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      Regulation of Mindfulness-Based Music Listening on Negative Emotions Related to COVID-19: An ERP Study

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          Abstract

          The current study aimed to explore the behavioral and neural correlates of mindfulness-based music listening regulation of induced negative emotions related to COVID-19 using the face–word Stroop task. Eighty-five young adults visited the laboratory and were randomly assigned to three groups: a calm music group (CMG: n = 28), a happy music group (HMG: n = 30), and a sad music group (SMG: n = 27). Negative emotions were induced in all participants using a COVID-19 video, followed by the music intervention condition. Participants underwent the face–word Stroop tasks during which event-related potentials (ERPs) were recorded. The N2, N3, P3, and late positive component (LPC) were investigated. The results showed that calm music and happy music effectively regulate young adults’ induced negative emotions, while young adults experienced more negative emotions when listening to sad music; the negative mood states at the post-induction phase inhibited the reaction of conflict control in face–word Stroop tasks, which manifested as lower accuracy (ACC) and slower reaction times (RTs). ERP results showed negative mood states elicited greater N2, N3, and LPC amplitudes and smaller P3 amplitudes. Further studies are needed to develop intervention strategies to enhance emotion regulation related to COVID-19 for other groups.

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          In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented.
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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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              Stress, Appraisal, and Coping

              <p><b>The reissue of a classic work, now with a foreword by Daniel Goleman!</b><p>Here is a monumental work that continues in the tradition pioneered by co-author Richard Lazarus in his classic book <i>Psychological Stress and the Coping Process</i>. Dr. Lazarus and his collaborator, Dr. Susan Folkman, present here a detailed theory of psychological stress, building on the concepts of cognitive appraisal and coping which have become major themes of theory and investigation.</p> <p>As an integrative theoretical analysis, this volume pulls together two decades of research and thought on issues in behavioral medicine, emotion, stress management, treatment, and life span development. A selective review of the most pertinent literature is included in each chapter. The total reference listing for the book extends to 60 pages.</p> <p>This work is necessarily multidisciplinary, reflecting the many dimensions of stress-related problems and their situation within a complex social context. While the emphasis is on psychological aspects of stress, the book is oriented towards professionals in various disciplines, as well as advanced students and educated laypersons. The intended audience ranges from psychiatrists, clinical psychologists, nurses, and social workers to sociologists, anthropologists, medical researchers, and physiologists.</p>
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                01 July 2021
                July 2021
                : 18
                : 13
                : 7063
                Affiliations
                [1 ]Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing 400715, China; Liumusicpsy@ 123456163.com (X.L.); liuy0768@ 123456swu.edu.cn (Y.L.)
                [2 ]School of Psychology, Southwest University, Chongqing 400715, China
                [3 ]Institute of Chinese Music Aesthetic Psychology and Basic Theory of Music Performance, Chongqing Institute of Foreign Studies, Chongqing 401120, China; shishi1984219@ 123456sina.com (H.S.); llling19954@ 123456126.com (L.L.)
                [4 ]School of Music, Southwest University, Beibei, Chongqing 400715, China
                Author notes
                [* ]Correspondence: zhengswu@ 123456126.com
                [†]

                Xiaolin Liu and Yong Liu contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1753-4653
                Article
                ijerph-18-07063
                10.3390/ijerph18137063
                8296951
                34280999
                9aaf8e65-fae5-42ea-979b-a65503038bbb
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 28 April 2021
                : 23 June 2021
                Categories
                Article

                Public health
                mindfulness meditation,music listening,emotion regulation,cognitive control,erps
                Public health
                mindfulness meditation, music listening, emotion regulation, cognitive control, erps

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