Information theory and neural coding, Nature Neuroscience, vol.381, issue.11, pp.947-57, 1999. ,
DOI : 10.1038/381610a0
Decoding and information theory in neuroscience, pg. 139?163, Principles of Neural Coding, Quiroga and Panezeri, 2013. ,
Reading a neural code, Science, vol.252, issue.5014, pp.1854-1861, 1991. ,
DOI : 10.1126/science.2063199
Decoding Visual Information From a Population of Retinal Ganglion Cells, Journal of Neurophysiology, vol.36, issue.5, pp.2336-2350, 1997. ,
DOI : 10.1152/jn.1991.66.5.1690
High Accuracy Decoding of Dynamical Motion from a Large Retinal Population, PLOS Computational Biology, vol.1, issue.NO. 4, 2015. ,
DOI : 10.1371/journal.pcbi.1004304.g009
URL : https://hal.archives-ouvertes.fr/hal-01236241
Low error discrimination using a correlated population code, Journal of Neurophysiology, vol.78, issue.4, pp.1069-88, 2012. ,
DOI : 10.1523/JNEUROSCI.3127-11.2011
Fidelity of the Ensemble Code for Visual Motion in Primate Retina, Journal of Neurophysiology, vol.94, issue.1, pp.119-135, 2004. ,
DOI : 10.1038/370140a0
Spatio-temporal correlations and visual signalling in a complete neuronal population, Nature, vol.22, issue.7207, pp.995-1004, 2008. ,
DOI : 10.1113/jphysiol.1978.sp012571
Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains, Neural Computation, vol.79, issue.1, pp.1-45, 2011. ,
DOI : 10.1109/TNSRE.2009.2023307
Massively parallel neural encoding and decoding of visual stimuli Neural Networks, pp.303-312, 2012. ,
Reconstructing Stimuli from the Spike Times of Leaky Integrate and Fire Neurons, Frontiers in Neuroscience, vol.5, p.21390287, 2011. ,
DOI : 10.3389/fnins.2011.00001
Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains, Neural Computation, vol.79, issue.1, pp.46-96, 2011. ,
DOI : 10.1152/jn.90941.2008
Determining the role of correlated firing in large populations of neurons using white noise and natural scene stimuli, Vision Research, vol.70, pp.44-53, 2012. ,
DOI : 10.1016/j.visres.2012.07.007
Interacting Linear and Nonlinear Characteristics Produce Population Coding Asymmetries between ON and OFF Cells in the Retina, Journal of Neuroscience, vol.33, issue.37, pp.14958-14973, 2013. ,
DOI : 10.1523/JNEUROSCI.1004-13.2013
Mapping a Complete Neural Population in the Retina, Journal of Neuroscience, vol.32, issue.43, pp.14859-14873, 2012. ,
DOI : 10.1523/JNEUROSCI.0723-12.2012
A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing, Neural Computation, vol.64, issue.2, pp.424-449, 2009. ,
DOI : 10.1137/1.9781611970128
Deep learning, Nature, vol.9, issue.7553, pp.436-444, 2015. ,
DOI : 10.1007/s10994-013-5335-x
A schematic eye for the rat, Vision Research, vol.19, issue.5, pp.569-880042, 1979. ,
DOI : 10.1016/0042-6989(79)90143-3
An Interior-Point Method for Large-Scale -Regularized Least Squares, IEEE Journal of Selected Topics in Signal Processing, vol.1, issue.4, pp.606-617910971, 2007. ,
DOI : 10.1109/JSTSP.2007.910971
Kernel Methods in Computer Vision. Foundations and trends in computer graphics and vision, 2009. ,
, Bishop CM. Pattern Recognition and Machine Learning, 2006.
Kernel Methods on Spike Train Space for Neuroscience: A Tutorial, IEEE Signal Processing Magazine, vol.30, issue.4, 2013. ,
DOI : 10.1109/MSP.2013.2251072
Adam: A Method for Stochastic Optimization, Proceedings of ICLR, 2015. ,
Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs, PLoS Computational Biology, vol.78, issue.7 ,
DOI : 10.1371/journal.pcbi.1003143.s006
MAINTAINED ACTIVITY IN THE CAT'S RETINA IN LIGHT AND DARKNESS, The Journal of General Physiology, vol.40, issue.5, pp.683-702, 1957. ,
DOI : 10.1085/jgp.40.5.683
Abstract, Visual Neuroscience, vol.30, issue.01, pp.111-118, 1994. ,
DOI : 10.1364/JOSAA.7.002223
The Structure of Multi-Neuron Firing Patterns in Primate Retina, Journal of Neuroscience, vol.26, issue.32, pp.8254-8266, 2006. ,
DOI : 10.1523/JNEUROSCI.1282-06.2006
Abstract, Visual Neuroscience, vol.29, issue.04, pp.535-548, 2008. ,
DOI : 10.1017/S0952523800001784
A Point Process Framework for Relating Neural Spiking Activity to Spiking History, Neural Ensemble, and Extrinsic Covariate Effects, Journal of Neurophysiology, vol.93, issue.2, pp.1074-1089, 2004. ,
DOI : 10.1126/science.8351520
Likelihood-based approaches to modeling the neural code In Bayesian Brain: Probabilistic Approaches to Neural Coding, pp.53-70, 2007. ,
Collective dynamics in human and monkey sensorimotor cortex: predicting single neuron spikes, Nature Neuroscience, vol.18, issue.1, pp.105-113, 2010. ,
DOI : 10.1038/nn.2455
Population decoding of motor cortical activity using a generalized linear model with hidden states, Journal of Neuroscience Methods, vol.189, issue.2, pp.267-280, 2010. ,
DOI : 10.1016/j.jneumeth.2010.03.024
Multiplexed computations in retinal ganglion cells of a single type, Nature Comms, vol.8, 1964. ,
URL : https://hal.archives-ouvertes.fr/hal-01699587
Recording from Two Neurons: Second-Order Stimulus Reconstruction from Spike Trains and Population Coding, Neural Computation, vol.74, issue.15, pp.2537-2557, 2010. ,
DOI : 10.1016/j.cub.2009.04.003
Coding and computation with neural spike trains, Journal of Statistical Physics, vol.16, issue.1-2, pp.103-115, 1990. ,
DOI : 10.1007/BF01015565
Information rates and optimal decoding in large neural populations, Adv Neural Proc Syst, vol.24, pp.846-854, 2011. ,
Nonlinear Dynamics Support a Linear Population Code in a Retinal Target-Tracking Circuit, The Journal of Neuroscience, vol.33, issue.43, pp.16971-16982, 2013. ,
DOI : 10.1523/JNEUROSCI.2257-13.2013
Spike-Based Population Coding and Working Memory, PLoS Computational Biology, vol.10, issue.2, p.21379319, 20117. ,
DOI : 10.1371/journal.pcbi.1001080.g008
URL : https://hal.archives-ouvertes.fr/inserm-00704812
Predictive Coding of Dynamical Variables in Balanced Spiking Networks, PLoS Computational Biology, vol.10, issue.7, p.24244113, 2013. ,
DOI : 10.1371/journal.pcbi.1003258.s001
URL : http://doi.org/10.1371/journal.pcbi.1003258
Efficiency turns the table on neural encoding, decoding and noise, Current Opinion in Neurobiology, vol.37, pp.141-148, 2016. ,
DOI : 10.1016/j.conb.2016.03.002
Neural correlations, population coding and computation, Nature Reviews Neuroscience, vol.2, issue.5, pp.358-366, 2006. ,
DOI : 10.1007/978-3-662-02728-8
Weak pairwise correlations imply strongly correlated network states in a neural population, Nature, vol.37, issue.Suppl. C, pp.1007-1019, 2006. ,
DOI : 10.1109/18.61115
URL : http://europepmc.org/articles/pmc1785327?pdf=render
Decorrelated Neuronal Firing in Cortical Microcircuits, Science, vol.458, issue.7237, pp.584-587, 2010. ,
DOI : 10.1038/nature07722
Stimulus-dependent Maximum Entropy Models of Neural Population Codes, PLoS Computational Biology, vol.012020, issue.3, pp.1002922-23516339, 2013. ,
DOI : 10.1371/journal.pcbi.1002922.g010
URL : https://doi.org/10.1371/journal.pcbi.1002922
Reconstruction of Natural Scenes from Ensemble Responses in the Lateral Geniculate Nucleus, The Journal of Neuroscience, vol.19, issue.18, pp.8036-8042, 1999. ,
DOI : 10.1523/JNEUROSCI.19-18-08036.1999
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
URL : https://doi.org/10.1016/j.cub.2011.08.031
How Does the Brain Solve Visual Object Recognition?, Neuron, vol.73, issue.3, pp.415-434, 2012. ,
DOI : 10.1016/j.neuron.2012.01.010
Natural Image Statistics?A probabilistic approach to early computational vision, 2009. ,
Responses of auditory-cortex neurons to structural features of natural sounds, Nature, vol.42, issue.6715, pp.154-156, 1999. ,
DOI : 10.1016/0378-5955(89)90116-0
Sparse Coding and Decorrelation in Primary Visual Cortex During Natural Vision, Science, vol.287, issue.5456, pp.1273-1276, 2000. ,
DOI : 10.1126/science.287.5456.1273
URL : http://jacknife.med.yale.edu/spikeclub/VinjeScience2000.pdf
Population code in mouse V1 facilitates readout of natural scenes through increased sparseness, Nature Neuroscience, vol.265, issue.6, pp.851-860, 2014. ,
DOI : 10.1098/rspb.1998.0303
URL : http://europepmc.org/articles/pmc4106281?pdf=render
Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons, Frontiers in Neural Circuits, vol.7, pp.206-24409121, 2013. ,
DOI : 10.3389/fncir.2013.00206
URL : https://hal.archives-ouvertes.fr/hal-01055318
Cortical activity in the null space: permitting preparation without movement, Nature Neuroscience, vol.82, issue.3, pp.440-448, 2014. ,
DOI : 10.1126/science.285.5436.2136
URL : http://europepmc.org/articles/pmc3955357?pdf=render
Neuronal Computations with Stochastic Network States, Science, vol.314, issue.5796, pp.85-90, 2006. ,
DOI : 10.1126/science.1127241
URL : https://hal.archives-ouvertes.fr/hal-00120632
Persistent neural activity: prevalence and mechanisms, Current Opinion in Neurobiology, vol.14, issue.6, pp.675-684, 2004. ,
DOI : 10.1016/j.conb.2004.10.017
Spontaneous and driven cortical activity: implications for computation, Current Opinion in Neurobiology, vol.19, issue.4, pp.439-444, 2009. ,
DOI : 10.1016/j.conb.2009.07.005
URL : http://europepmc.org/articles/pmc3319344?pdf=render