Independent component analysis for brain FMRI does indeed select for maximal independence.
Independent component analysis for brain FMRI does indeed select for maximal independence.
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DOI：
10.1371/journal.pone.0073309
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Adalı T
中科院分区：
文献类型：
--
作者：
Calhoun VD;Potluru VK;Phlypo R;Silva RF;Pearlmutter BA;Caprihan A;Plis SM;Adalı T
A recent paper by Daubechies et al. claims that two independent component analysis (ICA) algorithms, Infomax and FastICA, which are widely used for functional magnetic resonance imaging (fMRI) analysis, select for sparsity rather than independence. The argument was supported by a series of experiments on synthetic data. We show that these experiments fall short of proving this claim and that the ICA algorithms are indeed doing what they are designed to do: identify maximally independent sources.
