Publications

1. Idrees S, Manookin MB, Rieke F, Field GD, Zylberberg J. Author Correction: Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation.. Nature communications, 2025.
2. Heyman A, Zylberberg J. Fine Granularity Is Critical for Intelligent Neural Network Pruning.. Neural computation, 2024.
3. Idrees S, Manookin MB, Rieke F, Field GD, Zylberberg J. Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation.. Nature communications, 2024.
4. Tang D, Zylberberg J, Jia X, Choi H. Stimulus type shapes the topology of cellular functional networks in mouse visual cortex.. Nature communications, 2024.
5. Gillon CJ, Pina JE, Lecoq JA, Ahmed R, Billeh YN, Caldejon S, Groblewski P, Henley TM, Kato I, Lee E, Luviano J, Mace K, Nayan C, Nguyen TV, North K, Perkins J, Seid S, Valley MT, Williford A, Bengio Y, Lillicrap TP, Richards BA, Zylberberg J. Responses to Pattern-Violating Visual Stimuli Evolve Differently Over Days in Somata and Distal Apical Dendrites.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2024.
6. Tang D, Zylberberg J, Jia X, Choi H. Stimulus-dependent functional network topology in mouse visual cortex.. bioRxiv : the preprint server for biology, 2023.
7. Gillon CJ, Lecoq JA, Pina JE, Ahmed R, Billeh YN, Caldejon S, Groblewski P, Henley TM, Kato I, Lee E, Luviano J, Mace K, Nayan C, Nguyen TV, North K, Perkins J, Seid S, Valley MT, Williford A, Bengio Y, Lillicrap TP, Zylberberg J, Richards BA. Responses of pyramidal cell somata and apical dendrites in mouse visual cortex over multiple days.. Scientific data, 2023.
8. Cayco-Gajic NA, Zylberberg J. Good decisions require more than information.. Nature neuroscience, 2021.
9. Jones S, Zylberberg J, Schoppa N. Cellular and Synaptic Mechanisms That Differentiate Mitral Cells and Superficial Tufted Cells Into Parallel Output Channels in the Olfactory Bulb.. Frontiers in cellular neuroscience, 2020.
10. Ruda K, Zylberberg J, Field GD. Ignoring correlated activity causes a failure of retinal population codes.. Nature communications, 2020.
11. Federer C, Xu H, Fyshe A, Zylberberg J. Improved object recognition using neural networks trained to mimic the brain's statistical properties.. Neural networks : the official journal of the International Neural Network Society, 2020.
12. Cafaro J, Zylberberg J, Field GD. Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2020.
13. Richards BA, Lillicrap TP, Beaudoin P, Bengio Y, Bogacz R, Christensen A, Clopath C, Costa RP, de Berker A, Ganguli S, Gillon CJ, Hafner D, Kepecs A, Kriegeskorte N, Latham P, Lindsay GW, Miller KD, Naud R, Pack CC, Poirazi P, Roelfsema P, Sacramento J, Saxe A, Scellier B, Schapiro AC, Senn W, Wayne G, Yamins D, Zenke F, Zylberberg J, Therien D, Kording KP. A deep learning framework for neuroscience.. Nature neuroscience, 2019.
14. Pruszynski JA, Zylberberg J. The language of the brain: real-world neural population codes.. Current opinion in neurobiology, 2019.
15. Lintz MJ, Essig J, Zylberberg J, Felsen G. Spatial representations in the superior colliculus are modulated by competition among targets.. Neuroscience, 2019.
16. Kindel WF, Christensen ED, Zylberberg J. Using deep learning to probe the neural code for images in primary visual cortex.. Journal of vision, 2019.
17. Christensen E, Abosch A, Thompson JA, Zylberberg J. Inferring sleep stage from local field potentials recorded in the subthalamic nucleus of Parkinson's patients.. Journal of sleep research, 2018.
18. Cayco-Gajic NA, Zylberberg J, Shea-Brown E. A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data.. Entropy (Basel, Switzerland), 2018.
19. Federer C, Zylberberg J. A self-organizing short-term dynamical memory network.. Neural networks : the official journal of the International Neural Network Society, 2018.
20. Zylberberg J, Strowbridge BW. Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory.. Annual review of neuroscience, 2017.
21. Zylberberg J, Pouget A, Latham PE, Shea-Brown E. Robust information propagation through noisy neural circuits.. PLoS computational biology, 2017.
22. Zylberberg J, Cafaro J, Turner MH, Shea-Brown E, Rieke F. Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code.. Neuron, 2016.
23. Zylberberg J, Shea-Brown E. Input nonlinearities can shape beyond-pairwise correlations and improve information transmission by neural populations.. Physical review. E, Statistical, nonlinear, and soft matter physics, 2015.
24. Zylberberg J, Hyde RA, Strowbridge BW. Dynamics of robust pattern separability in the hippocampal dentate gyrus.. Hippocampus, 2015.
25. Cayco-Gajic NA, Zylberberg J, Shea-Brown E. Triplet correlations among similarly tuned cells impact population coding.. Frontiers in computational neuroscience, 2015.
26. Hu Y, Zylberberg J, Shea-Brown E. The sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes.. PLoS computational biology, 2014.
27. Zylberberg J, DeWeese MR. Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images.. PLoS computational biology, 2013.
28. King PD, Zylberberg J, DeWeese MR. Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1.. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2013.
29. Zylberberg J, Pfau D, Deweese MR. Dead leaves and the dirty ground: low-level image statistics in transmissive and occlusive imaging environments.. Physical review. E, Statistical, nonlinear, and soft matter physics, 2012.
30. Zylberberg J, Murphy JT, DeWeese MR. 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, 2011.
31. Zylberberg J, Deweese MR. How should prey animals respond to uncertain threats?. Frontiers in computational neuroscience, 2011.
32. Zhao GB, Pogosian L, Silvestri A, Zylberberg J. Cosmological tests of general relativity with future tomographic surveys.. Physical review letters, 2009.