A. Yuille and H. Bulthoff, Bayesian decision theory and psychophysics, Perception as Bayesian Inference, pp.123-161, 1996.
DOI : 10.1017/CBO9780511984037.006
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.6107

R. S. Zemel, P. Dayan, and A. Pouget, Probabilistic Interpretation of Population Codes, Neural Computation, vol.76, issue.4, pp.403-430, 1998.
DOI : 10.1038/370140a0

W. Ma, . Beck, A. Latham, and . Pouget, Bayesian inference with probabilistic population codes, Nature Neuroscience, vol.9, issue.11, 2006.
DOI : 10.1038/nn1691

P. Rajesh and . Rao, Bayesian computation in recurrent neural circuits, Neural Comput, vol.16, issue.1, pp.1-38, 2004.

J. Gold and M. Shadlen, Neural computations that underlie decisions about sensory stimuli, Trends in Cognitive Sciences, vol.5, issue.1, pp.10-16, 2001.
DOI : 10.1016/S1364-6613(00)01567-9

C. David, A. Knill, and . Pouget, The bayesian brain: the role of uncertainty in neural coding and computation, Trends Neurosci, vol.27, issue.12, pp.712-719, 2004.

M. W. Oram, D. Xiao, B. Dritschel, and K. R. Payne, The temporal resolution of neural codes: does response latency have a unique role?, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.357, issue.1424, pp.987-1001, 1424.
DOI : 10.1098/rstb.2002.1113

D. S. Reich, F. Mechler, and J. D. Victor, Temporal coding of contrast in primary visual cortex: when, what, and why, J Neurophysiol, vol.85, issue.3, pp.1039-1050, 2001.

R. Kiani, H. Esteky, and K. Tanaka, Differences in Onset Latency of Macaque Inferotemporal Neural Responses to Primate and Non-Primate Faces, Journal of Neurophysiology, vol.94, issue.2, pp.1587-1596, 2005.
DOI : 10.1152/jn.00540.2004

T. Michelet, P. Duncan, and . Cisek, Response Competition in the Primary Motor Cortex: Corticospinal Excitability Reflects Response Replacement During Simple Decisions, Journal of Neurophysiology, vol.104, issue.1, 2010.
DOI : 10.1152/jn.00819.2009

E. Hazeltine, J. Poldrack, and . Gabrieli, Neural Activation During Response Competition, Journal of Cognitive Neuroscience, vol.70, issue.supplement 2, pp.118-129, 2000.
DOI : 10.1097/00004728-199207000-00024

R. Borowsky and M. E. Masson, Semantic ambiguity effects in word identification., Psych: Learning, Memory, and Cognition, p.63, 1996.
DOI : 10.1037/0278-7393.22.1.63

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

. Shun-ichi-amari, Mathematical foundations of neurocomputing, Proceedings of the IEEE, pp.1441-1463, 1990.

P. Cisek, Integrated Neural Processes for Defining Potential Actions and Deciding between Them: A Computational Model, Journal of Neuroscience, vol.26, issue.38, pp.9761-9770, 2006.
DOI : 10.1523/JNEUROSCI.5605-05.2006

S. Kubota and K. Aihara, Anayzing global dynamics of a neural field model, Neural Processing Letters, 2005.

C. Faubel and G. Schöner, Learning to recognize objects on the fly: A neurally based dynamic field approach, Neural Networks, vol.21, issue.4, pp.562-576, 2008.
DOI : 10.1016/j.neunet.2008.03.007

A. Gepperth, Processing and Transmission of Confidence in Recurrent Neural Hierarchies, Neural Processing Letters, 2013.
DOI : 10.1007/s11063-013-9311-z

C. Bishop, Pattern recognition and machine learning, 2006.