Decomposition of individual-specific and individual-shared components from resting-state functional connectivity using a multi-task machine learning method

Decomposition of individual-specific and individual-shared components from resting-state functional connectivity using a multi-task machine learning method

Resting-state functional connectivity (RSFC) can be used for mapping large-scale human brain networks during rest. There is considerable interest in distinguishing the individual-shared and individual-specific components in RSFC for the better identification of individuals and prediction of behavior...

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Bibliographic Details
Main Authors: Xuetong Wang, Qiongling Li, Yan Zhao, Yirong He, Baoqiang Ma, Zhenrong Fu, Shuyu Li
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:NeuroImage
Subjects:
RSFC
Individual difference
Individual-specific connectivity
Predict behavioral scores
Fingerprint analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811921005292

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http://www.sciencedirect.com/science/article/pii/S1053811921005292

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