D. Felleman and D. Van-essen, Distributed Hierarchical Processing in the Primate Cerebral Cortex, Cerebral Cortex, vol.1, issue.1, 1991.
DOI : 10.1093/cercor/1.1.1

M. Mishkin and L. Ungerleider, Contribution of striate inputs to the visuospatial functions of parieto-preoccipital cortex in monkeys, Behavioural Brain Research, vol.6, issue.1, pp.57-77, 1982.
DOI : 10.1016/0166-4328(82)90081-X

M. Goodale and D. Milner, Separate visual pathways for perception and action, Trends in Neurosciences, vol.15, issue.1, pp.20-25, 1992.
DOI : 10.1016/0166-2236(92)90344-8

S. Thorpe, D. Fize, and C. Marlot, Speed of processing in the human visual system, 1996.

M. Fabre-thorpe, A. Delorme, C. Marlot, and S. Thorpe, A Limit to the Speed of Processing in Ultra-Rapid Visual Categorization of Novel Natural Scenes, Journal of Cognitive Neuroscience, vol.73, issue.2, pp.171-180, 2001.
DOI : 10.1016/S0959-4388(98)80144-X

B. Wandell, S. Dumoulin, and A. Brewer, Visual Field Maps in Human Cortex, Neuron, vol.56, issue.2, pp.366-383, 2007.
DOI : 10.1016/j.neuron.2007.10.012

D. Hubel and T. Wiesel, Receptive fields of single neurones in the cat's striate cortex, The Journal of Physiology, vol.148, issue.3, pp.574-591, 1959.
DOI : 10.1113/jphysiol.1959.sp006308

A. Anzai, X. Peng, and D. Van-essen, Neurons in monkey visual area V2 encode combinations of orientations, Nature Neuroscience, vol.7, issue.10, pp.1313-1321, 2007.
DOI : 10.1038/nn1975

J. Freeman, C. Ziemba, D. Heeger, E. Simoncelli, and J. Movshon, A functional and perceptual signature of the second visual area in primates, Nature Neuroscience, vol.28, issue.7, pp.974-81, 2013.
DOI : 10.3758/BF03194544

A. Roe, L. Chelazzi, C. Connor, B. Conway, and I. Fujita, Toward a Unified Theory of Visual Area V4, Neuron, vol.74, issue.1, pp.12-29, 2012.
DOI : 10.1016/j.neuron.2012.03.011

R. Desimone, T. Albright, C. Gross, and C. Bruce, Stimulus-selective Properties of Inferior Temporal Neurons in the Macaque, Journal of Neuroscience, vol.4, pp.2051-2062, 1984.

N. Logothetis, J. Pauls, and T. Poggio, Shape representation in the inferior temporal cortex of monkeys, Current Biology, vol.5, issue.5, pp.552-563, 1995.
DOI : 10.1016/S0960-9822(95)00108-4

N. Kanwisher, J. Mcdermott, and M. Chun, The Fusiform Face Area : A Module in Human Extrastriate Cortex Specialized for Face Perception, The Journal of Neuroscience, vol.17, pp.4302-4311, 1997.

P. Downing, Y. Jiang, M. Shuman, and N. Kanwisher, A Cortical Area Selective for Visual Processing of the Human Body, Science, vol.293, issue.5539, pp.2470-2473, 2001.
DOI : 10.1126/science.1063414

R. Epstein and N. Kanwisher, A cortical representation of the local visual environment, Nature, vol.392, issue.6676, pp.598-601, 1998.
DOI : 10.1038/33402

T. Naselaris, K. Kay, S. Nishimoto, and J. Gallant, Encoding and decoding in fMRI, NeuroImage, vol.56, issue.2, pp.400-410, 2011.
DOI : 10.1016/j.neuroimage.2010.07.073

K. Kay, T. Naselaris, R. Prenger, and J. Gallant, Identifying natural images from human brain activity, Nature, vol.79, issue.7185, pp.352-355, 2008.
DOI : 10.1038/nature06713

T. Naselaris, R. Prenger, K. Kay, M. Oliver, and J. Gallant, Bayesian Reconstruction of Natural Images from Human Brain Activity, Neuron, vol.63, issue.6, pp.902-915, 2009.
DOI : 10.1016/j.neuron.2009.09.006

S. Nishimoto, A. Vu, T. Naselaris, Y. Benjamini, and B. Yu, Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies, Current Biology, vol.21, issue.19, pp.1641-1646, 2011.
DOI : 10.1016/j.cub.2011.08.031

P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, and R. Fergus, OverFeat : Integrated Recognition , Localization and Detection using Convolutional Networks. arXiv preprint arXiv, pp.13126229-13126230, 2013.

A. Huth, S. Nishimoto, A. Vu, and J. Gallant, A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain, Neuron, vol.76, issue.6, pp.1210-1224, 2012.
DOI : 10.1016/j.neuron.2012.10.014

K. Simonyan, A. Vedaldi, and A. Zisserman, Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. arXiv preprint arXiv, pp.13126034-13126035, 2013.

U. Guclu, . Van-gerven, and . Maj, Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream, Journal of Neuroscience, vol.35, issue.27, pp.10005-10014, 2015.
DOI : 10.1523/JNEUROSCI.5023-14.2015

S. Khaligh-razavi and N. Kriegeskorte, Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation, PLoS Computational Biology, vol.55, issue.14, 2014.
DOI : 10.1371/journal.pcbi.1003915.s014

E. Simoncelli and W. Freeman, The steerable pyramid: a flexible architecture for multi-scale derivative computation, Proceedings., International Conference on Image Processing, pp.444-447, 1995.
DOI : 10.1109/ICIP.1995.537667

M. Riesenhuber and T. Poggio, Hierarchical models of object recognition in cortex, Nature neuroscience, vol.2, pp.1019-1025, 1999.

T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber, and T. Poggio, Robust Object Recognition with Cortex-Like Mechanisms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.3, pp.411-426, 2007.
DOI : 10.1109/TPAMI.2007.56

J. Bruna and S. Mallat, Invariant Scattering Convolution Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, pp.1872-1886, 2013.
DOI : 10.1109/TPAMI.2012.230

M. Eickenberg, F. Pedregosa, M. Senoussi, A. Gramfort, and B. Thirion, Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures, 2013 International Workshop on Pattern Recognition in Neuroimaging, pp.5-8, 2013.
DOI : 10.1109/PRNI.2013.11
URL : https://hal.archives-ouvertes.fr/hal-00834928

N. Kriegeskorte, M. Mur, D. Ruff, R. Kiani, and J. Bodurka, Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey, Neuron, vol.60, issue.6, pp.1126-1141, 2008.
DOI : 10.1016/j.neuron.2008.10.043

Y. Lecun, Y. Bengio, and G. Hinton, Deep learning, Nature, vol.9, issue.7553, pp.436-444, 2015.
DOI : 10.1007/s10994-013-5335-x

D. Yamins, H. Hong, C. Cadieu, S. Ea, and D. Seibert, Performance-optimized hierarchical models predict neural responses in higher visual cortex, Proceedings of the National Academy of Sciences, vol.111, issue.23, pp.8619-8643, 2014.
DOI : 10.1073/pnas.1403112111

. Krizhevsky-a, I. Sutskever, and G. Hinton, Imagenet classification with deep convolutional neural networks Advances in neural information processing systems, pp.1097-1105, 2012.

K. He, X. Zhang, S. Ren, and J. Sun, Delving Deep into Rectifiers: Surpassing Human- Level Performance on ImageNet Classification. arXiv preprint arXiv, p.150201852, 2015.

K. Kay, T. Naselaris, and J. Gallant, fmri of human visual areas in response to natural images, 2011.

J. Gao, A. Huth, M. Lescroart, and J. Gallant, Pycortex: an interactive surface visualizer for fMRI, Frontiers in neuroinformatics 9, 2015.
DOI : 10.1136/jamia.2001.0080443

Y. Benjamini and Y. Hochberg, Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, 1995.

M. Sereno, A. Dale, and J. Reppas, Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging, Science, vol.268, issue.5212, 1995.
DOI : 10.1126/science.7754376

N. Pinto, D. Cox, and J. Dicarlo, Why is Real-World Visual Object Recognition Hard?, PLoS Computational Biology, vol.58, issue.1, pp.151-0156, 2008.
DOI : 10.1371/journal.pcbi.0040027.sg004

J. Haxby, M. Gobbini, M. Furey, A. Ishai, and J. Schouten, Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex, Science, vol.293, issue.5539, pp.2425-2430, 2001.
DOI : 10.1126/science.1063736

K. Bettencourt and Y. Xu, The Role of Transverse Occipital Sulcus in Scene Perception and Its Relationship to Object Individuation in Inferior Intraparietal Sulcus, Journal of Cognitive Neuroscience, vol.4, issue.10, pp.1711-1733, 2013.
DOI : 10.1016/S0959-4388(03)00033-3

K. Grill-spector, Z. Kourtzi, and N. Kanwisher, The lateral occipital complex and its role in object recognition, Vision Research, vol.41, issue.10-11, pp.1409-1422, 2001.
DOI : 10.1016/S0042-6989(01)00073-6

J. Taylor, A. Wiggett, and P. Downing, Functional MRI Analysis of Body and Body Part Representations in the Extrastriate and Fusiform Body Areas, Journal of Neurophysiology, vol.98, issue.3, pp.1626-1633, 2007.
DOI : 10.1152/jn.00012.2007

J. Gallant, C. Connor, S. Rakshit, J. Lewis, and D. Van-essen, Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey, Journal of neurophysiology, vol.76, pp.2718-2739, 1996.

S. Bentin, T. Allison, A. Puce, E. Perez, and G. Mccarthy, Electrophysiological Studies of Face Perception in Humans, Journal of Cognitive Neuroscience, vol.87, issue.6, p.551, 1996.
DOI : 10.1126/science.1598577

J. Gallant, C. Connor, and D. Van-essen, Neural activity in areas V1, V2 and V4 during free viewing of natural scenes compared to controlled viewing, NeuroReport, vol.9, issue.9, pp.2153-2158, 1998.
DOI : 10.1097/00001756-199806220-00045

B. Olshausen and D. Field, Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, vol.381, issue.6583, p.607, 1996.
DOI : 10.1038/381607a0

S. Khaligh-razavi, L. Henriksson, K. Kay, and N. Kriegeskorte, Explaining the hierarchy of visual representational geometries by remixing of features from many computational vision models, 2014.

M. Schira, A. Wade, and C. Tyler, Two-Dimensional Mapping of the Central and Parafoveal Visual Field to Human Visual Cortex, Journal of Neurophysiology, vol.97, issue.6, pp.4284-4295, 2007.
DOI : 10.1152/jn.00972.2006

J. Heinzle, T. Kahnt, and J. Haynes, Topographically specific functional connectivity between visual field maps in the human brain, NeuroImage, vol.56, issue.3, pp.1426-1436, 2011.
DOI : 10.1016/j.neuroimage.2011.02.077