Nicolas Brunel

Affiliations: 
University of Paris V and CNRS, Paris, Île-de-France, France 
Area:
Computational neuroscience
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"Nicolas Brunel"
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Publications

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Bouvier G, Aljadeff J, Clopath C, et al. (2018) Cerebellar learning using perturbations. Elife. 7
Martí D, Brunel N, Ostojic S. (2018) Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks. Physical Review. E. 97: 062314
Pereira U, Brunel N. (2018) Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data. Neuron
Tartaglia EM, Brunel N. (2017) Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons. Scientific Reports. 7: 11916
Zampini V, Liu JK, Diana MA, et al. (2016) Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit. Elife. 5
De Pittà M, Brunel N. (2016) Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study. Neural Plasticity. 2016: 7607924
Bouvier G, Higgins D, Spolidoro M, et al. (2016) Burst-Dependent Bidirectional Plasticity in the Cerebellum Is Driven by Presynaptic NMDA Receptors. Cell Reports. 15: 104-16
Dubreuil AM, Brunel N. (2016) Storing structured sparse memories in a multi-modular cortical network model. Journal of Computational Neuroscience
Lim S, McKee JL, Woloszyn L, et al. (2015) Inferring learning rules from distributions of firing rates in cortical neurons. Nature Neuroscience
Alemi A, Baldassi C, Brunel N, et al. (2015) A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks. Plos Computational Biology. 11: e1004439
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