Literature DB >> 19556548

Independent component analysis for brain fMRI does not select for independence.

I Daubechies1, E Roussos, S Takerkart, M Benharrosh, C Golden, K D'Ardenne, W Richter, J D Cohen, J Haxby.   

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.

Mesh：

Year:  2009        PMID： 19556548      PMCID： PMC2705604          DOI： 10.1073/pnas.0903525106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN： 0027-8424            Impact factor:   11.205


  13 in total

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Authors:  V D Calhoun; T Adali; G D Pearlson; J J Pekar
Journal:  Hum Brain Mapp       Date:  2001-05       Impact factor: 5.038

2.  Can recent innovations in harmonic analysis 'explain' key findings in natural image statistics?

Authors:  D L Donoho; A G Flesia
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3.  Generalizable patterns in neuroimaging: how many principal components?

Authors:  L K Hansen; J Larsen; F A Nielsen; S C Strother; E Rostrup; R Savoy; N Lange; J Sidtis; C Svarer; O B Paulson
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4.  Latency (in)sensitive ICA. Group independent component analysis of fMRI data in the temporal frequency domain.

Authors:  V D Calhoun; T Adali; J J Pekar; G D Pearlson
Journal:  Neuroimage       Date:  2003-11       Impact factor: 6.556

5.  Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

Authors:  Fabrizio Esposito; Elia Formisano; Erich Seifritz; Rainer Goebel; Renato Morrone; Gioacchino Tedeschi; Francesco Di Salle
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6.  The chronoarchitecture of the human brain--natural viewing conditions reveal a time-based anatomy of the brain.

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Review 7.  Advances in functional and structural MR image analysis and implementation as FSL.

Authors:  Stephen M Smith; Mark Jenkinson; Mark W Woolrich; Christian F Beckmann; Timothy E J Behrens; Heidi Johansen-Berg; Peter R Bannister; Marilena De Luca; Ivana Drobnjak; David E Flitney; Rami K Niazy; James Saunders; John Vickers; Yongyue Zhang; Nicola De Stefano; J Michael Brady; Paul M Matthews
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8.  Analysis of fMRI data by blind separation into independent spatial components.

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9.  An information-maximization approach to blind separation and blind deconvolution.

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10.  Distributed and overlapping representations of faces and objects in ventral temporal cortex.

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  61 in total

1.  A novel group ICA approach based on multi-scale individual component clustering. Application to a large sample of fMRI data.

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2.  Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

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Journal:  Brain Connect       Date:  2012-03-23

Review 3.  Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity.

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4.  Dynamic Multiscale Modes of Resting State Brain Activity Detected by Entropy Field Decomposition.

Authors:  Lawrence R Frank; Vitaly L Galinsky
Journal:  Neural Comput       Date:  2016-07-08       Impact factor: 2.026

Review 5.  Machine learning in resting-state fMRI analysis.

Authors:  Meenakshi Khosla; Keith Jamison; Gia H Ngo; Amy Kuceyeski; Mert R Sabuncu
Journal:  Magn Reson Imaging       Date:  2019-06-05       Impact factor: 2.546

6.  Making group inferences using sparse representation of resting-state functional mRI data with application to sleep deprivation.

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Journal:  Hum Brain Mapp       Date:  2017-06-19       Impact factor: 5.038

7.  Connectivity trajectory across lifespan differentiates the precuneus from the default network.

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8.  Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

Authors:  Aristeidis Sotiras; Susan M Resnick; Christos Davatzikos
Journal:  Neuroimage       Date:  2014-12-12       Impact factor: 6.556

9.  Unsupervised spatiotemporal analysis of fMRI data using graph-based visualizations of self-organizing maps.

Authors:  Santosh B Katwal; John C Gore; Rene Marois; Baxter P Rogers
Journal:  IEEE Trans Biomed Eng       Date:  2013-04-16       Impact factor: 4.538

10.  On consciousness, resting state fMRI, and neurodynamics.

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Journal:  Nonlinear Biomed Phys       Date:  2010-06-03
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