Robust data driven model order estimation for independent component analysis of FMRI data with low contrast to noise.
Independent component analysis (ICA) has been successfully utilized for analysis of functional MRI (fMRI) data for task related as well as resting state studies. Although it holds the promise of becoming an unbiased data-driven analysis technique, a few choices have to be made prior to performing IC...
Main Authors: | Waqas Majeed, Malcolm J Avison |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4005775?pdf=render |
Similar Items
-
A robust classifier to distinguish noise from fMRI independent components.
by: Vanessa Sochat, et al.
Published: (2014-01-01) -
On the definition of signal-to-noise ratio and contrast-to-noise ratio for FMRI data.
by: Marijke Welvaert, et al.
Published: (2013-01-01) -
An empirical comparison of information-theoretic criteria in estimating the number of independent components of fMRI data.
by: Mingqi Hui, et al.
Published: (2011-01-01) -
Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data
by: N. Vanello, et al.
Published: (2016-01-01) -
Parallel group independent component analysis for massive fMRI data sets.
by: Shaojie Chen, et al.
Published: (2017-01-01)