
Papers Published

 Bouvier, G; Aljadeff, J; Clopath, C; Bimbard, C; Ranft, J; Blot, A; Nadal, JP; Brunel, N; Hakim, V; Barbour, B, Cerebellar learning using perturbations.,
Elife, vol. 7
(November, 2018) [doi] [abs]
.
 Pereira, U; Brunel, N, Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.,
Neuron, vol. 99 no. 1
(July, 2018),
pp. 227238.e4 [doi] [abs]
.
 Martí, D; Brunel, N; Ostojic, S, Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.,
Physical Review. E, vol. 97 no. 61
(June, 2018),
pp. 062314 [doi] [abs]
.
 Tartaglia, EM; Brunel, N, Bistability and up/down state alternations in inhibitiondominated randomly connected networks of LIF neurons.,
Scientific Reports, vol. 7 no. 1
(September, 2017),
pp. 11916 [doi] [abs]
.
 Titley, HK; Brunel, N; Hansel, C, Toward a Neurocentric View of Learning.,
Neuron, vol. 95 no. 1
(July, 2017),
pp. 1932 [doi] [abs]
.
 Zampini, V; Liu, JK; Diana, MA; Maldonado, PP; Brunel, N; Dieudonné, S, Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit.,
Elife, vol. 5
(September, 2016) [doi] [abs]
.
 Brunel, N, Is cortical connectivity optimized for storing information?,
Nature Neuroscience, vol. 19 no. 5
(May, 2016),
pp. 749755 [doi] [abs]
.
 De Pittà, M; Brunel, N; Volterra, A, Astrocytes: Orchestrating synaptic plasticity?,
Neuroscience, vol. 323
(May, 2016),
pp. 4361 [doi] [abs]
.
 Dubreuil, AM; Brunel, N, Storing structured sparse memories in a multimodular cortical network model.,
Journal of Computational Neuroscience, vol. 40 no. 2
(April, 2016),
pp. 157175 [doi] [abs]
.
 Bouvier, G; Higgins, D; Spolidoro, M; Carrel, D; Mathieu, B; Léna, C; Dieudonné, S; Barbour, B; Brunel, N; Casado, M, BurstDependent Bidirectional Plasticity in the Cerebellum Is Driven by Presynaptic NMDA Receptors.,
Cell Reports, vol. 15 no. 1
(April, 2016),
pp. 104116 [doi] [abs]
.
 De Pittà, M; Brunel, N, Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study.,
Neural Plasticity, vol. 2016
(January, 2016),
pp. 7607924 [doi] [abs]
.
 Lim, S; McKee, JL; Woloszyn, L; Amit, Y; Freedman, DJ; Sheinberg, DL; Brunel, N, Inferring learning rules from distributions of firing rates in cortical neurons.,
Nature Neuroscience, vol. 18 no. 12
(December, 2015),
pp. 18041810 [doi] [abs]
.
 Alemi, A; Baldassi, C; Brunel, N; Zecchina, R, A ThreeThreshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.,
Plos Computational Biology, vol. 11 no. 8
(August, 2015),
pp. e1004439 [doi] [abs]
.
 Ostojic, S; Szapiro, G; Schwartz, E; Barbour, B; Brunel, N; Hakim, V, Neuronal morphology generates highfrequency firing resonance.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 35 no. 18
(May, 2015),
pp. 70567068 [doi] [abs]
.
 Tartaglia, EM; Brunel, N; Mongillo, G, Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.,
Plos Computational Biology, vol. 11 no. 2
(February, 2015),
pp. e1004059 [doi] [abs]
.
 Higgins, D; Graupner, M; Brunel, N, Memory maintenance in synapses with calciumbased plasticity in the presence of background activity.,
Plos Computational Biology, vol. 10 no. 10
(October, 2014),
pp. e1003834 [doi] [abs]
.
 Barbieri, F; Mazzoni, A; Logothetis, NK; Panzeri, S; Brunel, N, Stimulus dependence of local field potential spectra: experiment versus theory.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 34 no. 44
(October, 2014),
pp. 1458914605 [doi] [abs]
.
 Dubreuil, AM; Amit, Y; Brunel, N, Memory capacity of networks with stochastic binary synapses.,
Plos Computational Biology, vol. 10 no. 8
(August, 2014),
pp. e1003727 [doi] [abs]
.
 Clopath, C; Badura, A; De Zeeuw, CI; Brunel, N, A cerebellar learning model of vestibuloocular reflex adaptation in wildtype and mutant mice.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 34 no. 21
(May, 2014),
pp. 72037215 [doi] [abs]
.
 Brunel, N; Hakim, V; Richardson, MJE, Single neuron dynamics and computation.,
Current Opinion in Neurobiology, vol. 25
(April, 2014),
pp. 149155 [doi] [abs]
.
 Hertäg, L; Durstewitz, D; Brunel, N, Analytical approximations of the firing rate of an adaptive exponential integrateandfire neuron in the presence of synaptic noise.,
Frontiers in Computational Neuroscience, vol. 8
(January, 2014),
pp. 116 [doi] [abs]
.
 Tartaglia, EM; Mongillo, G; Brunel, N, On the relationship between persistent delay activity, repetition enhancement and priming.,
Frontiers in Psychology, vol. 5
(January, 2014),
pp. 1590 [doi] [abs]
.
 Brunel, N; Hakim, V, Population Density Models.,
in Encyclopedia of Computational Neuroscience, edited by Jaeger, D; Jung, R
(2014), SPRINGER [doi] .
 Brunel, N; Hakim, V, FokkerPlanck Equation.,
in Encyclopedia of Computational Neuroscience, edited by Jaeger, D; Jung, R
(2014), SPRINGER [doi] .
 Clopath, C; Brunel, N, Optimal properties of analog perceptrons with excitatory weights.,
Plos Computational Biology, vol. 9 no. 2
(January, 2013),
pp. e1002919 [doi] [abs]
.
 Brunel, N, Dynamics of neural networks,
in Principles of Neural Coding
(January, 2013),
pp. 489512 [doi] [abs]
.
 Graupner, M; Brunel, N, Calciumbased plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location.,
Proceedings of the National Academy of Sciences of the United States of America, vol. 109 no. 10
(March, 2012),
pp. 39913996 [doi] [abs]
.
 Clopath, C; Nadal, JP; Brunel, N, Storage of correlated patterns in standard and bistable Purkinje cell models.,
Plos Computational Biology, vol. 8 no. 4
(January, 2012),
pp. e1002448 [doi] [abs]
.
 Roxin, A; Brunel, N; Hansel, D; Mongillo, G; van Vreeswijk, C, On the distribution of firing rates in networks of cortical neurons.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 31 no. 45
(November, 2011),
pp. 1621716226 [doi] [abs]
.
 Ostojic, S; Brunel, N, From spiking neuron models to linearnonlinear models.,
Plos Computational Biology, vol. 7 no. 1
(January, 2011),
pp. e1001056 [doi] [abs]
.
 Ledoux, E; Brunel, N, Dynamics of networks of excitatory and inhibitory neurons in response to timedependent inputs.,
Frontiers in Computational Neuroscience, vol. 5
(January, 2011),
pp. 25 [doi] [abs]
.
 Mazzoni, A; Brunel, N; Cavallari, S; Logothetis, NK; Panzeri, S, Cortical dynamics during naturalistic sensory stimulations: experiments and models.,
Journal of Physiology, Paris, vol. 105 no. 13
(January, 2011),
pp. 215 [doi] [abs]
.
 Hamaguchi, K; Riehle, A; Brunel, N, Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons.,
Journal of Neurophysiology, vol. 105 no. 1
(January, 2011),
pp. 487500 [doi] [abs]
.
 Mazzoni, A; Whittingstall, K; Brunel, N; Logothetis, NK; Panzeri, S, Understanding the relationships between spike rate and delta/gamma frequency bands of LFPs and EEGs using a local cortical network model.,
Neuroimage, vol. 52 no. 3
(September, 2010),
pp. 956972 [doi] [abs]
.
 Panzeri, S; Brunel, N; Logothetis, NK; Kayser, C, Sensory neural codes using multiplexed temporal scales.,
Trends in Neurosciences, vol. 33 no. 3
(March, 2010),
pp. 111120 [doi] [abs]
.
 Graupner, M; Brunel, N, Mechanisms of induction and maintenance of spiketiming dependent plasticity in biophysical synapse models.,
Frontiers in Computational Neuroscience, vol. 4
(January, 2010) [doi] [abs]
.
 Brunel, N; Lavigne, F, Semantic priming in a cortical network model.,
Journal of Cognitive Neuroscience, vol. 21 no. 12
(December, 2009),
pp. 23002319 [doi] [abs]
.
 Ostojic, S; Brunel, N; Hakim, V, How connectivity, background activity, and synaptic properties shape the crosscorrelation between spike trains.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 29 no. 33
(August, 2009),
pp. 1023410253 [doi] [abs]
.
 Ostojic, S; Brunel, N; Hakim, V, Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.,
Journal of Computational Neuroscience, vol. 26 no. 3
(June, 2009),
pp. 369392 [doi] [abs]
.
 Zillmer, R; Brunel, N; Hansel, D, Very long transients, irregular firing, and chaotic dynamics in networks of randomly connected inhibitory integrateandfire neurons.,
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, vol. 79 no. 3 Pt 1
(March, 2009),
pp. 031909 [doi] [abs]
.
 Dugué, GP; Brunel, N; Hakim, V; Schwartz, E; Chat, M; Lévesque, M; Courtemanche, R; Léna, C; Dieudonné, S, Electrical coupling mediates tunable lowfrequency oscillations and resonance in the cerebellar Golgi cell network.,
Neuron, vol. 61 no. 1
(January, 2009),
pp. 126139 [doi] [abs]
.
 Graupner, M; Brunel, N, A bitable synaptic model with transitions between states induced by calcium dynamics: theory vs experiment,
Bmc Neuroscience, vol. 10 no. Suppl 1
(2009),
pp. O15O15 [doi] .
 Brunel, N; Hakim, V, Neuronal Dynamics.,
in Encyclopedia of Complexity and Systems Science, edited by Meyers, RA
(2009),
pp. 60996116, SPRINGER [doi] .
 Mazzoni, A; Panzeri, S; Logothetis, NK; Brunel, N, Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons.,
Plos Computational Biology, vol. 4 no. 12
(December, 2008),
pp. e1000239 [doi] [abs]
.
 Roxin, A; Hakim, V; Brunel, N, The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 28 no. 42
(October, 2008),
pp. 1073410745 [doi] [abs]
.
 Barbieri, F; Brunel, N, Can attractor network models account for the statistics of firing during persistent activity in prefrontal cortex?,
Frontiers in Neuroscience, vol. 2 no. 1
(July, 2008),
pp. 114122 [doi] [abs]
.
 de Solages, C; Szapiro, G; Brunel, N; Hakim, V; Isope, P; Buisseret, P; Rousseau, C; Barbour, B; Léna, C, Highfrequency organization and synchrony of activity in the purkinje cell layer of the cerebellum.,
Neuron, vol. 58 no. 5
(June, 2008),
pp. 775788 [doi] [abs]
.
 Brunel, N; Hakim, V, Sparsely synchronized neuronal oscillations.,
Chaos (Woodbury, N.Y.), vol. 18 no. 1
(March, 2008),
pp. 015113 [doi] [abs]
.
 Brunel, N, Daniel Amit (19382007).,
Network: Computation in Neural Systems, vol. 19 no. 1
(January, 2008),
pp. 38 [doi] .
 Battaglia, D; Brunel, N; Hansel, D, Temporal decorrelation of collective oscillations in neural networks with local inhibition and longrange excitation.,
Physical Review Letters, vol. 99 no. 23
(December, 2007),
pp. 238106 [doi] [abs]
.
 Barbour, B; Brunel, N; Hakim, V; Nadal, JP, What can we learn from synaptic weight distributions?,
Trends in Neurosciences, vol. 30 no. 12
(December, 2007),
pp. 622629 [doi] [abs]
.
 Brunel, N; van Rossum, MCW, Lapicque's 1907 paper: from frogs to integrateandfire.,
Biological Cybernetics, vol. 97 no. 56
(December, 2007),
pp. 337339 [doi] [abs]
.
 Graupner, M; Brunel, N, STDP in a bistable synapse model based on CaMKII and associated signaling pathways.,
Plos Computational Biology, vol. 3 no. 11
(November, 2007),
pp. e221 [doi] [abs]
.
 Baldassi, C; Braunstein, A; Brunel, N; Zecchina, R, Efficient supervised learning in networks with binary synapses.,
Proceedings of the National Academy of Sciences of the United States of America, vol. 104 no. 26
(June, 2007),
pp. 1107911084 [doi] [abs]
.
 Barbieri, F; Brunel, N, Irregular persistent activity induced by synaptic excitatory feedback.,
Frontiers in Computational Neuroscience, vol. 1
(January, 2007),
pp. 5 [doi] [abs]
.
 Brunel, N; Hansel, D, How noise affects the synchronization properties of recurrent networks of inhibitory neurons.,
Neural Computation, vol. 18 no. 5
(May, 2006),
pp. 10661110 [doi] [abs]
.
 Roxin, A; Brunel, N; Hansel, D, Rate Models with Delays and the Dynamics of Large Networks of Spiking Neurons,
Progress of Theoretical Physics Supplement, vol. 161
(2006),
pp. 6885 [doi] .
 Brunel, N, Course 10 Network models of memory,
Les Houches, vol. 80 no. C
(December, 2005),
pp. 407476 [doi] .
 Geisler, C; Brunel, N; Wang, XJ, Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges.,
Journal of Neurophysiology, vol. 94 no. 6
(December, 2005),
pp. 43444361 [doi] [abs]
.
 Roxin, A; Brunel, N; Hansel, D, Role of delays in shaping spatiotemporal dynamics of neuronal activity in large networks.,
Physical Review Letters, vol. 94 no. 23
(June, 2005),
pp. 238103 [doi] [abs]
.
 FourcaudTrocmé, N; Brunel, N, Dynamics of the instantaneous firing rate in response to changes in input statistics.,
Journal of Computational Neuroscience, vol. 18 no. 3
(June, 2005),
pp. 311321 [doi] [abs]
.
 Boucheny, C; Brunel, N; Arleo, A, A continuous attractor network model without recurrent excitation: maintenance and integration in the head direction cell system.,
Journal of Computational Neuroscience, vol. 18 no. 2
(March, 2005),
pp. 205227 [doi] [abs]
.
 Brunel, N; Hakim, V; Isope, P; Nadal, JP; Barbour, B, Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.,
Neuron, vol. 43 no. 5
(September, 2004),
pp. 745757 [doi] [abs]
.
 FourcaudTrocmé, N; Hansel, D; van Vreeswijk, C; Brunel, N, How spike generation mechanisms determine the neuronal response to fluctuating inputs.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 23 no. 37
(December, 2003),
pp. 1162811640 [doi] [abs]
.
 Brunel, N, Dynamics and plasticity of stimulusselective persistent activity in cortical network models.,
Cerebral Cortex (New York, N.Y. : 1991), vol. 13 no. 11
(November, 2003),
pp. 11511161 [doi] [abs]
.
 Mongillo, G; Amit, DJ; Brunel, N, Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network.,
The European Journal of Neuroscience, vol. 18 no. 7
(October, 2003),
pp. 20112024 [doi] [abs]
.
 Brunel, N; Latham, PE, Firing rate of the noisy quadratic integrateandfire neuron.,
Neural Computation, vol. 15 no. 10
(October, 2003),
pp. 22812306 [doi] [abs]
.
 Brunel, N; Frégnac, Y; Meunier, C; Nadal, JP, Neuroscience and computation.,
Journal of Physiology, Paris, vol. 97 no. 46
(July, 2003),
pp. 387390 [doi] .
 Brunel, N; Wang, XJ, What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitationinhibition balance.,
Journal of Neurophysiology, vol. 90 no. 1
(July, 2003),
pp. 415430 [doi] [abs]
.
 Brunel, N; Hakim, V; Richardson, MJE, Firingrate resonance in a generalized integrateandfire neuron with subthreshold resonance.,
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, vol. 67 no. 5 Pt 1
(May, 2003),
pp. 051916 [doi] [abs]
.
 Richardson, MJE; Brunel, N; Hakim, V, From subthreshold to firingrate resonance.,
Journal of Neurophysiology, vol. 89 no. 5
(May, 2003),
pp. 25382554 [doi] [abs]
.
 Fourcaud, N; Brunel, N, Dynamics of the firing probability of noisy integrateandfire neurons.,
Neural Computation, vol. 14 no. 9
(September, 2002),
pp. 20572110 [doi] [abs]
.
 Brunel, N; Wang, XJ, Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition.,
Journal of Computational Neuroscience, vol. 11 no. 1
(July, 2001),
pp. 6385 [doi] [abs]
.
 Brunel, N; Chance, FS; Fourcaud, N; Abbott, LF, Effects of synaptic noise and filtering on the frequency response of spiking neurons.,
Physical Review Letters, vol. 86 no. 10
(March, 2001),
pp. 21862189 [doi] [abs]
.
 Brunel, N, Persistent activity and the singlecell frequencycurrent curve in a cortical network model.,
Network: Computation in Neural Systems, vol. 11 no. 4
(November, 2000),
pp. 261280 [doi] [abs]
.
 Compte, A; Brunel, N; GoldmanRakic, PS; Wang, XJ, Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model.,
Cerebral Cortex (New York, N.Y. : 1991), vol. 10 no. 9
(September, 2000),
pp. 910923 [doi] [abs]
.
 Brunel, N, Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons.,
Journal of Physiology, Paris, vol. 94 no. 56
(September, 2000),
pp. 445463 [doi] [abs]
.
 Brunel, N, Phase diagrams of sparsely connected networks of excitatory and inhibitory spiking neurons,
Neurocomputing, vol. 3233
(June, 2000),
pp. 307312 [doi] .
 Brunel, N, Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.,
Journal of Computational Neuroscience, vol. 8 no. 3
(May, 2000),
pp. 183208 [doi] [abs]
.
 Brunel, N; Wang, XJ, Fast network oscillations with intermittent principal cell firing in a model of a recurrent excitatoryinhibitory circuit,
The European Journal of Neuroscience, vol. 12
(2000),
pp. 7979 .
 Brunel, N; Hakim, V, Fast global oscillations in networks of integrateandfire neurons with low firing rates.,
Neural Computation, vol. 11 no. 7
(October, 1999),
pp. 16211671 [doi] [abs]
.
 Brunel, N; Trullier, O, Plasticity of directional place fields in a model of rodent CA3,
Hippocampus, vol. 8 no. 6
(December, 1998),
pp. 651665 [doi] [abs]
.
 Brunel, N; Sergi, S, Firing frequency of leaky intergrateandfire neurons with synaptic current dynamics.,
Journal of Theoretical Biology, vol. 195 no. 1
(November, 1998),
pp. 8795 [doi] [abs]
.
 Brunel, N; Nadal, JP, Mutual information, Fisher information, and population coding.,
Neural Computation, vol. 10 no. 7
(October, 1998),
pp. 17311757 [doi] [abs]
.
 Nadal, JP; Brunel, N; Parga, N, Nonlinear feedforward networks with stochastic outputs: infomax implies redundancy reduction.,
Network: Computation in Neural Systems, vol. 9 no. 2
(May, 1998),
pp. 207217 [doi] [abs]
.
 Brunel, N; Nadal, JP, Modeling memory: what do we learn from attractor neural networks?,
Comptes Rendus Biologies, vol. 321 no. 23
(February, 1998),
pp. 249252 [doi] [abs]
.
 Brunel, N; Carusi, F; Fusi, S, Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network.,
Network: Computation in Neural Systems, vol. 9 no. 1
(February, 1998),
pp. 123152 [doi] [abs]
.
 Brunel, N; Trullier, O, Plasticity of directional place fields in a model of rodent CA3.,
Hippocampus, vol. 8 no. 6
(January, 1998),
pp. 651665 [doi] [abs]
.
 Amit, D; Brunel, N, Dynamics of a recurrent network of spiking neurons before and following learning,
Network: Computation in Neural Systems, vol. 8 no. 4
(November, 1997),
pp. 373404 [doi] .
 Brunel, N; Ninio, J, Time to detect the difference between two images presented side by side.,
Brain Research. Cognitive Brain Research, vol. 5 no. 4
(June, 1997),
pp. 273282 [doi] [abs]
.
 Amit, DJ; Brunel, N, Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex.,
Cerebral Cortex (New York, N.Y. : 1991), vol. 7 no. 3
(April, 1997),
pp. 237252 [doi] [abs]
.
 Brunel, N, Crosscorrelations in sparsely connected recurrent networks of spiking neurons,
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1327
(January, 1997),
pp. 3136 [abs]
.
 Brunel, N; Nadal, JP, Optimal tuning curves for neurons spiking as a Poisson process., edited by Verleysen, M,
ESANN
(1997), DFacto public .
 Brunel, N, Hebbian learning of context in recurrent neural networks.,
Neural Computation, vol. 8 no. 8
(November, 1996),
pp. 16771710 [doi] [abs]
.
 Ninio, J; Brunel, N, Time to detect a single difference between two correlated images,
Perception, vol. 25
(1996),
pp. 8989 .
 BRUNEL, N; ZECCHINA, R, A SIMPLE GEOMETRICAL BOUND FOR REPLICA SYMMETRY STABILITY IN NEURAL NETWORKS MODELS,
Modern Physics Letters B, vol. 09 no. 18
(August, 1995),
pp. 11591164 [doi] .
 Amit†, D; Brunel, N, Learning internal representations in an attractor neural network with analogue neurons,
Network: Computation in Neural Systems, vol. 6 no. 3
(August, 1995),
pp. 359388 [doi] .
 Amit, DJ; Brunel, N, Learning internal representations in an attractor neural network with analogue neurons,
Network: Computation in Neural Systems, vol. 6 no. 3
(January, 1995),
pp. 359388 [doi] .
 Brunel, N; Amit, DJ, Learning internal representations in an analog attractor neural network,
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995
(1995),
pp. 1923 .
 Brunel, N, Quantitative modeling of local Hebbian reverberations in primate cortex,
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995
(1995),
pp. 1317 .
 Amit, D; Brunel, N; Tsodyks, M, Correlations of cortical Hebbian reverberations: theory versus experiment,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 14 no. 11
(November, 1994),
pp. 64356445 [doi] [abs]
.
 Brunel, N, Dynamics of an attractor neural network converting temporal into spatial correlations,
Network: Computation in Neural Systems, vol. 5 no. 4
(November, 1994),
pp. 449470 [doi] .
 Amit, DJ; Brunel, N; Tsodyks, MV, Correlations of cortical Hebbian reverberations: theory versus experiment.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 14 no. 11 Pt 1
(November, 1994),
pp. 64356445 [abs]
.
 Brunel, N, Storage capacity of neural networks: effect of the fluctuations of the number of active neurons per memory,
Journal of Physics A: Mathematical and General, vol. 27 no. 14
(July, 1994),
pp. 47834789 [doi] .
 Brunel, N; Zecchina, R, Response functions improving performance in analog attractor neural networks.,
Physical Review E Statistical, Nonlinear, and Soft Matter Physics, vol. 49 no. 3
(March, 1994),
pp. R1823R1826 [doi] .
 Brunel, N, Dynamics of an attractor neural network converting temporal into spatial correlations,
Network: Computation in Neural Systems, vol. 5 no. 4
(January, 1994),
pp. 449470 [doi] .
 Brunel, N, Effect of synapse dilution on the memory retrieval in structured attractor neural networks,
Journal De Physique I, vol. 3 no. 8
(August, 1993),
pp. 16931715 [doi] .
 Amit, DJ; Brunel, N, Adequate input for learning in attractor neural networks,
Network: Computation in Neural Systems, vol. 4 no. 2
(January, 1993),
pp. 177194 [doi] .
 Brunel, N; Nadal, JP; Toulouse, G, Information capacity of a perceptron,
Journal of Physics A: Mathematical and General, vol. 25 no. 19
(October, 1992),
pp. 50175038 [doi] .