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      Critical role of rhythms in prefrontal transcranial magnetic stimulation for depression: A randomized sham‐controlled study

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          Abstract

          Repetitive transcranial magnetic stimulation (rTMS) is an alternative treatment for depression, but the neural correlates of the treatment are currently inconclusive, which might be a limit of conventional analytical methods. The present study aimed to investigate the neurophysiological evidence and potential biomarkers for rTMS and intermittent theta burst stimulation (iTBS) treatment. A total of 61 treatment‐resistant depression patients were randomly assigned to receive prolonged iTBS (piTBS; N = 19), 10 Hz rTMS ( N = 20), or sham stimulation ( N = 22). Each participant went through a treatment phase with resting state electroencephalography (EEG) recordings before and after the treatment phase. The aftereffects of stimulation showed that theta‐alpha amplitude modulation frequency ( f am) was associated with piTBS_Responder, which involves repetitive bursts delivered in the theta frequency range, whereas alpha carrier frequency ( f c) was related to 10 Hz rTMS, which uses alpha rhythmic stimulation. In addition, theta‐alpha amplitude modulation frequency was positively correlated with piTBS antidepressant efficacy, whereas the alpha frequency was not associated with the 10 Hz rTMS clinical outcome. The present study showed that TMS stimulation effects might be lasting, with changes of brain oscillations associated with the delivered frequency. Additionally, theta‐alpha amplitude modulation frequency may be as a function of the degree of recovery in TRD with piTBS treatment and also a potential EEG‐based predictor of antidepressant efficacy of piTBS in the early treatment stage, that is, first 2 weeks.

          Abstract

          The present study, utilizing HHSA to study the nonlinear cross‐frequency modulation, provided evidence of the distinct antidepressant neural correlates of 10 Hz rTMS and piTBS for TRD. The findings suggested that the TMS treatment, whatever protocol was applied, may provide lasting benefits, with the possible entrainment aftereffects seemingly revealed in resulting brain oscillation changes. Furthermore, our findings imply that theta‐alpha amplitude modulation frequency changes may indicate a function of response to piTBS treatment, not for rTMS, which may also indicate a possible predictive biomarker for treatment efficacy of piTBS in the early treatment stage, that is, first 2 weeks.

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          Most cited references53

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          A RATING SCALE FOR DEPRESSION

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            Nonparametric statistical testing of EEG- and MEG-data.

            In this paper, we show how ElectroEncephaloGraphic (EEG) and MagnetoEncephaloGraphic (MEG) data can be analyzed statistically using nonparametric techniques. Nonparametric statistical tests offer complete freedom to the user with respect to the test statistic by means of which the experimental conditions are compared. This freedom provides a straightforward way to solve the multiple comparisons problem (MCP) and it allows to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the statistical test. The paper is written for two audiences: (1) empirical neuroscientists looking for the most appropriate data analysis method, and (2) methodologists interested in the theoretical concepts behind nonparametric statistical tests. For the empirical neuroscientist, a large part of the paper is written in a tutorial-like fashion, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect. And for the methodologist, it is explained why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis.
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              The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

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                Author and article information

                Contributors
                ctil2@vghtpe.gov.tw
                chijuan@cc.ncu.edu.tw
                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
                07 December 2021
                1 April 2022
                : 43
                : 5 ( doiID: 10.1002/hbm.v43.5 )
                : 1535-1547
                Affiliations
                [ 1 ] Institute of Cognitive Neuroscience College of Health Sciences and Technology, National Central University Taoyuan City Taiwan
                [ 2 ] Department of Psychiatry Taipei Veterans General Hospital Taipei Taiwan
                [ 3 ] Institute of Brain Science National Yang‐Ming Chiao‐Tung University Taipei Taiwan
                [ 4 ] Division of Psychiatry, Faculty of Medicine National Yang‐Ming Chiao‐Tung University Taipei Taiwan
                [ 5 ] Cognitive Intelligence and Precision Healthcare Center National Central University Taoyuan City Taiwan
                [ 6 ] Department of Psychiatry Taoyuan Armed Forces General Hospital Taoyuan Taiwan
                [ 7 ] Key Laboratory of Data Analysis and Applications First Institute of Oceanography, State Oceanic Administration Qingdao China
                [ 8 ] Department of Psychology Kaohsiung Medical University Kaohsiung Taiwan
                Author notes
                [*] [* ] Correspondence

                Chi‐Hung Juan, Institute of Cognitive Neuroscience, College of Health Sciences and Technology, Cognitive Intelligence and Precision Healthcare Research Center, National Central University, No. 300, Jhongda Rd., Jhongli City 320, Taiwan.

                Email: chijuan@ 123456cc.ncu.edu.tw

                Cheng‐Ta Li, Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih‐Pai Rd., Beitou District, Taipei 112, Taiwan.

                Email: ctil2@ 123456vghtpe.gov.tw

                Author information
                https://orcid.org/0000-0002-0670-1153
                https://orcid.org/0000-0002-9076-3591
                Article
                HBM25740
                10.1002/hbm.25740
                8886663
                34873781
                05a60f2a-1f5c-4d6d-922b-51bfda3d7b3d
                © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 25 November 2021
                : 28 October 2021
                : 28 November 2021
                Page count
                Figures: 6, Tables: 1, Pages: 13, Words: 9813
                Funding
                Funded by: Ministry of Science and Technology , doi 10.13039/100007225;
                Award ID: 106‐2314‐B‐075‐034‐MY3
                Award ID: 106‐2410‐H‐008‐038‐MY3
                Award ID: 107‐2628‐H‐008‐002‐MY3
                Award ID: 108‐2321‐B‐075‐004‐MY2
                Award ID: 108‐2639‐H‐008‐001‐ASP
                Award ID: 109‐2639‐H‐008‐001‐ASP
                Award ID: 109‐2321‐B‐037‐001‐
                Award ID: 110‐2639‐H‐008‐001‐ASP
                Award ID: 110‐2321‐B‐037‐001
                Funded by: Taipei Veterans General Hospital , doi 10.13039/501100011912;
                Award ID: V108D44‐003‐MY3‐1
                Funded by: Taiwan Ministry of Education
                Funded by: National Yang‐Ming Chiao‐Tung University, Brain Research Center
                Award ID: 108BRC‐B502
                Funded by: Academic Strategic Alliance
                Funded by: Taiwan and Oxford University
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                April 1, 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.1 mode:remove_FC converted:01.03.2022

                Neurology
                brain oscillation,holo‐hilbert spectral analysis,prolonged intermittent theta burst stimulation,repetitive transcranial magnetic stimulation,treatment‐resistant depression

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