Non-linear ICA Analysis of Resting-State fMRI in Mild Cognitive Impairment

Non-linear ICA Analysis of Resting-State fMRI in Mild Cognitive Impairment

Compared to linear independent component analysis (ICA), non-linear ICA is more suitable for the decomposition of mixed components. Existing studies of functional magnetic resonance imaging (fMRI) data by using linear ICA assume that the brain's mixed signals, which are caused by the activity o...

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Bibliographic Details
Main Authors: Xia-an Bi, Qi Sun, Junxia Zhao, Qian Xu, Liqin Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Neuroscience
Subjects:
resting state networks
mild cognitive impairment
functional magnetic resonance imaging
functional connectivity
post-non-linear independent component analysis
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2018.00413/full

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https://www.frontiersin.org/article/10.3389/fnins.2018.00413/full

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