Neuronal population coding of movement direction, Science, vol.233, issue.4771, pp.1416-1425, 1986. ,
Natural image statistics and neural representation, vol.24, pp.1193-216, 2001. ,
Neural correlations, population coding and computation, Nature Reviews Neuroscience, vol.7, issue.5, pp.358-66, 2006. ,
Population-wide distributions of neural activity during perceptual decision-making, Progress in neurobiology, vol.103, pp.156-93, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-01904763
Dynamics of pattern formation in lateral-inhibition type neural fields, Biological cybernetics, vol.27, issue.2, pp.77-87, 1977. ,
Theory of orientation tuning in visual cortex, Proceedings of the National Academy of Sciences, vol.92, issue.9, pp.3844-3852, 1995. ,
A unified approach to building and controlling spiking attractor networks. Neural computation, vol.17, pp.1276-314, 2005. ,
Fundamental limits on persistent activity in networks of noisy neurons, Proceedings of the National Academy of Sciences, vol.109, issue.43, pp.17645-50, 2012. ,
Inhibitory plasticity: Balance, control, and codependence, Annual Review of Neuroscience, vol.40, pp.557-79, 2017. ,
An information-maximization approach to blind separation and blind deconvolution, Neural computation, vol.7, issue.6, pp.1129-59, 1995. ,
Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, vol.381, issue.6583, pp.607-616, 1996. ,
A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of v1 simple cell receptive fields, PLoS Comput Biol, vol.7, issue.10, p.1002250, 2011. ,
Independent component analysis in spiking neurons, PLoS Comput Biol, vol.6, issue.4, 2010. ,
Learning optimal spike-based representations, Advances in neural information processing systems, pp.2285-93, 2012. ,
Mirrored stdp implements autoencoder learning in a network of spiking neurons, PLoS computational biology, vol.11, issue.12, p.1004566, 2015. ,
Unsupervised learning of an efficient short-term memory network, Advances in neural information processing systems, pp.3653-61, 2014. ,
A hebbian/anti-hebbian neural network for linear subspace learning: A derivation from multidimensional scaling of streaming data, Neural computation, vol.27, issue.7, pp.1461-95, 2015. ,
Why do similarity matching objectives lead to hebbian/antihebbian networks?, Neural computation, vol.30, issue.1, pp.84-124, 2018. ,
An approximation of the error backpropagation algorithm in a predictive coding network with local hebbian synaptic plasticity, Neural computation, vol.29, issue.5, pp.1229-62, 2017. ,
Towards deep learning with segregated dendrites, ELife, vol.6, 2017. ,
Dendritic cortical microcircuits approximate the backpropagation algorithm, Advances in neural information processing systems, pp.8721-8753, 2018. ,
Deep learning without weight transport, Advances in neural information processing systems, pp.974-82, 2019. ,
Learning to solve the credit assignment problem, International conference on learning representations, 2020. ,
Mean-field theory of irregularly spiking neuronal populations and working memory in recurrent cortical networks. Computational neuroscience: A comprehensive approach, pp.431-90, 2004. ,
A large-scale model of the functioning brain, science, vol.338, issue.6111, pp.1202-1207, 2012. ,
Efficient codes and balanced networks, Nature neuroscience, vol.19, issue.3, pp.375-82, 2016. ,
Predictive coding of dynamical variables in balanced spiking networks, Plos Computiational Biology, vol.9, issue.11, p.1003258, 2013. ,
Optimal compensation for neuron loss, eLife, vol.5, p.12454, 2016. ,
Neural oscillations as a signature of efficient coding in the presence of synaptic delays, Elife, vol.5, 2016. ,
Chaos in neuronal networks with balanced excitatory and inhibitory activity, Science, vol.274, issue.5293, pp.1724-1730, 1996. ,
Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex, Cerebral cortex, vol.7, issue.3, pp.237-52, 1997. ,
The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding, The Journal of neuroscience, vol.18, issue.10, pp.3870-96, 1998. ,
The asynchronous state in cortical circuits, Science, vol.327, issue.5965, pp.587-90, 2010. ,
Competitive hebbian learning through spike-timing-dependent synaptic plasticity, Nature neuroscience, vol.3, issue.9, pp.919-945, 2000. ,
Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks, Science, vol.334, issue.6062, pp.1569-73, 2011. ,
Connectivity reflects coding: A model of voltage-based stdp with homeostasis, Nature neuroscience, vol.13, issue.3, pp.344-52, 2010. ,
Efficient sensory encoding and bayesian inference with heterogeneous neural populations, Neural Computation, vol.26, issue.10, pp.2103-2137, 2014. ,
Mechanisms of noise robust representation of speech in primary auditory cortex, Proc Natl Acad Sci, vol.111, issue.18, pp.6792-6799, 2014. ,
Rapid spectrotemporal plasticity in primary auditory cortex during behavior, J Neurosci, vol.34, issue.12, pp.4396-408, 2014. ,
Kinetics of endogenous camkii required for synaptic plasticity revealed by optogenetic kinase inhibitor, Neuron, vol.94, issue.1, pp.37-47, 2017. ,
Learning overcomplete representations, Neural computation, vol.12, issue.2, pp.337-65, 2000. ,
Independent component analysis, vol.46, 2004. ,
Simplified neuron model as a principal component analyzer, Journal of mathematical biology, vol.15, issue.3, pp.267-73, 1982. ,
Self-organization in a perceptual network, Computer, vol.21, issue.3, pp.105-122, 1988. ,
A new learning algorithm for blind signal separation, Advances in neural information processing systems, pp.757-63, 1996. ,
A local learning rule that enables information maximization for arbitrary input distributions, Neural Computation, vol.9, issue.8, pp.1661-1666, 1997. ,
A normative theory of adaptive dimensionality reduction in neural networks, Advances in neural information processing systems, pp.2269-77, 2015. ,
A local learning rule for independent component analysis, Scientific reports, vol.6, p.28073, 2016. ,
Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of v1, The Journal of Neuroscience, vol.33, issue.13, pp.5475-85, 2013. ,
Learning universal computations with spikes, PLoS computational biology, vol.12, issue.6, p.1004895, 2016. ,
Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network, Elife, vol.6, p.28295, 2017. ,
Learning nonlinear dynamics in efficient, balanced spiking networks using local plasticity rules, Thirty-second aaai conference on artificial intelligence, pp.588-95, 2018. ,
Learning by the dendritic prediction of somatic spiking, Neuron, vol.81, issue.3, pp.521-529, 2014. ,
The brain as an efficient and robust adaptive learner, Neuron, vol.94, issue.5, pp.969-77, 2017. ,
The statistical reliability of signals in single neurons in cat and monkey visual cortex. Vision research, vol.23, pp.90200-90206, 1983. ,
Statistically optimal perception and learning: From behavior to neural representations, Trends in cognitive sciences, vol.14, issue.3, pp.119-149, 2010. ,
Neural dynamics as sampling: A model for stochastic computation in recurrent networks of spiking neurons, PLoS Comput Biol, vol.7, issue.11, p.1002211, 2011. ,
Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice, Nature, vol.454, issue.7206, pp.881-886, 2008. ,
Membrane potential synchrony in primary visual cortex during sensory stimulation, Neuron, vol.68, issue.6, pp.1187-201, 2010. ,
How inhibition shapes cortical activity, Neuron, vol.72, issue.2, pp.231-274, 2011. ,
Equalizing excitation-inhibition ratios across visual cortical neurons, Nature, vol.511, issue.7511, pp.596-600, 2014. ,
Spike timing-dependent plasticity: A hebbian learning rule, Annu Rev Neurosci, vol.31, pp.25-46, 2008. ,
The spike-timing dependence of plasticity, Neuron, vol.75, issue.4, pp.556-71, 2012. ,