# 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.

Baldassi, Carlo, et al. “Efficient supervised learning in networks with binary synapses..” *Proc Natl Acad Sci U S A*, vol. 104, no. 26, June 2007, pp. 11079–84. *Pubmed*, doi:10.1073/pnas.0700324104.
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Barbieri, Francesca, and Nicolas Brunel. “Irregular persistent activity induced by synaptic excitatory feedback..” *Front Comput Neurosci*, vol. 1, 2007. *Pubmed*, doi:10.3389/neuro.10.005.2007.
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Brunel, Nicolas, and David Hansel. “How noise affects the synchronization properties of recurrent networks of inhibitory neurons..” *Neural Comput*, vol. 18, no. 5, May 2006, pp. 1066–110. *Pubmed*, doi:10.1162/089976606776241048.
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Geisler, Caroline, et al. “Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges..” *J Neurophysiol*, vol. 94, no. 6, Dec. 2005, pp. 4344–61. *Pubmed*, doi:10.1152/jn.00510.2004.
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Roxin, Alex, et al. “Role of delays in shaping spatiotemporal dynamics of neuronal activity in large networks..” *Phys Rev Lett*, vol. 94, no. 23, June 2005. *Pubmed*, doi:10.1103/PhysRevLett.94.238103.
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Boucheny, Christian, et al. “A continuous attractor network model without recurrent excitation: maintenance and integration in the head direction cell system..” *J Comput Neurosci*, vol. 18, no. 2, Mar. 2005, pp. 205–27. *Pubmed*, doi:10.1007/s10827-005-6559-y.
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Brunel, N. *Course 10 Network models of memory*. Vol. 80, no. C, Jan. 2005, pp. 407–76. *Scopus*, doi:10.1016/S0924-8099(05)80016-2.
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Brunel, Nicolas, et al. “Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell..” *Neuron*, vol. 43, no. 5, Sept. 2004, pp. 745–57. *Pubmed*, doi:10.1016/j.neuron.2004.08.023.
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Fourcaud-Trocmé, Nicolas, et al. “How spike generation mechanisms determine the neuronal response to fluctuating inputs..” *J Neurosci*, vol. 23, no. 37, Dec. 2003, pp. 11628–40.

Brunel, Nicolas. “Dynamics and plasticity of stimulus-selective persistent activity in cortical network models..” *Cereb Cortex*, vol. 13, no. 11, Nov. 2003, pp. 1151–61. *Pubmed*, doi:10.1093/cercor/bhg096.
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