中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Functional Connectivity among Brain Networks in Continuous Feedback of FInger Force

文献类型:期刊论文

作者Hang Zhang; Han Zhang; Yufeng Zang
刊名Neuroscience
出版日期2015
英文摘要Abstract—Motor feedback usually engages distinct sensory and cognitive processes based on different feedback conditions,e.g., the real and sham feedbacks. It was thought that these processes may rely on the functional connectivity among the brain networks. However, it remains unclear whether there is a difference in the network connectivity between the two feedback conditions. To address this issue,we carried out a functional magnetic resonance imaging (fMRI) study by employing a new paradigm, i.e., continuous feedback (8 min) of finger force. Using independent componentanalysis and functional connectivity analysis, we found that as compared with the sham feedback, the real feedback recruited stronger negative connectivity between the executive network (EN) and the posterior default mode network (pDMN). More intriguingly, the left frontal parietal network (lFPN) exhibits positive connectivity with the pDMN in the real feedback while in the sham feedback, the lFPN shows connectivity with the EN. These results suggest that the connectivity among EN, pDMN, lFPN could differ depending on the real and sham feedbacks, and the lFPN may balance the competition between the pDMN and EN, thus supporting the sensory and cognitive processes of the motor feedback.
收录类别SCI
原文出处http://www.ncbi.nlm.nih.gov/pubmed/25595972
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/7133]  
专题深圳先进技术研究院_医工所
作者单位Neuroscience
推荐引用方式
GB/T 7714
Hang Zhang,Han Zhang,Yufeng Zang. Functional Connectivity among Brain Networks in Continuous Feedback of FInger Force[J]. Neuroscience,2015.
APA Hang Zhang,Han Zhang,&Yufeng Zang.(2015).Functional Connectivity among Brain Networks in Continuous Feedback of FInger Force.Neuroscience.
MLA Hang Zhang,et al."Functional Connectivity among Brain Networks in Continuous Feedback of FInger Force".Neuroscience (2015).

入库方式: OAI收割

来源:深圳先进技术研究院

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