Independent component analysis for brain fMRI does not select for independence
Independent component analysis for brain fMRI does not select for independence
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DOI：
10.1073/pnas.0903525106
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发表时间：
2009-06-30
影响因子：
11.1
通讯作者：
Haxby, J.
中科院分区：
文献类型：
--
作者：
Daubechies, I.;Roussos, E.;Haxby, J.
InfoMax和FastICA是最常用的独立成分分析算法，显然对大脑fMRI最有效。我们表明，这是链接到他们的能力，有效地处理稀疏的组件，而不是独立的组件。因此，更好的脑功能磁共振成像分析工具的数学设计应该强调其他数学特征，而不是独立性。
InfoMax and FastICA are the independent component analysis algorithms most used and apparently most effective for brain fMRI. We show that this is linked to their ability to handle effectively sparse components rather than independent components as such. The mathematical design of better analysis tools for brain fMRI should thus emphasize other mathematical characteristics than independence.