R. Grech and T. Cassar, Review on solving the inverse problem in EEG source analysis, Journal of NeuroEngineering and Rehabilitation, vol.5, issue.1, p.25, 2008.
DOI : 10.1186/1743-0003-5-25

B. Cottereau and K. Jerbi, Multiresolution imaging of MEG cortical sources using an explicit piecewise model, NeuroImage, vol.38, issue.3, pp.439-451, 2007.
DOI : 10.1016/j.neuroimage.2007.07.046

R. A. Chowdhury and J. M. Lina, MEG Source Localization of Spatially Extended Generators of Epileptic Activity: Comparing Entropic and Hierarchical Bayesian Approaches, PLoS ONE, vol.2011, issue.2, p.55969, 2013.
DOI : 10.1371/journal.pone.0055969.s004

A. Anwander and M. Tittgemeyer, Connectivity-Based Parcellation of Broca's Area, Cerebral Cortex, vol.17, issue.4, pp.816-825, 2007.
DOI : 10.1093/cercor/bhk034

C. Amblard and E. Lapalme, Biomagnetic Source Detection by Maximum Entropy and Graphical Models, IEEE Transactions on Biomedical Engineering, vol.51, issue.3, pp.427-442, 2004.
DOI : 10.1109/TBME.2003.820999

K. Friston and . Harrison, Multiple sparse priors for the M/EEG inverse problem, NeuroImage, vol.39, issue.3, pp.1104-1120, 2008.
DOI : 10.1016/j.neuroimage.2007.09.048

J. Mattout and M. Pélégrini-issac, Multivariate source prelocalization (MSP): Use of functionally informed basis functions for better conditioning the MEG inverse problem, NeuroImage, vol.26, issue.2, pp.356-373, 2005.
DOI : 10.1016/j.neuroimage.2005.01.026

R. N. Henson and D. G. Wakeman, A Parametric Empirical Bayesian Framework for the EEG/MEG Inverse Problem: Generative Models for Multi-Subject and Multi-Modal Integration, Frontiers in Human Neuroscience, vol.5, issue.76, 2011.
DOI : 10.3389/fnhum.2011.00076

D. G. Wakeman and R. N. Henson, A multi-subject, multi-modal human neuroimaging dataset, Scientific Data, 2015.
DOI : 10.1088/0031-9155/48/22/002

A. M. Dale and B. Fischl, Cortical Surface-Based Analysis, NeuroImage, vol.9, issue.2, p.179194, 1999.
DOI : 10.1006/nimg.1998.0395

F. Tadel and S. Baillet, Brainstorm: A User-Friendly Application for MEG/EEG Analysis, Computational Intelligence and Neuroscience, vol.57, issue.1, p.19, 2011.
DOI : 10.1002/hbm.20781

S. M. Smith and . Jenkinson, Advances in functional and structural MR image analysis and implementation as FSL, Mathematics in Brain Imag- ing, pp.208-219, 2004.
DOI : 10.1016/j.neuroimage.2004.07.051

A. Gramfort and T. Papadopoulo, OpenMEEG: opensource software for quasistatic bioelectromagnetics, BioMedical Engineering OnLine, vol.9, issue.1, p.45, 2010.
DOI : 10.1186/1475-925X-9-45
URL : https://hal.archives-ouvertes.fr/inria-00467061

A. Gramfort and M. Luessi, MEG and EEG data analysis with MNE-Python, Frontiers in Neuroscience, vol.7, issue.267, 2013.
DOI : 10.3389/fnins.2013.00267

T. E. Behrens and H. Berg, Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?, NeuroImage, vol.34, issue.1, pp.144-155, 2007.
DOI : 10.1016/j.neuroimage.2006.09.018

B. Rossion and R. Caldara, A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing, Brain, vol.126, issue.11, pp.2381-2395, 2003.
DOI : 10.1093/brain/awg241

A. Ishai and E. Yago, Recognition memory of newly learned faces, Brain Research Bulletin, vol.71, issue.1-3, pp.167-173, 2006.
DOI : 10.1016/j.brainresbull.2006.08.017

J. V. Haxby and L. G. Ungerleider, The Effect of Face Inversion on Activity in Human Neural Systems for Face and Object Perception, Neuron, vol.22, issue.1, pp.189-199, 1999.
DOI : 10.1016/S0896-6273(00)80690-X

D. J. Bayle and M. J. Taylor, Attention inhibition of early cortical activation to fearful faces, Brain Research, vol.1313, issue.0, pp.113-123, 2010.
DOI : 10.1016/j.brainres.2009.11.060