See also the Google Scholar page.





  • Repeated sequential learning increases memory capacity via effective decorrelation in a recurrent neural network. Tomoki Kurikawa, Omri Barak, and Kunihiko Kaneko
    Phys. Rev. Research 2, 023307 – Published 9 June 2020
  • Dynamics of random recurrent networks with correlated low-rank structure
    F Schuessler, A Dubreuil, F Mastrogiuseppe, S Ostojic, O Barak
    in press, Phys Rev Research. arXiv preprint arXiv:1909.04358
  • Implementing Inductive bias for different navigation tasks through diverse RNN attrractors
    Tie Xu, Omri Barak
    International conference for learning and representations (ICLR) 2020
  • Stable memory with unstable synapses
    L Susman, N Brenner, O Barak
  • One step back, two steps forward: interference and learning in recurrent neural networks
    C Beer, O Barak
    Neural Computation 31 (10), 1985-2003
  • Understanding and Controlling Memory in Recurrent Neural Networks
    D Haviv, A Rivkind, O Barak
    Proceedings of the 36th International Conference on Machine Learning,
  • Ismakov, R., Barak, O., Jeffery, K., & Derdikman, D. (2017). Grid cells encode local positional information. Current Biology.
  • Barak, O. (2017). Recurrent neural networks as versatile tools of neuroscience research. Current Opinion in Neurobiology, 46, 1-6.
  • Rivkind, A., & Barak, O. (2017). Local dynamics in trained recurrent neural networks. Physical Review Letters, 118(25), 258101.
  • Xu, Tie and Omri Barak. “Dynamical timescale explains marginal stability in excitability dynamics” Journal of Neuroscience. Accepted.
  • Barzelay, Oded, Miriam Furst, and Omri Barak. “A New Approach to Model Pitch Perception Using Sparse Coding.” PLOS Computational Biology 13, no. 1 (January 18, 2017): e1005338. doi:10.1371/journal.pcbi.1005338.
  • Rivkind Alexander, Omri Barak. Local dynamics in trained recurrent neural networks.  arXiv:1511.05222 [q-bio.NC]. PDF, Supplement,  Matlab Code
  • Tocker, Gilad, Omri Barak, and Dori Derdikman. “Grid cells correlation structure suggests organized feedforward projections into superficial layers of the medial entorhinal cortex.” Hippocampus (2015).
  • Carnevale F, de Lafuente V, Romo R, Barak O*, Parga N*. Dynamic control of response criterion in premotor cortex during perceptual detection under temporal uncertainty. Neuron, Volume 86, Issue 4, 20 May 2015, Pages 1067–1077. (* co-senior authors) PDF, Preview.
  • Barak O, Tsodyks M. Working models of working memory. Current opinion in Neurobiology. Volume 25, April 2014, Pages 20–24
  • Rigotti M, Barak O, Warden MR, Wang XJ, Daw ND, Miller EK, Fusi S. The importance of mixed selectivity in complex cognitive tasks. Nature 497:585-590 (2013)
  • Barak O, Sussillo D, Romo R, Tsodyks M, Abbott LF. From fixed points to chaos: three models of delayed discrimination. Prog. in Neurobiology.103:214-222. (2013) PDF
  • Barak O, Rigotti M, Fusi S. The sparseness of mixed selectivity neurons controls the generalization-discrimination trade off. Journal of Neuroscience. 33 (9), 3844-3856 PDF
  • Sussillo D*, Barak O*. Opening the Black Box: Low-dimensional dynamics in high-dimensional recurrent neural networks. Neural Computation. 25(3):626-649 (2013) (* equal contribution) PDF  code
  • Barak O, Rigotti M. A simple derivation of a bound on the Perceptron margin using Singular Value Decomposition. Neural Computation. 23(10):1935-1943. (2011) PDF
  • Barak O, Tsodyks M, Romo R. Neuronal population coding of parametric working memory. J Neuroscience, 2010 Jul 14;30(28):9424-30 PDF Supplementary PDF
  • Melamed O, Barak O, Silberberg G, Markram H, Tsodyks M. Slow oscillations in neural networks with facilitating synapses. J Comput Neurosci., 2008 Oct;25(2):308-16. Epub 2008 May 16
  • G. Mongillo*, O. Barak* & M. Tsodyks. Synaptic theory of working memory. Science. 2008 Mar 14;319(5869):1543-6 (* equal contribution)
    PDF SOM perspective
  • O. Barak & M. Tsodyks. Persistent activity in neural networks with dynamic synapses. PLoS Comput Biol. 2007 Feb 23;3(2)
  • Mokeichev A., Okun M., Barak O., Katz Y., Ben-Shahar O., Lampl, I. Stochastic emergence of repeating cortical motifs in spontaneous membrane potential fluctuations in-vivo Neuron 2007 Feb 1;53(3):413-25.
  • O. Barak & M. Tsodyks. Recognition by Variance: Learning Rules for Spatiotemporal Patterns. Neural Computation, Neural Comput. 18(10):2343-58. (2006)
  • Szwed M., Bagdasarian K., Blumenfeld B., Barak O., Derdikman D. and Ahissar E. Responses of trigeminal ganglion neurons to the radial distance of contact during active vibrissal touch. J Neurophysiol. 2006 Feb;95(2):791-802.