Nicolas Brunel
Affiliations: | 2017- | Neurobiology, Physics | Duke univeristy, Durham, NC, United States |
Area:
Computational neuroscienceGoogle:
"Nicolas Brunel"Mean distance: 13.7 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| Jean-Pierre Nadal | grad student | ENS Paris | |
| Daniel Amit | post-doc | Università di Roma La Sapienza | |
| Xiao-Jing Wang | research scientist | Brandeis |
Children
Sign in to add trainee| Michael Graupner | grad student | University of Paris V and CNRS | |
| Ulises Pereira Obilinovic | grad student | 2013-2018 | Chicago |
| Claudia Clopath | post-doc | CNRS, Université Paris V | |
| Jian K. Liu | post-doc | ||
| Alberto Mazzoni | post-doc | ||
| Magnus Richardson | post-doc | University of Warwick, UK | |
| Alex Roxin | post-doc | Columbia | |
| Maurizio De Pittà | post-doc | 2015- | Chicago |
| Ruediger Zillmer | post-doc | 2006-2007 | (Physics Tree) |
| Demian Battaglia | post-doc | 2005-2008 | University of Paris V and CNRS |
| Kosuke Hamaguchi | post-doc | 2006-2008 | University of Paris V and CNRS |
| Srdjan Ostojic | post-doc | 2006-2009 | ENS Paris |
| Alireza Alemi | post-doc | 2013-2015 | |
| Frederic Lavigne | research scientist | Université Paris 5 - CNRS |
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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 |
| 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 |
| Riordan B, Dye M, Jones MN. (2015) Grammatical number processing and anticipatory eye movements are not tightly coordinated in English spoken language comprehension. Frontiers in Psychology. 6: 590 |