ICA of fMRI data: Performance of three ICA algorithms and the importance of taking correlation information into account

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2011, Pages 1573-1576

  Du, Wei ^a   Li, Hualiang ^a   Li, Xi Lin ^a   Calhoun, Vince D ^b   Adali, Tulay ^a  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^b UNIVERSITY OF NEW MEXICO   (United States)

Author keywords

AOD task; fMRI; ICA; independent component analysis

Indexed keywords

AOD TASK; BRAIN FUNCTIONS; DENSITY MODELS; ENTROPY BOUND; FMRI; FMRI DATA; FMRI-ANALYSIS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; ICA ALGORITHMS; INDEPENDENT COMPONENTS; INFOMAX; ODDBALL TASK; SOURCE DISTRIBUTION; TIME COURSE;

BLIND SOURCE SEPARATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; RESONANCE;

INDEPENDENT COMPONENT ANALYSIS;

EID: 80055042987     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2011.5872702     Document Type: Conference Paper

References (15)

1. M.J. Mckeown, S. Makeig, G.G. Brown, et al., "Analysis of fMRI by blind separation into independent spatial components," Human Brain Mapping, vol. 6, pp. 168-188, 1998.
2. N. Correa, T. Adali and V. D. Calhoun, "Performance of blind source separation algorithms for fMRI analysis using a group ICA method," Magnetic Resonance Imaging, vol. 25, no. 5, pp. 684-694, 2006.
3. A.J. Bell and T.J. Sejnowski, "An information-maximization approach to blind separation and blind deconvolution," Neural Computation, vol. 7, no. 6, pp. 1129-1159, 1995.
4. X.-L. Li and T. Adali, "Independent component analysis by entropy bound minimization," IEEE Trans. Signal Process., vol. 58, pp. 5151-5164, 2010.
5. X.-L. Li and T. Adali, "Blind spatiotemporal separation of second and/or higher-oreder correlated sources by entropy rate minimization," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Dallas, Tx, March 2010.
6. Y.-O. Li, T. Adali, and V. D. Calhoun, "Estimating the number of independent components for fMRI data," Human Brain Mapping, vol. 28, pp. 1251-66, 2007.
7. M.E. Raichle, A.M. MacLeod, A.Z. Snyder, et al., "A default mode of brain function," Proc Natl Acad Sci USA, vol. 98, pp. 676-682, 2001.
8. V.D. Calhoun, P.K. Maciejewski, G. D. Pearlson, et al., "Temporal Lobe and "Default" Hemodynamic Brain Modes Discriminate Between Schizophrenia and Bipolar Disorder," Human Brain Mapping, vol. 29, pp. 1265-1275, 2008.
9. V.D. Calhoun, T. Adali, G. D. Pearlson, et al., "A method for making group inferences from functional MRI data using independent component analysis," Human Brain Mapping, vol. 14, pp. 140-151, 2001.
10. GIFT, http://icatb.sourceforge.net
11. K.A. Kiehl, M.C. Stevens, K.R. Laurens, et al., "An adaptive reflexive processing model of neurocognitive function: supporting evidence from a large scale (n= 100) fMRI study of an auditory oddball task," NeuroIamge, vol. 25, no. 3, pp. 899-915, 2005.
12. SPM5, http://www.fil.ion.ucl.ac.uk/spm/software/spm5/
13. C.F. Beckmann, M. DeLuca, J.T. Devlin, et al., "Investigations into resting-state connectivity using Independent Component Analysis," Philos Trans R Soc Lond B Biol Sci, vol. 360, pp. 1001-1013, 2005.
14. J. Himberg, and A. Hyvärinen. "ICASSO: software for investigating the reliability of ICA estimates by clustering and visualization," Proceedings of IEEE workshop on Neural Networks for Signal Process (NNSP), Toulouse, France, 2003.
15. J. Maldjian. P. Laurienti, R. Kraft, et al., "An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data set," NeuroImage, vol. 19, pp. 1233-1239, July 2003.