jZ Lab Publications

Preprints, etc. are listed in Joel’s CV.
For information on citations to these papers, please refer to Google scholar.

J. Zylberberg and B. Strowbridge (2017). Mechanisms of persistent activity in cortical circuits: possible neural substrates for working memory. Annual Review of Neuroscience 40: 603-627.

J. Zylberberg, A. Pouget, P. Latham, E. Shea-Brown (2017). Robust information propagation through noisy neural circuits. PLoS Computational Biology 13: e1005497.

J. Zylberberg*, J. Cafaro*, M.H. Turner*, E. Shea-Brown, and F. Rieke (2016). Direction-selective circuits shape noise to ensure a precise population code . Neuron 89: 369-383. (* denotes equal contribution)

J. Zylberberg, R.A. Hyde, and B.W. Strowbridge (2016). Dynamics of robust pattern separability in the hippocampal dentate gyrus. Hippocampus 29: 623-632.

J. Zylberberg and E. Shea-Brown (2015). Input nonlinearities can shape beyond-pairwise correlations and improve information transmission by neural populations. Physical Review E 92: 062707.

N.A. Cayco Gajic, J. Zylberberg, and E. Shea-Brown (2015). Triplet correlations among similarly tuned cells impact population coding. Frontiers in Computational Neuroscience 9: 57.

Y. Hu, J. Zylberberg, and E. Shea-Brown (2014). The sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes. PLoS Computational Biology 10: e1003469.

J. Zylberberg and M.R. DeWeese (2013). Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images. PLoS Computational Biology 9: e1003182.

P. King, J. Zylberberg, and M.R. DeWeese (2013) Inhibitory Interneurons Decorrelate Excitatory Cells to Drive Sparse Code Formation in a Spiking Model of V1. Journal of Neuroscience 33: 5475.

J. Zylberberg, D. Pfau, and M.R. DeWeese (2012) Dead leaves and the dirty ground: low-level image statistics in transmissive and occlusive imaging environments. Physical Review E 86: 066112.

J. Zylberberg, J.T. Murphy, and M.R. DeWeese (2011). A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields. PLoS Computational Biology 7: e1002250.

J. Zylberberg and M.R. DeWeese (2011). How should prey animals respond to uncertain threats? Frontiers in Computational Neuroscience 5: 20.

G. Zhao, L. Pogosian, A. Silvestri, and J. Zylberberg (2009). Cosmological tests of general relativity with future tomographic surveys. Physical Review Letters 103: 241301.

G. Zhao, L. Pogosian, A. Silvestri, and J. Zylberberg (2009). Searching for modified growth patterns with tomographic surveys. Physical Review D 79: 083513.

C. Vockenhuber et al. (2008). Improvements of the DRAGON recoil separator at ISAC. Nuclear Instruments and Methods in Physics Research B 266: 4167.

J. Zylberberg et al. (2007). Charge-state distributions after radiative capture of helium nuclei by a carbon beam. Nuclear Instruments and Methods in Physics Research B 254: 17.

J. Zylberberg, A.A. Belik, E. Takayama-Muromachi, and Z.-G. Ye (2007). Bismuth Aluminate: A new high-TC lead-free piezo-/ferroelectric. Chemistry of Materials 19: 6385.

J. Bechhoefer, Y. Deng, J. Zylberberg, C. Lei, and Z.-G. Ye (2007). Temperature dependence of the capacitance of a ferroelectric material. American Journal of Physics 75: 1046.

J. Zylberberg and Z.-G. Ye (2006). Improved dielectric properties of bismuth-doped LaAlO3. Journal of Applied Physics 100: 086102.