Joel Zylberberg, Ph.D.

Affiliations: 
Physiology and Biophysics University of Colorado School of Medicine, Aurora, CO, United States 
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"Joel Zylberberg"
Mean distance: 15.07 (cluster 17)
 
SNBCP
Cross-listing: Physics Tree

Parents

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Michael R. DeWeese grad student 2012 York University
 (From scenes to spikes: Understanding vision from the outside in.)
Eric Shea-Brown post-doc 2012-2015 University of Washington
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Publications

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Idrees S, Manookin MB, Rieke F, et al. (2024) Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation. Nature Communications. 15: 5957
Tang D, Zylberberg J, Jia X, et al. (2024) Stimulus type shapes the topology of cellular functional networks in mouse visual cortex. Nature Communications. 15: 5753
Tang D, Zylberberg J, Jia X, et al. (2023) Stimulus-dependent functional network topology in mouse visual cortex. Biorxiv : the Preprint Server For Biology
Ruda K, Zylberberg J, Field GD. (2020) Ignoring correlated activity causes a failure of retinal population codes. Nature Communications. 11: 4605
Federer C, Xu H, Fyshe A, et al. (2020) 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. 131: 103-114
Cafaro J, Zylberberg J, Field G. (2020) Global motion processing by populations of direction-selective retinal ganglion cells. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Pruszynski JA, Zylberberg J. (2019) The language of the brain: real-world neural population codes. Current Opinion in Neurobiology. 58: 30-36
Cayco-Gajic NA, Zylberberg J, Shea-Brown E. (2018) A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data. Entropy (Basel, Switzerland). 20
Cayco-Gajic N, Zylberberg J, Shea-Brown E. (2018) A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data Entropy. 20: 489
Zylberberg J, Strowbridge BW. (2017) Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory. Annual Review of Neuroscience. 40: 603-627
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