTEWORTHY Pain is inherently linked to motor processes, but the interactions between pain and motor processes in the human brain are not yet fully understood. Using electroencephalography, we show that pain reduces movement-preparatory brain activity. Further results indicate that this effect is not pain specific but independent of the modality of stimulation., (Copyright © 2017 the American Physiological Society.)

Noxious stimuli induce physiological processes which commonly translate into pain. However, under certain conditions, pain intensity can substantially dissociate from stimulus intensity, e.g. during longer-lasting pain in chronic pain syndromes. How stimulus intensity and pain intensity are differentially represented in the human brain is, however, not yet fully understood. We therefore used electroencephalography (EEG) to investigate the cerebral representation of noxious stimulus intensity and pain intensity during 10min of painful heat stimulation in 39 healthy human participants. Time courses of objective stimulus intensity and subjective pain ratings indicated a dissociation of both measures. EEG data showed that stimulus intensity was encoded by decreases of neuronal oscillations at alpha and beta frequencies in sensorimotor areas. In contrast, pain intensity was encoded by gamma oscillations in the medial prefrontal cortex. Contrasting right versus left hand stimulation revealed that the encoding of stimulus intensity in contralateral sensorimotor areas depended on the stimulation side. In contrast, a conjunction analysis of right and left hand stimulation revealed that the encoding of pain in the medial prefrontal cortex was independent of the side of stimulation. Thus, the translation of noxious stimulus intensity into pain is associated with a change from a spatially specific representation of stimulus intensity by alpha and beta oscillations in sensorimotor areas to a spatially independent representation of pain by gamma oscillations in brain areas related to cognitive and affective-motivational processes. These findings extend the understanding of the brain mechanisms of nociception and pain and their dissociations during longer-lasting pain as a key symptom of chronic pain syndromes., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

The perception of pain is characterized by its tremendous intra- and interindividual variability. Different individuals perceive the very same painful event largely differently. Here, we aimed to predict the individual pain sensitivity from brain activity. We repeatedly applied identical painful stimuli to healthy human subjects and recorded brain activity by using electroencephalography (EEG). We applied a multivariate pattern analysis to the time-frequency transformed single-trial EEG responses. Our results show that a classifier trained on a group of healthy individuals can predict another individual's pain sensitivity with an accuracy of 83%. Classification accuracy depended on pain-evoked responses at about 8 Hz and pain-induced gamma oscillations at about 80 Hz. These results reveal that the temporal-spectral pattern of pain-related neuronal responses provides valuable information about the perception of pain. Beyond, our approach may help to establish an objective neuronal marker of pain sensitivity which can potentially be recorded from a single EEG electrode.

Chronic pain is a major health care issue characterized by ongoing pain and a variety of sensory, cognitive, and affective abnormalities. The neural basis of chronic pain is still not completely understood. Previous work has implicated prefrontal brain areas in chronic pain. Furthermore, prefrontal neuronal oscillations at gamma frequencies (60–90 Hz) have been shown to reflect the perceived intensity of longer lasting experimental pain in healthy human participants. In contrast, noxious stimulus intensity has been related to alpha (8–13 Hz) and beta (14–29 Hz) oscillations in sensorimotor areas. However, it is not fully understood how the intensity of ongoing pain as the key symptom of chronic pain is represented in the human brain. Here, we asked 31 chronic back pain patients to continuously rate their ongoing pain while simultaneously recording electroencephalography (EEG). Time–frequency analyses revealed a positive association between ongoing pain intensity and prefrontal beta and gamma oscillations. No association was found between pain and alpha or beta oscillations in sensorimotor areas. These findings indicate that ongoing pain as the key symptom of chronic pain is reflected by neuronal oscillations implicated in the subjective perception of longer lasting pain rather than by neuronal oscillations related to the processing of objective nociceptive input. The findings, thus, support a dissociation of pain intensity from nociceptive processing in chronic back pain patients. Furthermore, although possible confounds by muscle activity have to be taken into account, they might be useful for defining a neurophysiological marker of ongoing pain in the human brain. [ABSTRACT FROM AUTHOR]

Painful stimuli are of utmost behavioral relevance and thereby affect attentional resources. In health, variable effects of pain on attention have been observed, indicating alerting as well as distracting effects of pain. In the human brain, these effects are closely related to modulations of neuronal gamma oscillations. As hypervigilance as an abnormal increase of attention to external stimuli has been implicated in chronic pain states, we assumed both attentional performance and pain-induced gamma oscillations to be altered in patients with fibromyalgia syndrome (FMS). We recorded electroencephalography from healthy subjects (n = 22) and patients with FMS (n = 19) during an attention demanding visual reaction time task. In 50% of the trials we applied painful laser stimuli. The results of self-assessment questionnaires confirm that patients with FMS consider themselves hypervigilant towards pain as compared to healthy controls. However, the experimental findings indicate that the effects of painful stimuli on attentional performance and neuronal gamma oscillations do not differ between patients and healthy subjects. We further found a significant correlation between the pain-induced modulation of visual gamma oscillations and the pain-induced modulation of reaction times. This relationship did not differ between groups either. These findings confirm a close relationship between gamma oscillations and the variable attentional effects of pain, which appear to be comparable in health and disease. Thus, our results do not provide evidence for a behavioral or neuronal manifestation of hypervigilance in patients with FMS. [ABSTRACT FROM AUTHOR]

Abstract: Chronic pain is a major healthcare issue posing a large burden on individuals and society. Converging lines of evidence indicate that chronic pain is associated with substantial changes of brain structure and function. However, it remains unclear which neuronal measures relate to changes of clinical parameters over time and could thus monitor chronic pain and treatment responses. We therefore performed a longitudinal study in which we assessed clinical characteristics and resting-state electroencephalography data of 41 patients with chronic pain before and 6 months after interdisciplinary multimodal pain therapy. We specifically assessed electroencephalography measures that have previously been shown to differ between patients with chronic pain and healthy people. These included the dominant peak frequency; the amplitudes of neuronal oscillations at theta, alpha, beta, and gamma frequencies; as well as graph theory-based measures of brain network organization. The results show that pain intensity, pain-related disability, and depression were significantly improved after interdisciplinary multimodal pain therapy. Bayesian hypothesis testing indicated that these clinical changes were not related to changes of the dominant peak frequency or amplitudes of oscillations at any frequency band. Clinical changes were, however, associated with an increase in global network efficiency at theta frequencies. Thus, changes in chronic pain might be reflected by global network changes in the theta band. These longitudinal insights further the understanding of the brain mechanisms of chronic pain. Beyond, they might help to identify biomarkers for the monitoring of chronic pain. [ABSTRACT FROM AUTHOR]