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      Prefrontal gamma oscillations reflect ongoing pain intensity in chronic back pain patients

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          Abstract

          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.

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          Most cited references 28

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          Removing electroencephalographic artifacts by blind source separation.

          Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.
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            The short-form McGill Pain Questionnaire.

             R Melzack (1987)
            A short form of the McGill Pain Questionnaire (SF-MPQ) has been developed. The main component of the SF-MPQ consists of 15 descriptors (11 sensory; 4 affective) which are rated on an intensity scale as 0 = none, 1 = mild, 2 = moderate or 3 = severe. Three pain scores are derived from the sum of the intensity rank values of the words chosen for sensory, affective and total descriptors. The SF-MPQ also includes the Present Pain Intensity (PPI) index of the standard MPQ and a visual analogue scale (VAS). The SF-MPQ scores obtained from patients in post-surgical and obstetrical wards and physiotherapy and dental departments were compared to the scores obtained with the standard MPQ. The correlations were consistently high and significant. The SF-MPQ was also shown to be sufficiently sensitive to demonstrate differences due to treatment at statistical levels comparable to those obtained with the standard form. The SF-MPQ shows promise as a useful tool in situations in which the standard MPQ takes too long to administer, yet qualitative information is desired and the PPI and VAS are inadequate.
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              Non-specific low back pain.

              Non-specific low back pain affects people of all ages and is a leading contributor to disease burden worldwide. Management guidelines endorse triage to identify the rare cases of low back pain that are caused by medically serious pathology, and so require diagnostic work-up or specialist referral, or both. Because non-specific low back pain does not have a known pathoanatomical cause, treatment focuses on reducing pain and its consequences. Management consists of education and reassurance, analgesic medicines, non-pharmacological therapies, and timely review. The clinical course of low back pain is often favourable, thus many patients require little if any formal medical care. Two treatment strategies are currently used, a stepped approach beginning with more simple care that is progressed if the patient does not respond, and the use of simple risk prediction methods to individualise the amount and type of care provided. The overuse of imaging, opioids, and surgery remains a widespread problem.
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                Author and article information

                Contributors
                markus.ploner@tum.de
                Journal
                Hum Brain Mapp
                Hum Brain Mapp
                10.1002/(ISSN)1097-0193
                HBM
                Human Brain Mapping
                John Wiley & Sons, Inc. (Hoboken, USA )
                1065-9471
                1097-0193
                10 September 2018
                January 2019
                : 40
                : 1 ( doiID: 10.1002/hbm.v40.1 )
                : 293-305
                Affiliations
                [ 1 ] Department of Neurology Technische Universität München Munich Germany
                [ 2 ] TUM‐Neuroimaging Center Technische Universität München Munich Germany
                [ 3 ] Institute of Neuroscience and Psychology University of Glasgow Glasgow United Kingdom
                [ 4 ] Institute for Biomagnetism and Biosignalanalysis University of Münster Münster Germany
                Author notes
                [* ] Correspondence Markus Ploner, Department of Neurology, Technische Universität München, Ismaninger Str. 22, 81675 Munich, Germany.

                Email: markus.ploner@ 123456tum.de

                Article
                HBM24373
                10.1002/hbm.24373
                6585682
                30260531
                © 2018 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 5, Tables: 2, Pages: 13, Words: 11544
                Product
                Funding
                Funded by: Bavarian State Ministry of Education, Science and the Arts
                Funded by: Deutsche Forschungsgemeinschaft
                Award ID: PL 321/13‐1
                Award ID: PL 321/11‐2
                Award ID: PL 321/10‐2
                Award ID: PL 321/11‐1
                Award ID: PL 321/10‐1
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                hbm24373
                January 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.4 mode:remove_FC converted:20.06.2019

                Neurology

                prefrontal cortex, oscillations, electroencephalography, chronic pain, brain

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