Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.neuroimage.2009.02.048
Title: Spatial and temporal reproducibility-based ranking of the independent components of BOLD fMRI data
Authors: Zeng, W.
Qiu, A. 
Chodkowski, B.
Pekar, J.J.
Keywords: fMRI
Independent component analysis
Maximum mean correlation
Issue Date: 15-Jul-2009
Source: Zeng, W., Qiu, A., Chodkowski, B., Pekar, J.J. (2009-07-15). Spatial and temporal reproducibility-based ranking of the independent components of BOLD fMRI data. NeuroImage 46 (4) : 1041-1054. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neuroimage.2009.02.048
Abstract: Independent component analysis (ICA) decomposes fMRI data into spatially independent maps and their corresponding time courses. However, distinguishing the neurobiologically and biophysically reasonable components from those representing noise and artifacts is not trivial. We present a simple method for the ranking of independent components, by assessing the resemblance between components estimated from all the data, and components estimated from only the odd- (or even-) numbered time points. We show that the meaningful independent components of fMRI data resemble independent components estimated from downsampled data, and thus tend to be highly ranked by the method. © 2009 Elsevier Inc. All rights reserved.
Source Title: NeuroImage
URI: http://scholarbank.nus.edu.sg/handle/10635/67281
ISSN: 10538119
DOI: 10.1016/j.neuroimage.2009.02.048
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