Dr. Alexis Dubreuil (Postdoc Sorbonne University)

Vision Institute
Aging in Vision and Action Lab
CNRS – INSERM – Sorbonne University
17, rue Moreau F-75012 Paris, France



Research statement: I use tools from statistical physics and machine learning to understand how computing abilities emerge from the interactions of recurrently connected networks of neurons. This understanding leads to the production of mathematical models that allow, in collaboration with experimental neuroscientists to study the functioning of biological neural networks.

Short-bio: In 2011 I have received the master « theoretical physics of complex systems » from ENS Cachan. I then worked between Paris (Neurophysics lab) and Chicago (Neurobiology department) as a neuroscience PhD student. From 2014 to 2017 I worked as a post-doctoral fellow in the Laboratory of Theoretical Physics of ENS, and from 2018 to 2020 in the cognitive science department of ENS.

Keywords: theoretical neuroscience – machine learning – recurrent neural networks – cortical processing.


CV and Publication List (pdf): [ download ]


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  1. Schuessler F, Dubreuil A, Mastrogiuseppe F, Ostojic S and Barak O (2020) Dynamics of random recurrent networks with correlated low-rank structure. Phys. Rev. Research, 2:013111.
  2. Beiran M, Dubreuil A, Valente A, Mastrogiuseppe F and Ostojic S (2020) Shaping dynamics with multiple populations in low-rank recurrent networks. arXiv, 2007.02062:q-bio.NC.
  3. Schuessler F, Mastrogiuseppe F, Dubreuil A, Ostojic S and Barak O (2020) The interplay between randomness and structure during learning in RNNs. NeurIPS.
  4. Dubreuil A, Valente A, Beiran M, Mastrogiuseppe F and Ostojic S (2020) Complementary roles of dimensionality and population structure in neural computations. bioRxiv.


  1. Dubreuil AM (2019) Short term memory properties of sensory neural architectures. Journal of Computational Neuroscience, 46(3):321?332.
  2. Spalla D, Dubreuil A, Rosay S, Monasson R and Treves A (2019) Can grid cell ensembles represent multiple spaces?. Neural Computation, 31(12):2324-2347.


  1. Wolf S, Dubreuil AM, Bertoni T, Böhm UL, Bormuth V, Candelier R, Karpenko S, Hildebrand DGC, Bianco IH, Monasson R and Debrégeas G (2017) Sensorimotor computation underlying phototaxis in zebrafish. Nature Communications, 8(1).


  1. Dubreuil AM and Brunel N (2016) Storing structured sparse memories in a multi-modular cortical network model. Journal of Computational Neuroscience, 40(2):157?175.
  2. Olive R, Wolf S, Dubreuil A, Bormuth V, Debregeas G and Candelier R (2016) Rheotaxis of larval zebrafish: behavioral study of a multi-sensory process. Frontiers in Systems Neuroscience, 10:14.


  1. Dubreuil AM, Amit Y and Brunel N (2014) Memory capacity of networks with stochastic binary synapses. PLoS computational biology, 10(8):e1003727.