Nicolas Brunel

Nicolas Brunel

Professor of Neurobiology

Professor of Physics (Joint)

Member of the Center for Cognitive Neuroscience

Faculty Network Member of the Duke Institute for Brain Sciences

Office Location: 
311 Research Drive, Durham, NC 27710
(919) 684-8684


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.

Education & Training

  • Ph.D., Pierre and Marie Curie University (France) 1993

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. Full Text

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. Full Text

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. Full Text

Mongillo, Gianluigi, et al. “Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network.Eur J Neurosci, vol. 18, no. 7, Oct. 2003, pp. 2011–24. Pubmed, doi:10.1046/j.1460-9568.2003.02908.x. Full Text

Brunel, Nicolas, and Peter E. Latham. “Firing rate of the noisy quadratic integrate-and-fire neuron.Neural Comput, vol. 15, no. 10, Oct. 2003, pp. 2281–306. Pubmed, doi:10.1162/089976603322362365. Full Text

Brunel, Nicolas, et al. “Neuroscience and computation.J Physiol Paris, vol. 97, no. 4–6, July 2003, pp. 387–90. Pubmed, doi:10.1016/j.jphysparis.2004.02.001. Full Text

Brunel, Nicolas, and Xiao-Jing Wang. “What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance.J Neurophysiol, vol. 90, no. 1, July 2003, pp. 415–30. Pubmed, doi:10.1152/jn.01095.2002. Full Text

Brunel, Nicolas, et al. “Firing-rate resonance in a generalized integrate-and-fire neuron with subthreshold resonance.Phys Rev E Stat Nonlin Soft Matter Phys, vol. 67, no. 5 Pt 1, May 2003, p. 051916. Pubmed, doi:10.1103/PhysRevE.67.051916. Full Text

Richardson, Magnus J. E., et al. “From subthreshold to firing-rate resonance.J Neurophysiol, vol. 89, no. 5, May 2003, pp. 2538–54. Pubmed, doi:10.1152/jn.00955.2002. Full Text