Independent component analysis for brain fMRI does not select for independence.
Publication
, Journal Article
Daubechies, I; Roussos, E; Takerkart, S; Benharrosh, M; Golden, C; D'Ardenne, K; Richter, W; Cohen, JD; Haxby, J
Published in: Proceedings of the National Academy of Sciences of the United States of America
June 2009
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.
Duke Scholars
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Published In
Proceedings of the National Academy of Sciences of the United States of America
DOI
EISSN
1091-6490
ISSN
0027-8424
Publication Date
June 2009
Volume
106
Issue
26
Start / End Page
10415 / 10422
Related Subject Headings
- Signal Processing, Computer-Assisted
- Reproducibility of Results
- Radiography
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Image Interpretation, Computer-Assisted
- Humans
- Computer Simulation
- Brain Mapping
- Brain
Citation
APA
Chicago
ICMJE
MLA
NLM
Daubechies, I., Roussos, E., Takerkart, S., Benharrosh, M., Golden, C., D’Ardenne, K., … Haxby, J. (2009). Independent component analysis for brain fMRI does not select for independence. Proceedings of the National Academy of Sciences of the United States of America, 106(26), 10415–10422. https://doi.org/10.1073/pnas.0903525106
Daubechies, I., E. Roussos, S. Takerkart, M. Benharrosh, C. Golden, K. D’Ardenne, W. Richter, J. D. Cohen, and J. Haxby. “Independent component analysis for brain fMRI does not select for independence.” Proceedings of the National Academy of Sciences of the United States of America 106, no. 26 (June 2009): 10415–22. https://doi.org/10.1073/pnas.0903525106.
Daubechies I, Roussos E, Takerkart S, Benharrosh M, Golden C, D’Ardenne K, et al. Independent component analysis for brain fMRI does not select for independence. Proceedings of the National Academy of Sciences of the United States of America. 2009 Jun;106(26):10415–22.
Daubechies, I., et al. “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. 10415–22. Epmc, doi:10.1073/pnas.0903525106.
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. 2009 Jun;106(26):10415–10422.
Published In
Proceedings of the National Academy of Sciences of the United States of America
DOI
EISSN
1091-6490
ISSN
0027-8424
Publication Date
June 2009
Volume
106
Issue
26
Start / End Page
10415 / 10422
Related Subject Headings
- Signal Processing, Computer-Assisted
- Reproducibility of Results
- Radiography
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Image Interpretation, Computer-Assisted
- Humans
- Computer Simulation
- Brain Mapping
- Brain