Math @ Duke

Publications [#287187] of Ingrid Daubechies
Papers Published
 Daubechies, I; Roussos, E; Takerkart, S; Benharrosh, M; Golden, C; D'Ardenne, K; Richter, W; Cohen, JD; Haxby, J, Independent component analysis for brain fMRI does not select for independence.,
Proceedings of the National Academy of Sciences of the United States of America, vol. 106 no. 26
(June, 2009),
pp. 1041510422 [19556548], [doi]
(last updated on 2019/08/18)
Abstract: 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.


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