J. Left, R. Right, and R. Fig, Left: anatomical ROI definition; Top-middle: Initial and estimated parcellations; Topright and Bottom-right: HRF estimates with JDE and JPDE for the estimated parcels, and the two regions of interest; Bottom-right: NRL estimates with JDE and JPDE and difference image, Anatomical superposition Initial parcels Estimated parcels

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

F. Forbes and N. Peyrard, Hidden markov random field model selection criteria based on mean field-like approximations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.9, pp.1089-1101, 2003.
DOI : 10.1109/TPAMI.2003.1227985

G. H. Glover, Deconvolution of Impulse Response in Event-Related BOLD fMRI1, NeuroImage, vol.9, issue.4, pp.416-429, 1999.
DOI : 10.1006/nimg.1998.0419

C. Goutte, F. Nielsen, and L. K. Hansen, Modeling the hemodynamic response in fMRI using smooth FIR filters, IEEE Transactions on Medical Imaging, vol.19, issue.12, pp.1188-1201, 2000.
DOI : 10.1109/42.897811

D. A. Handwerker, J. M. Ollinger, and D. Mark, Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses, NeuroImage, vol.21, issue.4, pp.1639-1651, 2004.
DOI : 10.1016/j.neuroimage.2003.11.029

J. Kershaw, B. A. Ardekani, and I. Kanno, Application of Bayesian inference to fMRI data analysis, IEEE Transactions on Medical Imaging, vol.18, issue.12, pp.1138-1152, 1999.
DOI : 10.1109/42.819324

S. Makni, J. Idier, T. Vincent, B. Thirion, G. Dehaene-lambertz et al., A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI, NeuroImage, vol.41, issue.3, pp.941-969, 2008.
DOI : 10.1016/j.neuroimage.2008.02.017

URL : https://hal.archives-ouvertes.fr/cea-00333624

P. Pinel, B. Thirion, S. Mériaux, A. Jobert, J. Serres et al., Fast reproducible identification and large-scale databasing of individual functional cognitive networks, BMC Neuroscience, vol.8, issue.1, p.91, 2007.
DOI : 10.1186/1471-2202-8-91

URL : https://hal.archives-ouvertes.fr/hal-00784462

B. Thirion, G. Flandin, P. Pinel, A. Roche, P. Ciuciu et al., Dealing with the shortcomings of spatial normalization: Multi-subject parcellation of fMRI datasets, Human Brain Mapping, vol.22, issue.8, pp.678-693, 2006.
DOI : 10.1002/hbm.20210

T. Vincent, L. Risser, and P. Ciuciu, Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series, IEEE Transactions on Medical Imaging, vol.29, issue.4, pp.1059-1074, 2010.
DOI : 10.1109/TMI.2010.2042064

URL : https://hal.archives-ouvertes.fr/cea-00470594

T. D. Wager, A. Vazquez, L. Hernandez, and D. C. Noll, Accounting for nonlinear BOLD effects in fMRI: parameter estimates and a model for prediction in rapid event-related studies, NeuroImage, vol.25, issue.1, pp.206-224, 2005.
DOI : 10.1016/j.neuroimage.2004.11.008

J. Wang, H. Zhu, J. Fan, K. Giovanello, and W. Lin, Adaptively and Spatially Estimating the Hemodynamic Response Functions in fMRI, In: MICCAI, vol.29, pp.269-276, 2011.
DOI : 10.1109/TMI.2010.2042064

M. Woolrich, M. Jenkinson, J. Brady, and S. Smith, Fully Bayesian Spatio-Temporal Modeling of FMRI Data, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.213-231, 2004.
DOI : 10.1109/TMI.2003.823065