当前位置: X-MOL 学术Brain Connect. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales
Brain Connectivity ( IF 3.4 ) Pub Date : 2022-09-15 , DOI: 10.1089/brain.2021.0079
Xing Meng 1 , Armin Iraji 1 , Zening Fu 1 , Peter Kochunov 2 , Aysenil Belger 3 , Judith Ford 4, 5 , Sara McEwen 6 , Daniel H Mathalon 4, 5 , Bryon A Mueller 7 , Godfrey Pearlson 8 , Steven G Potkin 9 , Adrian Preda 9 , Jessica Turner 1, 10 , Theo van Erp 11 , Jing Sui 1, 12, 13 , Vince D Calhoun 1, 10
Affiliation  

Background: While functional connectivity is widely studied, there has been little work studying functional connectivity at different spatial scales. Likewise, the relationship of functional connectivity between spatial scales is unknown.

中文翻译:

多模型阶独立分量分析:一种用于评估多个空间尺度内和之间的大脑功能网络连接性的数据驱动方法

背景:虽然功能连接性得到了广泛的研究,但研究不同空间尺度的功能连接性的工作却很少。同样,空间尺度之间的功能连接关系也是未知的。
更新日期:2022-09-16
down
wechat
bug