J. Grainger, S. Dufau, M. Montant, J. C. Ziegler, and J. Fagot, Orthographic Processing in Baboons (Papio papio), Science, vol.336, pp.245-248, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01152186

J. C. Ziegler, T. Hannagan, S. Dufau, M. Montant, and J. Fagot, Transposed Letter Effects Reveal Orthographic Processing in Baboons Psychological Science, vol.24, issue.8, pp.1609-1611, 2013.

W. Bains, Comment on ''Orthographic Processing in Baboons, Science, vol.337, p.1173, 2012.

R. Frost and E. Keuleers, What can we learn from monkeys about orthographic processing in humans? A reply to Ziegler et al, Psychological Science, vol.24, issue.9, pp.1868-1869, 2013.

J. C. Ziegler and U. Goswami, Reading acquisition, developmental dyslexia, and skilled reading across languages: a psycholinguistic grain size theory, Psychological Bulletin, vol.131, issue.1, pp.3-29, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00201391

J. C. Ziegler, C. Perry, and M. Zorzi, Modelling reading development through phonological decoding and self-teaching: Implications for dyslexia, Philosophical Transactions of the Royal Society B
URL : https://hal.archives-ouvertes.fr/hal-00932101

J. Grainger, Cracking the orthographic code: An introduction, Language and Cognitive Processes, vol.23, issue.1, pp.1-35, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00202912

T. Hannagan and J. Grainger, Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain, Cognitive Science, vol.36, pp.575-606, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00700309

J. R. Binder, D. A. Medler, C. F. Westbury, E. Liebenthal, and L. Buchanan, Tuning of the human left fusiform gyrus to sublexical orthographic structure, Neuroimage, vol.33, pp.739-748, 2006.

F. Vinckier, S. Dehaene, A. Jobert, J. P. Dubus, and M. Sigman, Hierarchical coding of letter strings in the ventral stream: dissecting the inner organization of the visual word-form system, Neuron, vol.55, issue.1, pp.143-156, 2007.

L. Cohen, S. Dehaene, L. Naccache, S. Lehéricy, and G. Dehaene-lambertz, The visual word form area: Spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients, Brain, vol.123, pp.291-307, 2000.

S. L. Brincat and C. E. Connor, Dynamic Shape Synthesis in Posterior Inferotemporal Cortex, Neuron, vol.49, issue.1, pp.17-24, 2006.
DOI : 10.1016/j.neuron.2005.11.026
URL : https://doi.org/10.1016/j.neuron.2005.11.026

S. Dehaene, L. Cohen, M. Sigman, and F. Vinckier, The neural code for written words: a proposal, Trends Cogn Sci, vol.9, pp.335-341, 2005.

X. Blaizot, B. Landeau, J. C. Baron, and C. Chavoix, Mapping the visual recognition memory network with PET in the behaving baboon, Journal of Cerebral Blood Flow and Metabolism, vol.20, pp.213-219, 2000.
DOI : 10.1097/00004647-200002000-00001
URL : http://journals.sagepub.com/doi/pdf/10.1097/00004647-200002000-00001

K. Fukushima, Neocognitron: A self-organizing neural network for a mechanism of pattern recognition unaffected by shift in position, Biological Cybernetics, vol.36, issue.4, pp.193-202, 1980.

Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998.
DOI : 10.1109/5.726791
URL : http://www.cs.berkeley.edu/~daf/appsem/Handwriting/papers/00726791.pdf

D. C. Van-essen and J. L. Gallant, Neural mechanisms of form and motion processing in the primate visual system, Neuron, vol.13, pp.1-10, 1994.

D. C. Ciresan, U. Meier, and J. Schmidhuber, Multi-column Deep Neural Networks for Image Classification, IEEE Conf. on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/cvpr.2012.6248110
URL : http://www.idsia.ch/idsiareport/IDSIA-04-12.pdf

C. Farabet, C. Couprie, L. Najman, and Y. Lecun, Learning hierarchical features for scene labeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013.
DOI : 10.1109/tpami.2012.231
URL : https://hal.archives-ouvertes.fr/hal-00742077

T. Serre, A. Oliva, and T. Poggio, A Feedforward Architecture Accounts for Rapid Categorization, Proc Natl Acad Sci, vol.104, issue.15, pp.6424-6429, 2007.
DOI : 10.1073/pnas.0700622104
URL : http://www.pnas.org/content/104/15/6424.full.pdf

J. Bergstra, F. Bastien, O. Breuleux, P. Lamblin, R. Pascanu et al., Theano: Deep learning on GPUs with python, NIPS 2011, BigLearning Workshop, 2011.

M. Perea and S. J. Lupker, Can CANISO activate CASINO? Transposed-letter similarity effects with nonadjacent letter positions, Journal of Memory and Language, vol.51, pp.231-246, 2004.
DOI : 10.1016/j.jml.2004.05.005

F. Mechler and D. L. Ringach, On the classification of simple and complex cells, Vision research, vol.42, pp.1017-1033, 2002.

D. H. Hubel and T. N. Wiesel, Receptive fields and functional architecture of monkey striate cortex, Journal of Physiology-London, vol.195, pp.215-243, 1968.
DOI : 10.1113/jphysiol.1968.sp008455
URL : http://onlinelibrary.wiley.com/doi/10.1113/jphysiol.1968.sp008455/pdf

B. C. Skottun, D. Valois, R. L. Grosof, D. H. Movshon, J. A. Albrecht et al., Classifying simple and complex cells on the basis of response modulation, Vision Research, vol.31, pp.1079-1086, 1991.
DOI : 10.1016/0042-6989(91)90033-2

J. Léveillé and T. Hannagan, Learning spatial invariance with the trace rule in non-uniform distributions, Neural Computation, vol.25, issue.5, pp.1261-1276, 2012.

D. Erhan, A. Courville, and Y. Bengio, Understanding Representations Learned in Deep Architectures, 2010.

I. Stoianov and M. Zorzi, Emergence of a ''visual number sense'' in hierarchical generative models, Nature neuroscience, vol.15, issue.2, pp.194-200, 2012.

D. C. Plaut and T. Shallice, Deep dyslexia: A case study of connectionist neuropsychology, Cognitive Neuropsychology, vol.10, pp.377-500, 1993.
DOI : 10.1080/02643299308253469
URL : http://www.cnbc.cmu.edu/~plaut/papers/abstracts/../pdf/PlautShallice93CN.deepDyslexia.pdf

G. Cohen, R. A. Johnston, and K. Plunkett, Exploring cognition: Damaged brains and neural networks, readings in cognitive neuropsychology and connectionist modelling, 2000.

M. Thomas, H. Purser, S. Tomlinson, and D. Mareschal, Are imaging and lesioning convergent methods for assessing functional specialisation? Investigations using an artificial neural network, Brain and Cognition, vol.78, issue.1, pp.38-49, 2011.
DOI : 10.1016/j.bandc.2011.10.003
URL : http://www.psyc.bbk.ac.uk/research/DNL/personalpages/Thomas_etal_BC_final.pdf

J. Mutch and D. G. &lowe, Object class recognition and localization using sparse features with limited receptive fields, International Journal of Computer Vision, vol.80, issue.1, pp.45-57, 2008.
DOI : 10.1007/s11263-007-0118-0
URL : http://www.cs.ubc.ca/~lowe/papers/08mutch.pdf

T. Hannagan, F. Dandurand, and J. Grainger, Broken symmetries in a locationinvariant word recognition network, Neural Comput, vol.23, pp.251-283, 2011.
DOI : 10.1162/neco_a_00064
URL : https://hal.archives-ouvertes.fr/hal-00579183

D. Bono, M. G. Zorzi, and M. , Deep generative learning of location-invariant visual word recognition, Front. Psychol, vol.4, p.635, 2013.

A. M. Rauschecker, R. F. Bowen, J. Parvizi, and B. A. Wandell, Position sensitivity in the visual word form area, Proc Natl Acad Sci, vol.109, issue.24, pp.1568-1577, 2012.
DOI : 10.1073/pnas.1121304109
URL : http://www.pnas.org/content/109/24/E1568.full.pdf

T. Hannagan and J. Grainger, The Lazy Visual Word Form Area: Computational Insights into Location-Sensitivity, PLoS Comput Biol, vol.9, issue.10, p.1003250, 2013.
DOI : 10.1371/journal.pcbi.1003250
URL : https://hal.archives-ouvertes.fr/hal-00932033

F. Pegado, K. Nakamura, L. Cohen, and S. Dehaene, Breaking the Symmetry: Mirror discrimination for single letters but not for pictures in the Visual Word Form Area, NeuroImage, vol.55, pp.742-751, 2011.

M. Mozer, Early parallel processing in reading: A connectionist approach, pp.83-104, 1987.

C. S. Whitney and R. S. Berndt, A new model of letter string encoding: Simulating right neglect dyslexia, Progress in Brain Research, vol.121, pp.143-163, 1999.
DOI : 10.1016/s0079-6123(08)63072-1

J. Grainger and W. Van-heuven, Modeling letter position coding in printed word perception, pp.1-23, 2003.