# Nicolas Brunel

## Professor of Neurobiology

### Overview

We use theoretical models of brain systems to investigate how they process and learn information from their inputs. Our current work focuses on the mechanisms of learning and memory, from the synapse to the network level, in collaboration with various experimental groups. Using methods from

statistical physics, we have shown recently that the synaptic

connectivity of a network that maximizes storage capacity reproduces

two key experimentally observed features: low connection probability

and strong overrepresentation of bidirectionnally connected pairs of

neurons. We have also inferred `synaptic plasticity rules' (a

mathematical description of how synaptic strength depends on the

activity of pre and post-synaptic neurons) from data, and shown that

networks endowed with a plasticity rule inferred from data have a

storage capacity that is close to the optimal bound.

Compte, A., et al. “Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model..” *Cereb Cortex*, vol. 10, no. 9, Sept. 2000, pp. 910–23. *Pubmed*, doi:10.1093/cercor/10.9.910.
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Brunel, N. “Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons..” *J Comput Neurosci*, vol. 8, no. 3, May 2000, pp. 183–208. *Pubmed*, doi:10.1023/a:1008925309027.
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Brunel, N., and V. Hakim. “Fast global oscillations in networks of integrate-and-fire neurons with low firing rates..” *Neural Comput*, vol. 11, no. 7, Oct. 1999, pp. 1621–71. *Pubmed*, doi:10.1162/089976699300016179.
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Brunel, N., and S. Sergi. “Firing frequency of leaky intergrate-and-fire neurons with synaptic current dynamics..” *J Theor Biol*, vol. 195, no. 1, Nov. 1998, pp. 87–95. *Pubmed*, doi:10.1006/jtbi.1998.0782.
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Brunel, N., and J. P. Nadal. “Mutual information, Fisher information, and population coding..” *Neural Comput*, vol. 10, no. 7, Oct. 1998, pp. 1731–57. *Pubmed*, doi:10.1162/089976698300017115.
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Nadal, J. P., et al. “Nonlinear feedforward networks with stochastic outputs: infomax implies redundancy reduction..” *Network*, vol. 9, no. 2, May 1998, pp. 207–17.

Brunel, N., et al. “Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network..” *Network*, vol. 9, no. 1, Feb. 1998, pp. 123–52.

Brunel, N., and O. Trullier. “Plasticity of directional place fields in a model of rodent CA3..” *Hippocampus*, vol. 8, no. 6, 1998, pp. 651–65. *Pubmed*, doi:10.1002/(SICI)1098-1063(1998)8:6<651::AID-HIPO8>3.0.CO;2-L.
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Brunel, N., and J. Ninio. “Time to detect the difference between two images presented side by side..” *Brain Res Cogn Brain Res*, vol. 5, no. 4, June 1997, pp. 273–82. *Pubmed*, doi:10.1016/s0926-6410(97)00003-7.
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Amit, D. J., and N. Brunel. “Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex..” *Cereb Cortex*, vol. 7, no. 3, Apr. 1997, pp. 237–52. *Pubmed*, doi:10.1093/cercor/7.3.237.
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