Memory efficient PCA methods for large group ICA
Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimension...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2016-02-01
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Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00017/full |