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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.