文章摘要
功能性近红外光谱技术应用于孤独症领域的知识图谱可视化分析
Application of functional near-infrared spectroscopy in autism: a visualized analysis of knowledge graph
投稿时间:2024-09-05  修订日期:2024-09-05
DOI:
中文关键词: 功能性近红外光谱  孤独症  可视化分析  知识图谱
英文关键词: functional near-infrared spectroscopy  autism  visualized analysis  knowledge graph
基金项目:
作者单位邮编
牛雅楠 山东中医药大学康复医学院 250355
陈宇 山东中医药大学康复医学院 250355
薛芙霞 山东中医药大学康复医学院 
陆璐 山东中医药大学康复医学院 
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中文摘要:
      目的 对功能性近红外光谱技术(fNIRS)应用于孤独症(ASD)领域相关文献的研究现状、热点及新兴趋势进行可视化分析。 方法 检索建库至 2024 年4月 Web of Science核心合集数据库关于fNIRS应用于孤独症领域的相关文献,采用CiteSpace 6.3.R2进行可视化分析,绘制作者、机构、国家、关键词共现及突现等知识图谱。 结果 共纳入 179 篇文献。年发文量总体呈波动上升趋势,发文量最多的作者是Li Jun,发文量最多的机构是华南师范大学,发文量最多的国家是美国。热点关键词包括儿童、激活、大脑、功能连接、皮层等。关键词突现显示,该领域前期集中在典型发展和非典型发展儿童的脑功能研究。随后,进一步证实了ASD脑半球间异常的连接及协调模式。发展后期至今以进一步探索ASD儿童与典型发展儿童脑区激活和脑区功能连接的差异,融合脑机接口技术多种分类算法为主。 结论 fNIRS应用于孤独症领域相关研究的热度总体呈上升趋势。未来应加强国内外机构间的交流与合作,深入分析孤独症脑病理机制,实现孤独症的早期识别。
英文摘要:
      Objective Visual analysis of the research status, hotspots, and emerging trends of functional near-infrared spectroscopy (fNIRS) technology applied in the field of autism spectrum disorder (ASD). Methods Retrieve relevant literature on the application of fNIRS in the field of autism from the Web of Science Core Collection database until April 2024, and use CiteSpace 6.3.R2 for visual analysis to draw a knowledge graph of authors, institutions, countries, keyword co-occurrence, and emergence. Results A total of 179 articles were included. The overall annual publication volume shows a fluctuating upward trend, with Li Jun being the author with the highest publication volume, South China Normal University being the institution with the highest publication volume, and the United States being the country with the highest publication volume. Hot keywords include children, activation, brain, functional connectivity, cortex, etc. The emergence of keywords indicates that the field has initially focused on the study of brain function in children with typical and atypical development. Subsequently, the abnormal connectivity and coordination patterns between the hemispheres of ASD were further confirmed. Since the later stage of development, the main focus has been on further exploring the differences in brain activation and functional connectivity between children with ASD and those with typical development, and integrating various classification algorithms using brain computer interface technology. Conclusion The popularity of fNIRS application in autism related research is generally on the rise. In the future, it is necessary to strengthen communication and cooperation between domestic and foreign institutions, conduct in-depth analysis of the brain pathological mechanisms of autism, and achieve early identification of autism.
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