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      Trends of Repetitive Transcranial Magnetic Stimulation From 2009 to 2018: A Bibliometric Analysis

      systematic-review

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          Abstract

          Repetitive transcranial magnetic stimulation (rTMS) technology, which is amongst the most used non-invasive brain stimulation techniques currently available, has developed rapidly from 2009 to 2018. However, reports on the trends of rTMS using bibliometric analysis are rare. The goal of the present bibliometric analysis is to analyze and visualize the trends of rTMS, including general (publication patterns) and emerging trends (research frontiers), over the last 10 years by using the visual analytic tool CiteSpace V. Publications related to rTMS from 2009 to 2018 were retrieved from the Web of Science (WoS) database, including 2,986 peer-reviewed articles/reviews. Active authors, journals, institutions, and countries were identified by WoS and visualized by CiteSpace V, which could also detect burst changes to identify emerging trends. GraphPad Prism 8 was used to analyze the time trend of annual publication outputs. The USA ranked first in this field. Pascual-Leone A (author A), Fitzgerald PB (author B), George MS (author C), Lefaucheur JP (author D), and Fregni F (author E) made great contributions to this field of study. The most prolific institution to publish rTMS-related publications in the last decade was the University of Toronto. The journal Brain Stimulation published most papers. Lefaucheur et al.'s paper in 2014, and the keyword “sham controlled trial” showed the strongest citation bursts by the end of 2018, which indicates increased attention to the underlying work, thereby indicating the research frontiers. This study reveals the publication patterns and emerging trends of rTMS based on the records published from 2009 to 2018. The insights obtained have reference values for the future research and application of rTMS.

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          Small-world brain networks.

          Many complex networks have a small-world topology characterized by dense local clustering or cliquishness of connections between neighboring nodes yet a short path length between any (distant) pair of nodes due to the existence of relatively few long-range connections. This is an attractive model for the organization of brain anatomical and functional networks because a small-world topology can support both segregated/specialized and distributed/integrated information processing. Moreover, small-world networks are economical, tending to minimize wiring costs while supporting high dynamical complexity. The authors introduce some of the key mathematical concepts in graph theory required for small-world analysis and review how these methods have been applied to quantification of cortical connectivity matrices derived from anatomical tract-tracing studies in the macaque monkey and the cat. The evolution of small-world networks is discussed in terms of a selection pressure to deliver cost-effective information-processing systems. The authors illustrate how these techniques and concepts are increasingly being applied to the analysis of human brain functional networks derived from electroencephalography/magnetoencephalography and fMRI experiments. Finally, the authors consider the relevance of small-world models for understanding the emergence of complex behaviors and the resilience of brain systems to pathological attack by disease or aberrant development. They conclude that small-world models provide a powerful and versatile approach to understanding the structure and function of human brain systems.
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            The bibliometric analysis of scholarly production: How great is the impact?

            Bibliometric methods or “analysis” are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449–551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, “subject” based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which contribute to the pool of bibliometric analysis, as well as a self-perpetuating effect in giving and taking references.
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              Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace.

              Regenerative medicine involves research in a number of fields and disciplines such as stem cell research, tissue engineering and biological therapy in general. As research in these areas advances rapidly, it is critical to keep abreast of emerging trends and critical turns of the development of the collective knowledge.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                26 February 2020
                2020
                : 14
                : 106
                Affiliations
                [1] 1Department of Sport Rehabilitation, Shanghai University of Sport , Shanghai, China
                [2] 2The Fifth Clinical College, Guangzhou Medical University , Guangzhou, China
                [3] 3Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University , Guangzhou, China
                [4] 4Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology , Guangzhou, China
                [5] 5Department of Rehabilitation Medicine, Shanghai Shangti Orthopaedic Hospital , Shanghai, China
                Author notes

                Edited by: Ioan Opris, University of Miami, United States

                Reviewed by: Estate M. Sokhadze, University of South Carolina, United States; Kim Drnec, United States Army Research Laboratory, United States

                *Correspondence: Yue Lan bluemooning@ 123456163.com

                This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience

                †These authors have contributed equally to this work

                Article
                10.3389/fnins.2020.00106
                7057247
                32174808
                ddff1ba3-424b-42de-aec6-067dabfaec77
                Copyright © 2020 Zheng, Dai, Lan and Wang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 03 October 2019
                : 27 January 2020
                Page count
                Figures: 4, Tables: 6, Equations: 0, References: 107, Pages: 11, Words: 8156
                Funding
                Funded by: Shanghai University of Sport 10.13039/501100002397
                Categories
                Neuroscience
                Systematic Review

                Neurosciences
                rtms,frontiers,bibliometrics,citation burst,web of science,citespace
                Neurosciences
                rtms, frontiers, bibliometrics, citation burst, web of science, citespace

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