Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis
Background: In the pursuit of causal insights into neural circuit functionality, various interventions, including electrical, genetic, and pharmacological approaches, have been applied over recent decades. This study employs a comprehensive bibliometric perspective to explore the field of neural cir...
| Published in: | Heliyon |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024006807 |
| _version_ | 1850347766809624576 |
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| author | Yuan Liu Wei Lin Jie Liu Haixia Zhu |
| author_facet | Yuan Liu Wei Lin Jie Liu Haixia Zhu |
| author_sort | Yuan Liu |
| collection | DOAJ |
| container_title | Heliyon |
| description | Background: In the pursuit of causal insights into neural circuit functionality, various interventions, including electrical, genetic, and pharmacological approaches, have been applied over recent decades. This study employs a comprehensive bibliometric perspective to explore the field of neural circuits. Methods: Reviews and articles on neural circuits were obtained from the Web of Science Core Collection (WOSCC) database on Apr. 12, 2023. In this article, co-authorship analysis, co-occurrence analysis, citation analysis, bibliographic analysis, and co-citation analysis were used to clarify the authors, journals, institutions, countries, topics, and internal associations between them. Results: More than 2000 organizations from 52 different countries published 3975 articles in the field of “neural circuit” were used to analysis. Luo liqun emerged as the most prolific author, and Deisseroth Karl garners the highest co-citations (3643). The Journal of Neuroscience leaded in publications, while Nature toped in citations. Chinese Academy of Science recorded the highest article count institutionally, with Stanford University ranking first with 14,350 citations. Since 2020, neurodynamic, anxiety-related mechanisms, and GABAergic neurons have gained prominence, shaping the trajectory of neural circuitry research. Conclusions: Our investigation has discerned a paradigmatic reorientation towards neurodynamic processes, anxiety-related mechanisms, and GABAergic neurons within the domain of neural circuit research. This identification intimates a prospective trajectory for the field. In the future, it is imperative for research endeavors to accord priority to the translational application of these discernments, with the aim of materializing tangible clinical solutions. |
| format | Article |
| id | doaj-art-7d985ff0dfa54553bf5d396cb5f4a2ed |
| institution | Directory of Open Access Journals |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| spelling | doaj-art-7d985ff0dfa54553bf5d396cb5f4a2ed2025-08-19T23:11:23ZengElsevierHeliyon2405-84402024-01-01102e2464910.1016/j.heliyon.2024.e24649Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysisYuan Liu0Wei Lin1Jie Liu2Haixia Zhu3Cancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, ChinaJiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China; Department of Pediatrics, The First Affiliated Hospital of Fujian Medical University, Fujian, ChinaDepartment of Orthopedics, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, ChinaCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China; Corresponding author.Background: In the pursuit of causal insights into neural circuit functionality, various interventions, including electrical, genetic, and pharmacological approaches, have been applied over recent decades. This study employs a comprehensive bibliometric perspective to explore the field of neural circuits. Methods: Reviews and articles on neural circuits were obtained from the Web of Science Core Collection (WOSCC) database on Apr. 12, 2023. In this article, co-authorship analysis, co-occurrence analysis, citation analysis, bibliographic analysis, and co-citation analysis were used to clarify the authors, journals, institutions, countries, topics, and internal associations between them. Results: More than 2000 organizations from 52 different countries published 3975 articles in the field of “neural circuit” were used to analysis. Luo liqun emerged as the most prolific author, and Deisseroth Karl garners the highest co-citations (3643). The Journal of Neuroscience leaded in publications, while Nature toped in citations. Chinese Academy of Science recorded the highest article count institutionally, with Stanford University ranking first with 14,350 citations. Since 2020, neurodynamic, anxiety-related mechanisms, and GABAergic neurons have gained prominence, shaping the trajectory of neural circuitry research. Conclusions: Our investigation has discerned a paradigmatic reorientation towards neurodynamic processes, anxiety-related mechanisms, and GABAergic neurons within the domain of neural circuit research. This identification intimates a prospective trajectory for the field. In the future, it is imperative for research endeavors to accord priority to the translational application of these discernments, with the aim of materializing tangible clinical solutions.http://www.sciencedirect.com/science/article/pii/S2405844024006807Neural circuitBibliometric analysisTopic trendsVisualizationNeurodynamic |
| spellingShingle | Yuan Liu Wei Lin Jie Liu Haixia Zhu Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis Neural circuit Bibliometric analysis Topic trends Visualization Neurodynamic |
| title | Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis |
| title_full | Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis |
| title_fullStr | Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis |
| title_full_unstemmed | Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis |
| title_short | Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis |
| title_sort | structural and temporal dynamics analysis of neural circuit from 2002 to 2022 a bibliometric analysis |
| topic | Neural circuit Bibliometric analysis Topic trends Visualization Neurodynamic |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024006807 |
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