H. Abdulrahman and R. N. Henson, Effect of trial-to-trial variability on optimal event-related fMRI design: Implications for Beta-series correlation and multi-voxel pattern analysis, NeuroImage, vol.125, pp.756-766, 2016.
DOI : 10.1016/j.neuroimage.2015.11.009

S. Badillo, T. Vincent, and P. Ciuciu, Grouplevel impacts of within-and between-subject hemodynamic variability in fmri, NeuroImage, vol.530, issue.82, pp.433-448, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00854481

L. Baldassarre, J. Mourao-miranda, and M. Pontil, Structured Sparsity Models for Brain Decoding from fMRI Data, 2012 Second International Workshop on Pattern Recognition in NeuroImaging, pp.5-8
DOI : 10.1109/PRNI.2012.31

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

P. Ciuciu, J. Poline, G. Marrelec, J. Idier, C. Pallier et al., Unsupervised robust nonparametric estimation of the hemodynamic response function for any fmri experiment, IEEE Transactions on Medical Imaging, vol.22, issue.10, pp.1235-1251, 2003.
DOI : 10.1109/TMI.2003.817759

URL : https://hal.archives-ouvertes.fr/cea-00333694

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, issue.2, pp.261-270, 2003.
DOI : 10.1016/S1053-8119(03)00049-1

K. J. Friston, A. P. Holmes, K. J. Worsley, J. Poline, C. D. Frith et al., Statistical parametric maps in functional imaging: A general linear approach, Human Brain Mapping, vol.26, issue.4, pp.189-210, 1994.
DOI : 10.2307/1427576

K. J. Friston, P. Jezzard, and R. Turner, Analysis of functional MRI time-series, Human Brain Mapping, vol.12, issue.2, pp.153-171, 1994.
DOI : 10.1038/jcbfm.1992.127

B. Gauthier, E. Eger, G. Hesselmann, A. Giraud, A. Kleinschmidt et al., Temporal tun- 575 ing properties along the human ventral visual stream Identifying predictive regions from fmri with tv-l1 prior, Proceedings of the 2013 International Workshop on Pattern Recognition in Neuroimaging, PRNI '13, pp.14433-14441, 2012.
DOI : 10.1523/jneurosci.2467-12.2012

URL : https://archive-ouverte.unige.ch/unige:26288/ATTACHMENT01

L. Grosenick, B. Klingenberg, K. Katovich, 5. B. Knutson, J. E. Taylor et al., Interpretable whole-brain prediction analysis with GraphNet, NeuroImage, vol.72, issue.293, pp.304-3212425, 2001.
DOI : 10.1016/j.neuroimage.2012.12.062

URL : http://doi.org/10.1016/j.neuroimage.2012.12.062

J. Haynes and G. Rees, Decoding mental states from brain activity in humans, Nature Reviews Neuroscience, vol.16, issue.7, pp.523-534, 2006.
DOI : 10.1520/JFS14925J

K. Jimura, F. Cazalis, E. R. Stover, and R. A. Poldrack, The neural basis of task switching changes with skill acquisition, Frontiers in Human Neuroscience, vol.26, issue.e47
DOI : 10.1523/JNEUROSCI.3109-05.2006

F. I. Karahanolu, C. Caballero-gaudes, F. Lazeyras, and D. Van-de-ville, Total activation: fMRI deconvolution through spatio-temporal regularization, NeuroImage, vol.73, pp.121-615, 2013.
DOI : 10.1016/j.neuroimage.2013.01.067

S. Lazebnik, C. Schmid, and J. Ponce, A sparse texture representation using local affine regions IEEE transactions on pattern analysis 620 and machine intelligence, pp.1265-1278, 2005.
DOI : 10.1109/tpami.2005.151

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. Mouro-miranda, K. J. Friston, and M. Brammer, Dynamic discrimination analysis: A spatial???temporal SVM, NeuroImage, vol.36, issue.1, pp.88-99, 2007.
DOI : 10.1016/j.neuroimage.2007.02.020

J. A. Mumford, B. O. Turner, F. G. Ashby, and R. A. Poldrack, Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses, NeuroImage, vol.59, issue.3, pp.2636-2643
DOI : 10.1016/j.neuroimage.2011.08.076

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3251697

K. A. Norman, S. M. Polyn, G. J. Detre, and 6. J. Haxby, Beyond mind-reading: multi-voxel pattern analysis of fMRI data, Trends in Cognitive Sciences, vol.10, issue.9, 2006.
DOI : 10.1016/j.tics.2006.07.005

F. Pedregosa, M. Eickenberg, P. Ciuciu, B. Thirion, and A. Gramfort, Data-driven HRF estimation for encoding and decoding models, NeuroImage, vol.104, pp.209-220, 2015.
DOI : 10.1016/j.neuroimage.2014.09.060

URL : https://hal.archives-ouvertes.fr/hal-00952554

S. Smith, C. Jenkinson, K. Beckmann, M. Miller, and . Woolrich, Meaningful design and contrast estimability in FMRI, NeuroImage, vol.34, issue.1, pp.127-136, 2007.
DOI : 10.1016/j.neuroimage.2006.09.019

B. O. Turner, J. A. Mumford, R. A. Poldrack, and F. G. Ashby, Spatiotemporal activity estimation for multivoxel pattern analysis with rapid event-related designs, NeuroImage, vol.62, issue.3, pp.1429-1438
DOI : 10.1016/j.neuroimage.2012.05.057

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3408801

G. Varoquaux and B. Thirion, How machine 655 learning is shaping cognitive neuroimaging, 2014.
DOI : 10.1186/2047-217x-3-28

URL : http://doi.org/10.1186/2047-217x-3-28