J. Ford, H. Farid, F. Makedon and L.A Flashman, "Patient Classification of fMRI Activation Maps," LNCS, vol. 2879, 2003, pp. 58-65.
M.A Lindquist, "The Statistic al Analysis of fMRI Data," Statistical Science, vol. 28, 2008, pp. 439-464.
R.A. Poldrack, J.A. Mumford and T.E. Nichols, Handbook of functional MRl data analysis. Cambridge University Press, 2011.
T.M. Mitchell, R. Hutchinson, R.S. Niculescu, F. Pereira, X. Wang and M. Just, "Classifying Instantaneous Cognitive States from fMRI data," American Medical Informatics Association Symposium, 2003, pp. 465-469.
T.M. Mitchell, R. Hutchinson, R.S. Niculescu, F. Pereira, X. Wang, M. Just and S. Newman, "Learning to decode Cognitive States from Brain Images," Machine Learning, vol. 57, 2004, pp. 145-175.
B.M. Bly, "When you have a General Linear Hammer, every fMRI time-series looks like independent identically distributed nails," Concepts and Metmds in NeuroImaging Workshop, 2001.
K.J. Friston, A.P. Holmes, K. Worsley, J.B. Poline, C.D. Frith and R.S.J. Frackowiak, "Statistical parametric maps in functional imaging: A general linear approach," Human Brain Mapping, vol. 2, 1995, pp. 189-210.
P.A.d.F.R. Hojen-Sorensen, L.K. Hansen and C.E. Rasmussen, "Bayesian modeling of fMRI time series," Proc. Conf. Advances in Neural Information Processing Systems, NIPS, 1999, pp. 754-760.
T. Jung, S. Makeig, M. McKeown, A. Bell, T. Lee and T. Sejnowski, "Imaging Brain dynamics using Independent Component Analysis," Proc.IEEE, vol. 89, 2001, pp. 1107-1122.
T. Jung, S. Makeig, M. McKeown, A. Bell, S. Kinderman and T. Sejnowski, "Analysis of fMRI data by blind separation into independent spatial components," Human Brain Mapping, vol. 6, 1998, pp. 160-188.
J.V. Haxby, M.I. Gobbini, M.L Furey, A. Ishai, J.L. Astouchen and P. Pietrini, "Distributed and overlapping representations of faces and objects in ventral temporal cortex," Science, vol. 293, 2001, pp. 2425-2430.
D.D. Cox and R.L. Savoy, " Functional magnetic resonance imaging (fMRI) "brain reading": Detecting and classifying distributed patterns of fMRI activity in human visual cortex," NeuroImage, vol. 19, 2003, pp. 261-270
M.T.T. Hoang, Y.G. Won and H.J. Yang, " Cognitive States Detection in fMARI Data Analysis using incremental PCA," ICCSA, 2007, pp. 335-341.
F. Yong, D. Shen and C. Davatzikos, "Detecting Cognitive States from fMRI Images by Machine Learning and Multivariate Classification," Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop. 2006.
J.A Etzel, Y. Gazzola and C. Keysers, "An introduction to anatomical ROI-based fMRI classification analysis," Brain Research, vol. 1282, 2009, pp. 114-125.
R.S. Bapi, V.Singh and K.P. Miyapuram, "Detection of Cognitive States from fMRI data using Machine Learning Techniques," IJCAI, 2007, pp. 587 -592 .
N. Bernard, A. Vahdat, G. Hamameh and R. Abugharbieh, " Generalized Sparse Classifiers for Decoding Cognitive States in fMRI," Proceedings of the First international conference on Machine learning in medical imaging, 2010, pp. 108- 115.
J. Rademacher, A.M. Galaburda, D.N. Kermedy, P.A. Filipek and V.S. Caviness, "Human celebral cortex: Localization, parcellation, and morphometry with magnetic resonance imaging," Journal of Cognitive Neuroscience, vol. 4, 1992, pp. 352-374.
S. Theoridis, A. Pikrakis, K. Koutroumbas and D. Cavouras, Introduction to Pattern Recognition - A MATLAB Approach, Academic Press, 2009.
P.Tan, M. Steinbach and V. Kumar, Introduction to Data Mining. Pearson Addison Wesley, 2006.