Nicolas Brunel

Nicolas Brunel

Professor of Neurobiology

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

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.

Education & Training

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

Selected Grants

Striatal Plasticity in Habit Formation as a Platform to Deconstruct Adaptive Learning awarded by National Institutes of Health (Co Investigator). 2018 to 2023

CRCNS: Multiscale dynamics of cortical circuits for visual recognition & memory awarded by University of Chicago (Principal Investigator). 2017 to 2022

An Integrated Nonparametric Bayesian and Deep Neural Network Framework for Biologically-Inspired Lifelong Learning awarded by Defense Advanced Research Projects Agency (Co Investigator). 2018 to 2020

Learning spatio-temporal statistics from the environment in recurrent networks awarded by Office of Naval Research (Principal Investigator). 2017 to 2019

Learning spatio-temporal statistics from the environment in recurrent networks awarded by University of Texas Health Science Center at Houston (Principal Investigator). 2017 to 2019

Large-scale, neuronal ensemble recordings in motor cortex of the behaving marmoset awarded by University of Chicago (Principal Investigator). 2018

Brunel, N, and Hakim, V. "Population Density Models." Encyclopedia of Computational Neuroscience. Ed. D Jaeger and R Jung. Springer, 2014.

Brunel, N, and Hakim, V. "Fokker-Planck Equation." Encyclopedia of Computational Neuroscience. Ed. D Jaeger and R Jung. Springer, 2014.

Brunel, N, and Hakim, V. "Neuronal Dynamics." Encyclopedia of Complexity and Systems Science. Ed. RA Meyers. Springer, 2009. 6099-6116.

Pereira, U, and Brunel, N. "Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data." Neuron 99.1 (July 2018): 227-238.e4. Full Text

Tartaglia, EM, and Brunel, N. "Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons." Scientific Reports 7.1 (September 20, 2017): 11916-null. Full Text

Titley, HK, Brunel, N, and Hansel, C. "Toward a Neurocentric View of Learning." Neuron 95.1 (July 2017): 19-32. (Review) Full Text

Zampini, V, Liu, JK, Diana, MA, Maldonado, PP, Brunel, N, and Dieudonné, S. "Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit." Elife 5 (September 19, 2016). Full Text Open Access Copy

De Pittà, M, Brunel, N, and Volterra, A. "Astrocytes: Orchestrating synaptic plasticity?." Neuroscience 323 (May 2016): 43-61. (Review) Full Text

Brunel, N. "Is cortical connectivity optimized for storing information?." Nature Neuroscience 19.5 (May 2016): 749-755. Full Text

Dubreuil, AM, and Brunel, N. "Storing structured sparse memories in a multi-modular cortical network model." Journal of Computational Neuroscience 40.2 (April 2016): 157-175. Full Text

Bouvier, G, Higgins, D, Spolidoro, M, Carrel, D, Mathieu, B, Léna, C, Dieudonné, S, Barbour, B, Brunel, N, and Casado, M. "Burst-Dependent Bidirectional Plasticity in the Cerebellum Is Driven by Presynaptic NMDA Receptors." Cell reports 15.1 (April 2016): 104-116. Full Text

De Pittà, M, and Brunel, N. "Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study." Neural Plasticity 2016 (January 2016): 7607924-null. Full Text

Lim, S, McKee, JL, Woloszyn, L, Amit, Y, Freedman, DJ, Sheinberg, DL, and Brunel, N. "Inferring learning rules from distributions of firing rates in cortical neurons." Nature Neuroscience 18.12 (December 2015): 1804-1810. Full Text Open Access Copy

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