Chaos in random neural networks, Phys. Rev. Lett, vol.61, p.10039285, 1988. ,
DOI : 10.1103/physrevlett.61.259
Suppressing chaos in neural networks by noise, Phys. Rev. Lett, vol.69, p.10046895, 1992. ,
Mean-field equations, bifurcation map and route to chaos in discrete time neural networks, Physica D: Nonlinear Phenomena, vol.74, pp.90024-90032, 1994. ,
Destabilization and route to chaos in neural networks with random connectivity, Advances in Neural Information Processing Systems, vol.5, pp.549-555, 1993. ,
State-dependent computations: spatiotemporal processing in cortical networks, Nature Review Neuroscience, vol.10, p.19145235, 2009. ,
Generating coherent patterns of activity from chaotic neural networks, Neuron, vol.63, p.19709635, 2009. ,
Robust timing and motor patterns by taming chaos in recurrent neural networks, Nature Neuroscience, vol.16, p.23708144, 2013. ,
Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks, Neural Comput, vol.5, issue.3, p.23272922, 2013. ,
Topological and dynamical complexity of random neural networks, Phys. Rev. Lett, vol.110, p.25166580, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00942212
Beyond the edge of chaos: amplification and temporal integration by recurrent networks in the chaotic regime, Phys. Rev. E, vol.84, p.22181445, 2011. ,
Stimulus-dependent suppression of chaos in recurrent neural networks, Phys. Rev. E, vol.82, p.11903, 2010. ,
Transition to chaos in random networks with cell-type-specific connectivity, Phys. Rev. Lett, vol.114, p.25768781, 2015. ,
DOI : 10.1103/physrevlett.114.088101
URL : https://link.aps.org/accepted/10.1103/PhysRevLett.114.088101
, On the low dimensional dynamics of structured random networks, 2015.
Dynamics of random neural networks with bistable units, Phys. Rev. E, vol.90, p.25615132, 2014. ,
, Noise dynamically suppresses chaos in random neural networks, 2016.
Transition to chaos in random neuronal networks, Phys. Rev. X, vol.5, p.4103, 2015. ,
Asynchronous rate chaos in spiking neuronal circuits, PLOS Comput. Biol, vol.11, issue.7, p.26230679, 2015. ,
Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons, Journal of Computational Neuroscience, vol.8, p.10809012, 2000. ,
Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons, Nature Neuroscience, vol.17, p.24561997, 2014. ,
Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons, 2015. ,
Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons, 2015. ,
Non-normal amplification in random balanced neuronal networks, Physical Review E, vol.86, p.11909, 2012. ,
Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements, Neuron, vol.82, p.24945778, 2014. ,
Physiological Gain Leads to High ISI Variability in a Simple Mo del of a Cortical Regular Spiking Cell, Neural Computation, vol.9, p.9188190, 1997. ,
Balanced amplification: a new mechanism of selective amplification of neural activity patterns, Neuron, vol.61, p.19249282, 2009. ,
Analysis of the stabilized supralinear network, Neural Computation. 25-8, 1994. ,
The stabilized supralinear network: a unifying circuit motif underlying multi-input integration in sensory cortex, Neuron, vol.85, p.25611511, 2015. ,
, Nonlinear Dynamics and Chaos: With Applications to Physics, 2007.
Eigenvalue spectra of random matrices for neural networks, Phys. Rev. Lett, vol.97, p.17155583, 2006. ,
Random matrices: Universality of ESDs and the circular law, The Annals of Probability, vol.38, pp.2023-2065, 2010. ,
Outliers in the spectrum of iid matrices with bounded rank perturbations, Probab. Theory Related Fields, vol.155, pp.231-263, 2013. ,
Relaxational dynamics of the Edwards-Anderson model and the meanfield theory of spin-glasses, Phys. Rev. B, vol.25, p.6860, 1982. ,
Large deviations for Langevin spin glass dynamics, The Annals of Probability, vol.102, pp.455-509, 1995. ,
DOI : 10.1007/bf01198846
Eigenvalues of block structured asymmetric random matrices, Journal of Mathematical Physics, 2015. ,
On the 1st passage time probability problem, Phys. Rev, vol.81, pp.617-623, 1951. ,
DOI : 10.1103/physrev.81.617
Fast global oscillations in networks of integrate-and-fire neurons with low firing rates, Neural Comput, vol.11, pp.1621-1671, 1999. ,
From Spiking Neuron Models to Linear-Nonlinear Models, PLoS Comput. Biol, vol.7, issue.1, p.21283777, 2011. ,
DOI : 10.1371/journal.pcbi.1001056
URL : https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1001056&type=printable
A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks, PLoS Comput. Biol, vol.9, issue.10, p.24204236, 2013. ,
Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex, Cereb. Cortex, vol.7, issue.3, p.9143444, 1997. ,
Interspike interval distributions of spiking neurons driven by fluctuating inputs, J. Neurophysiol, vol.106, p.21525364, 2011. ,
DOI : 10.1152/jn.00830.2010
How well do mean field theories of spiking quadratic-integrateand-fire networks work in realistic parameter regimes?, J. Comput. Neurosci, vol.36, p.24091644, 2014. ,
Effects of synaptic noise and filtering on the frequency response of spiking neurons, Phys Rev Lett, vol.86, p.11289886, 2001. ,
Rate models for conductance-based cortical neuronal networks, Neural Comput, vol.15, p.14511514, 2003. ,
DOI : 10.1162/08997660360675053
URL : https://hal.archives-ouvertes.fr/hal-00173803
Mean field theory for a balanced hypercolumn model of orientation selectivity in primary visual cortex, Network: Computation in Neural Systems, vol.17, p.16818394, 2006. ,
Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity, Frontiers in Computational Neuroscience, vol.8, p.25278869, 2014. ,
Slow fluctuations in recurrent networks of spiking neurons, Phys. Rev. E, vol.92, p.26565154, 2015. ,
, Decorrelation of Neural-Network Activity by Inhibitory Feedback, vol.8, p.23133368, 2012.
Recurrent interactions in spiking networks with arbitrary topology, Phys. Rev. E, vol.85, p.31916, 2012. ,
DOI : 10.1103/physreve.85.031916
URL : http://arxiv.org/pdf/1201.0288