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      A 5-day course of rTMS before pain onset ameliorates future pain and increases sensorimotor peak alpha frequency

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          Abstract

          Repetitive transcranial magnetic stimulation (rTMS) has shown promise as an intervention for pain. An unexplored research question is whether the delivery of rTMS prior to pain onset might protect against a future episode of prolonged pain. The present study aimed to determine i) whether 5 consecutive days of rTMS delivered prior to experimentally-induced prolonged jaw pain could reduce future pain intensity and ii) whether any effects of rTMS on pain were mediated by changes in corticomotor excitability (CME) and/or sensorimotor peak alpha frequency (PAF). On each day from Day 0–4, forty healthy individuals received a single session of active (n = 21) or sham (n = 19) rTMS over the left primary motor cortex. PAF and CME were assessed on Day 0 (before rTMS) and Day 4 (after rTMS). Prolonged pain was induced via intramuscular injection of nerve growth factor (NGF) in the right masseter muscle after the final rTMS session. From Days 5–25, participants completed twice-daily electronic dairies including pain on chewing and yawning (primary outcomes), as well as pain during other activities (e.g. talking), functional limitation in jaw function and muscle soreness (secondary outcomes). Compared to sham, individuals who received active rTMS subsequently experienced lower pain on chewing and yawning. Although active rTMS increased PAF, the effects of rTMS on pain were not mediated by changes in PAF or CME. This study is the first to show that rTMS delivered prior to pain onset can protect against future pain and associated functional impairment. Thus, rTMS may hold promise as a prophylactic intervention for persistent pain.

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          The PHQ-9: validity of a brief depression severity measure.

          While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
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            lavaan: AnRPackage for Structural Equation Modeling

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              EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

              We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                13 June 2024
                : 2024.06.11.598596
                Affiliations
                [1 ]Center for Pain IMPACT, Neuroscience Research Australia, Sydney, New South Wales, Australia
                [2 ]University of New South Wales, Sydney, New South Wales, Australia
                [3 ]School of Health Sciences, College of Health, Medicine and Wellbeing, The University of Newcastle, Callaghan, New South Wales, Australia
                [4 ]Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
                [5 ]Department of Medical Biophysics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada
                [6 ]The Gray Centre for Mobility and Activity, Parkwood Institute, St. Joseph’s Healthcare, London, Canada
                [7 ]School of Physical Therapy, University of Western Ontario, London, Canada
                Author notes
                Corresponding author: Dr Nahian Chowdhury, PhD , Center for Pain IMPACT, Neuroscience Research Australia, Sydney, New South Wales, Australia, n.chowdhury@ 123456neura.edu.au
                Author information
                http://orcid.org/0000-0001-6357-0746
                http://orcid.org/0000-0003-1409-8179
                http://orcid.org/0000-0003-3111-3756
                Article
                10.1101/2024.06.11.598596
                11195234
                38915700
                f4572548-4444-4430-9a2d-5ead89822c1a

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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                rtms,transcranial-magnetic stimulation,electroencephalography,pain,analgesia

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