20世纪中叶,学科互涉现象开始在学术界和教育界普及,并一举成为现代学科发展与知识创新的全新模式。学科互涉是在经典学科理论框架之隐忧日益显露的时候出现的,它并非呼吁取消学科分类,而是为了在学科交汇的中间地带谋求学科的合法性存...20世纪中叶,学科互涉现象开始在学术界和教育界普及,并一举成为现代学科发展与知识创新的全新模式。学科互涉是在经典学科理论框架之隐忧日益显露的时候出现的,它并非呼吁取消学科分类,而是为了在学科交汇的中间地带谋求学科的合法性存在。鉴于此,诞生于人文社会科学与自然科学十字路口的传播学,借助学科互涉概念推动学科建设与发展,具有天然的优势。本文以Web of Science数据库1937—2020年收录的传播学学科互涉论文为研究样本,基于学科共现分析方法对传播学领域的学科互涉网络结构及其演化历程进行了定量分析。结果表明,传播学的学科互涉程度越发深入,学科互涉群体间的关系也愈加稳固。在竞争日趋激烈的社会科学领域,传播学想要实现重大学术突破,借助学科互涉框架或许是最佳策略,因为传播学的优势在于它本就是一个多学科互涉空间。展开更多
分析老年福祉技术研究中的学科交叉现象,为我国老年福址技术创新研究提供参考。借助社会网络分析方法,对Web of Science收录的1945—2018年老年福祉技术研究文献数据进行学科交叉主题与特征分析。研究发现,老年福祉技术研究领域存在多...分析老年福祉技术研究中的学科交叉现象,为我国老年福址技术创新研究提供参考。借助社会网络分析方法,对Web of Science收录的1945—2018年老年福祉技术研究文献数据进行学科交叉主题与特征分析。研究发现,老年福祉技术研究领域存在多学科交叉特点。临床医学、公共卫生与预防医学、计算机科学与技术、社会学等学科在老年福祉技术研究中占据重要地位,是学科间联系的主要媒介,其中临床医学交叉程度最高。阿尔茨海默病和老年辅助技术是老年福祉技术研究的关键。展开更多
Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific dis...Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific discovery task,and has been demonstrated to possess the priming effect,which is attributed to the regularity identification and its subsequent extrapolation.In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study,the number magnitude and arithmetic operation involved in number series completion tasks are further restricted.Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected.Then,a factorial design (the priming effect:prime vs.target;the period length:simple vs.complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery.The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task.The priming effect in the left DLPFC is more significant for the simple task than for the complex task,while the priming effect in the left APFC is more significant for the complex task than for the simple task.The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery.The left DLPFC (BA 46) may play a crucial role in rule identification,while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation.展开更多
Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an effi...Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.展开更多
文摘20世纪中叶,学科互涉现象开始在学术界和教育界普及,并一举成为现代学科发展与知识创新的全新模式。学科互涉是在经典学科理论框架之隐忧日益显露的时候出现的,它并非呼吁取消学科分类,而是为了在学科交汇的中间地带谋求学科的合法性存在。鉴于此,诞生于人文社会科学与自然科学十字路口的传播学,借助学科互涉概念推动学科建设与发展,具有天然的优势。本文以Web of Science数据库1937—2020年收录的传播学学科互涉论文为研究样本,基于学科共现分析方法对传播学领域的学科互涉网络结构及其演化历程进行了定量分析。结果表明,传播学的学科互涉程度越发深入,学科互涉群体间的关系也愈加稳固。在竞争日趋激烈的社会科学领域,传播学想要实现重大学术突破,借助学科互涉框架或许是最佳策略,因为传播学的优势在于它本就是一个多学科互涉空间。
文摘分析老年福祉技术研究中的学科交叉现象,为我国老年福址技术创新研究提供参考。借助社会网络分析方法,对Web of Science收录的1945—2018年老年福祉技术研究文献数据进行学科交叉主题与特征分析。研究发现,老年福祉技术研究领域存在多学科交叉特点。临床医学、公共卫生与预防医学、计算机科学与技术、社会学等学科在老年福祉技术研究中占据重要地位,是学科间联系的主要媒介,其中临床医学交叉程度最高。阿尔茨海默病和老年辅助技术是老年福祉技术研究的关键。
基金supported by the National Natural Science Foundation of China (Grant Nos.60775039 and 60875075)supported by the Grant-in-aid for Scientific Research (Grant No.18300053) from the Japanese Society for the Promotion of Science+2 种基金Support Center for Advanced Telecommunications Technology Research,Foundationthe Open Foundation of Key Laboratory of Multimedia and Intelligent Software Technology (Beijing University of Technology) Beijingthe Doctoral Research Fund of Beijing University of Technology (Grant No.00243)
文摘Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific discovery task,and has been demonstrated to possess the priming effect,which is attributed to the regularity identification and its subsequent extrapolation.In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study,the number magnitude and arithmetic operation involved in number series completion tasks are further restricted.Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected.Then,a factorial design (the priming effect:prime vs.target;the period length:simple vs.complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery.The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task.The priming effect in the left DLPFC is more significant for the simple task than for the complex task,while the priming effect in the left APFC is more significant for the complex task than for the simple task.The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery.The left DLPFC (BA 46) may play a crucial role in rule identification,while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation.
基金partially supported by the National Basic Research Program (973) of China (2015CB351702)the National Natural Science Foundation of China (81220108014, 81471740, 81201153, 81171409, and 81270023)+4 种基金the Key Research Program (KSZD-EW-TZ-002)the Hundred Talents Program of the Chinese Academy of SciencesDr. Xiu-Xia Xing acknowledges the Beijing Higher Education Young Elite Teacher Project (No. YETP1593)Dr. Zhi Yang acknowledges the Foundation of Beijing Key Laboratory of Mental Disorders (2014JSJB03)the Outstanding Young Researcher Award from Institute of Psychology, Chinese Academy of Sciences (Y4CX062008)
文摘Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.
