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Functional brain network mapping with dual regression

Functional brain network mapping with dual regression
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摘要 Functional magnetic resonance imaging(fMRI)is an in-vivo non-invasive technique for measuring brain activity with excellent spatial and good temporal resolution.Without performing explicit tasks,resting-state fMRI(rfMRI)is widely used to map the functional connectivity network(FCN),which refers to a large-scale network of interdependent or functionally connected brain regions and it could be detected by using different algorithms(Zuo and Xing, 2014).ciation CAS (2016084), Guangxi Bagui Scholarship, the Natural Science Foundation of China (81471740, 81220108014), the Major Project of National Social Science Foundation of China (14ZDB161), Beijing Municipal Science and Tech Commission (Z161100002616023, Z161100000216152) and the National R&D Infrastructure and Facility Development Program "Fundamental Science Data Sharing Platform" (DKA2017-12-02-21). Functional magnetic resonance imaging(fMRI)is an in-vivo non-invasive technique for measuring brain activity with excellent spatial and good temporal resolution.Without performing explicit tasks,resting-state fMRI(rfMRI)is widely used to map the functional connectivity network(FCN),which refers to a large-scale network of interdependent or functionally connected brain regions and it could be detected by using different algorithms(Zuo
出处 《Science China(Life Sciences)》 SCIE CAS CSCD 2017年第12期1450-1452,共3页 中国科学(生命科学英文版)
基金 supported by the National Basic Research Program(2015CB351702) the Youth Innovation Promotion Association CAS(2016084) Guangxi Bagui Scholarship,the Natural Science Foundation of China(81471740,81220108014) the Major Project of National Social Science Foundation of China(14ZDB161) Beijing Municipal Science and Tech Commission(Z161100002616023,Z161100000216152) the National R&D Infrastructure and Facility Development Program“Fundamental Science Data Sharing Platform”(DKA2017-12-02-21)
关键词 Functional brain network mapping dual regression DMN PMN ICA
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