W. Schultz, P. Dayan, and R. R. Montague, A Neural Substrate of Prediction and Reward, Science, vol.275, issue.5306, pp.1593-1599, 1997.
DOI : 10.1126/science.275.5306.1593

I. Bar-gad, G. Morris, H. Bergman, and H. , Information processing, dimensionality reduction and reinforcement learning in the basal ganglia, Progress in Neurobiology, vol.71, issue.6, pp.439-477, 2003.
DOI : 10.1016/j.pneurobio.2003.12.001

J. Fix, N. Rougier, and F. Alexandre, From physiological principles to computational models of the cortex, Journal of Physiology-Paris, vol.101, issue.1-3, pp.1-3, 2007.
DOI : 10.1016/j.jphysparis.2007.10.009
URL : https://hal.archives-ouvertes.fr/inria-00166536

T. Kohonen, Self-Organizing Maps, 1997.

H. Frezza-buet and F. Alexandre, From a biological to a computational model for the autonomous behavior of an animat, Information Sciences, vol.144, issue.1-4, pp.1-43, 2002.
DOI : 10.1016/S0020-0255(02)00195-0
URL : https://hal.archives-ouvertes.fr/inria-00100715

J. Fix, A Computational Approach to the Control of Voluntary Saccadic Eye Movements, International Conference on Cognitive Neurodynamics, 2007.
DOI : 10.1007/978-1-4020-8387-7_85
URL : https://hal.archives-ouvertes.fr/inria-00166540

R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, IEEE Transactions on Neural Networks, vol.9, issue.5, 1998.
DOI : 10.1109/TNN.1998.712192

A. D. Craig, How do you feel ??? now? The anterior insula and human awareness, Nature Reviews Neuroscience, vol.90, issue.1, pp.59-70, 2009.
DOI : 10.1016/j.neuroimage.2007.05.026

M. A. Goodale and G. K. Humphrey, The objects of action and perception, Cognition, vol.67, issue.1-2, pp.181-207, 1998.
DOI : 10.1016/S0010-0277(98)00017-1

P. Cisek, Neural representations of motor plans, desired trajectories, and controlled objects, Cognitive Processing, vol.11, issue.1, pp.15-24, 2005.
DOI : 10.1007/s10339-004-0046-7

P. Redgrave, T. J. Prescott, and K. Gurney, The basal ganglia: a vertebrate solution to the selection problem?, Neuroscience, vol.89, issue.4, pp.1009-1023, 1999.
DOI : 10.1016/S0306-4522(98)00319-4

D. Joel, Y. Niv, and E. Ruppin, Actor???critic models of the basal ganglia: new anatomical and computational perspectives, Neural Networks, vol.15, issue.4-6, pp.535-547, 2002.
DOI : 10.1016/S0893-6080(02)00047-3

S. N. Haber, J. L. Fudge, N. R. Mcfarland, and . Nr, Striatonigrostriatal Pathways in Primates Form an Ascending Spiral from the Shell to the Dorsolateral Striatum, The Journal of Neuroscience, vol.20, issue.6, pp.2369-2382, 2000.

R. S. Sutton, Learning to predict by the methods of temporal differences, Machine Learning, pp.9-448, 1988.
DOI : 10.1007/BF00115009

K. Gurney, T. J. Prescott, and P. Redgrave, A computational model of action selection in the basal ganglia. I. A new functional anatomy, Biological Cybernetics, vol.84, issue.6, pp.401-410, 2001.
DOI : 10.1007/PL00007984

A. Leblois, T. Boraud, W. Meissner, H. Bergman, and D. Hansel, Competition between Feedback Loops Underlies Normal and Pathological Dynamics in the Basal Ganglia, Journal of Neuroscience, vol.26, issue.13, pp.3567-3583, 2006.
DOI : 10.1523/JNEUROSCI.5050-05.2006
URL : https://hal.archives-ouvertes.fr/hal-00094738

G. E. Alexander, M. R. Delong, and P. L. Strick, Parallel Organization of Functionally Segregated Circuits Linking Basal Ganglia and Cortex, Annual Review of Neuroscience, vol.9, issue.1, pp.357-81, 1986.
DOI : 10.1146/annurev.ne.09.030186.002041

N. D. Daw and K. Doya, The computational neurobiology of learning and reward, Current Opinion in Neurobiology, vol.16, issue.2, pp.199-204, 2006.
DOI : 10.1016/j.conb.2006.03.006

R. C. O-'reilly, M. J. Frank, T. E. Hazy, and B. Watz, PVLV: The Primary Value and Learned Value Pavlovian Learning Algorithm., Behavioral Neuroscience, vol.121, issue.1, pp.31-49, 2007.
DOI : 10.1037/0735-7044.121.1.31

E. Oja, Simplified neuron model as a principal component analyzer, Journal of Mathematical Biology, vol.35, issue.3, pp.267-273, 1982.
DOI : 10.1007/BF00275687

A. Carlson, Anti-Hebbian learning in a non-linear neural network, Biological Cybernetics, vol.10, issue.2, pp.171-176, 1990.
DOI : 10.1007/BF02331347

P. J. Zufiria and J. A. , Analysis of Hebbian Models with Lateral Weight Connections, International Workshop on Artificial Neural Networks, IWANN 2007, pp.39-46, 2007.
DOI : 10.1007/978-3-540-73007-1_6

S. Y. Kung and K. I. Diamantaras, A neural network learning algorithm for adaptive principal component extraction (APEX), International Conference on Acoustics, Speech, and Signal Processing, pp.861-864, 1990.
DOI : 10.1109/ICASSP.1990.115975

J. Rubner and K. Schulten, Development of feature detectors by self-organization, Biological Cybernetics, vol.61, issue.3, pp.193-199, 1990.
DOI : 10.1007/BF00198094

P. Földiák, Adaptive network for optimal linear feature extraction, International Joint Conference on Neural Networks, pp.401-405, 1989.
DOI : 10.1109/IJCNN.1989.118615

K. I. Diamantaras, Neural Networks and Principal Component Analysis, Chapter 8 of Handbook of Neural Network Signal Processing, 2002.

D. Jaeger, H. Kita, and C. J. Wilson, Surround inhibition among projection neurons is weak or nonexistent in the rat neostriatum, Journal of Neurophysiology, vol.72, pp.2555-2558, 1994.

S. Amari, Dynamics of pattern formation in lateral-inhibition type neural fields, Biological Cybernetics, vol.13, issue.2, pp.77-87, 1977.
DOI : 10.1007/BF00337259

W. Erlhagen and G. Schoener, Dynamic field theory of movement preparation., Psychological Review, vol.109, issue.3, pp.545-72, 2002.
DOI : 10.1037/0033-295X.109.3.545

J. J. Gibson, The Ecological Approach to Visual Perception, 1979.