A multivariate model for comparison of two datasets and its application to FMRI analysis

Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP

Volumn , Issue , 2007, Pages 217-222

  Li, Yi Ou ^a   Adali, Tülay ^a   Calhoun, Vince D ^b,c  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^b UNIVERSITY OF NEW MEXICO   (United States)

^c YALE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN ACTIVATION; BRAIN FUNCTIONS; CANONICAL CORRELATION ANALYSIS; DATA-SETS; DISTINCT FEATURES; FMRI-ANALYSIS; FUNCTIONAL MAGNETIC RESONANCE-IMAGING; IEEE SIGNAL PROCESSING SOCIETY; INDEPENDENT COMPONENTS; INFORMATION-THEORETIC CRITERION; MACHINE-LEARNING; MULTI-DIMENSIONAL DATASETS; SIMULATED DRIVING; STRUCTURED APPROACH;

ARTIFICIAL INTELLIGENCE; IMAGING TECHNIQUES; INFORMATION THEORY; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; RESONANCE; ROBOT LEARNING; SIGNAL PROCESSING;

INDEPENDENT COMPONENT ANALYSIS;

EID: 48149102534     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2007.4414309     Document Type: Conference Paper

References (12)

1. V. D. Calhoun, T. Adali, J. J. Pekar, and G. D. Pearlson, "A method for making group inferences from functional MRI data using independent component analysis," Human Brain Mapping, vol. 14, pp. 140-151, 2001.
2. A. C. Rencher, Methods of Multivariate Analysis (Second Edition), Wiley-Interscience, 2002.
3. H. Akaike, "Information theory and an extension of the maximum likelihood principle," inProc. 2nd International Symposium on Information Theory 1973, Tsahkadsor, Armenian SSR; Hungary.
4. J. Rissanen, "Modeling by the shortest data description," Automatica, vol. 14, pp. 465-471, 1978.
5. G. Schwartz, "Estimating the dimension of a model," The Annals of Statistics, vol. 6, pp. 461-464, 1978.
6. T. W. Anderson, "Asymptotic theory for principal component analysis," The Annals of Mathematical Statistics, vol. 34, 1963.
7. Y.-O. Li, T. Adali, and V. D. Calhoun, "Estimating the number of independent components in fMRI data," In press, Human Brain Mapping, 2007.
8. V. D. Calhoun, J. J. Pekar, V. B. McGinty, T. Adali, T. D. Watson, and G. D. Pearlson, "Different activation dynamics in multiple neural systems during simulated driving," Human Brain Mapping, vol. 16, pp. 158-167, 2002.
9. M. Wax and T. Kailath, "Detection of signals by information theoretic criteria," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 33, pp. 387-392, 1985.
10. A. S. Lukic, M. N. Wemick, L. K. Hansen, J. Anderson, and S. Strother, "A spatially robust ICA algorithm for multiple fMRI data sets," in Proc. IEEE International Symposium on Biomedical Imaging (ISBI) 2002, Arlington, VA.
11. S. Akaho, Y. Kiuchi, and S. Umeyama, "MICA: multidimensional independent component analysis," in Proc. IJCNN 1999, Washington DC.
12. A. Hyvarinen and P. Hoyer, "Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces," Neural Computation, vol. 12, pp. 1705-20, 2000.