Independent component analysis for brain fMRI does not select for independence
- 30 June 2009
- journal article
- research article
- Published by Proceedings of the National Academy of Sciences in Proceedings of the National Academy of Sciences of the United States of America
- Vol. 106 (26), 10415-10422
- https://doi.org/10.1073/pnas.0903525106
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.Keywords
This publication has 23 references indexed in Scilit:
- Beyond sparsity: Recovering structured representations by ${\ell}^1$ minimization and greedy algorithmsAdvances in Computational Mathematics, 2006
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solutionCommunications on Pure and Applied Mathematics, 2006
- For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solutionCommunications on Pure and Applied Mathematics, 2006
- The chronoarchitecture of the human brain—natural viewing conditions reveal a time-based anatomy of the brainNeuroImage, 2004
- Probabilistic Independent Component Analysis for Functional Magnetic Resonance ImagingIEEE Transactions on Medical Imaging, 2004
- Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal CortexScience, 2001
- Can recent innovations in harmonic analysis `explain' key findings in natural image statistics?Network: Computation in Neural Systems, 2001
- Fast and robust fixed-point algorithms for independent component analysisIEEE Transactions on Neural Networks, 1999
- An Information-Maximization Approach to Blind Separation and Blind DeconvolutionNeural Computation, 1995
- Analysis of fMRI Time-Series Revisited—AgainNeuroImage, 1995