Joel Zylberberg

发表

Using deep learning to reveal the neural code for images in primary visual cortex pdf

William F. Kindel, Elijah D. Christensen, Joel Zylberberg, 2017, ArXiv.

Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells

Joel Zylberberg, Jon Cafaro, Greg Field, 2020, The Journal of Neuroscience.

Training neural networks to mimic the brain improves object recognition performance.

Alona Fyshe, Joel Zylberberg, Callie Federer, 2019 .

Models of the ventral stream that categorize and visualize images

Elijah D. Christensen, Joel Zylberberg, Elijah Christensen, 2020, bioRxiv.

The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes

Yu Hu, Eric Shea-Brown, Joel Zylberberg, 2013, PLoS Comput. Biol..

Joel Zylberberg, Kiersten Ruda, Greg D Field, 2020, Nature communications.

Communicating with noisy signals: lessons learned from the mammalian visual system

Joel Zylberberg, 2014 .

A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data

Eric Shea-Brown, N. Alex Cayco-Gajic, Joel Zylberberg, 2018 .

A deep learning framework for neuroscience

Surya Ganguli, Yoshua Bengio, Claudia Clopath, 2019, Nature Neuroscience.

Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images

Michael Robert DeWeese, Joel Zylberberg, M. DeWeese, 2013, PLoS Comput. Biol..

A self-organizing short-term dynamical memory network

Joel Zylberberg, Callie Federer, 2018 .

A self-organizing short-term dynamical memory network

Joel Zylberberg, Callie Federer, 2018, Neural Networks.

A self-organizing memory network

Joel Zylberberg, Callie Federer, 2017 .

When does recurrent connectivity improve neural population coding?

Eric Shea-Brown, Joel Zylberberg, 2014, BMC Neuroscience.

Untuned but not irrelevant: The role of untuned neurons in sensory information coding

Joel Zylberberg, J. Zylberberg, 2017, bioRxiv.

Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells

Joel Zylberberg, Jon Cafaro, Greg D. Field, 2019, The Journal of Neuroscience.

Inhibitory interneurons enable sparse code formation in a spiking circuit model of V1

Joel Zylberberg, Paul D King, Michael R DeWeese, 2012, BMC Neuroscience.

Input nonlinearities can shape beyond-pairwise correlations and improve information transmission by neural populations.

Eric Shea-Brown, Joel Zylberberg, Eric T. Shea-Brown, 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

Consistency requirements determine optimal noise correlations in neural populations

Eric Shea-Brown, Fred Rieke, Joel Zylberberg, 2013, BMC Neuroscience.

How Should Prey Animals Respond to Uncertain Threats?

Michael Robert DeWeese, Joel Zylberberg, M. DeWeese, 2011, Front. Comput. Neurosci..

Training neural networks to have brain-like representations improves object recognition performance pdf

Alona Fyshe, Joel Zylberberg, Callie Federer, 2019, ArXiv.

Forming cooperative representations via solipsistic synaptic plasticity rules

Joel Zylberberg, Michael R DeWeese, 2011, BMC Neuroscience.

Transformation of population code from dLGN to V1 facilitates linear decoding

Eric Shea-Brown, Ramakrishnan Iyer, Michael Buice, 2019, bioRxiv.

Inhibitory Interneurons Decorrelate Excitatory Cells to Drive Sparse Code Formation in a Spiking Model of V1

Joel Zylberberg, Paul D King, Michael R DeWeese, 2013, The Journal of Neuroscience.

Untuned But Not Irrelevant: A Role For Untuned Neurons In Sensory Information Coding

Joel Zylberberg, 2017 .

Improved object recognition using neural networks trained to mimic the brain's statistical properties

Alona Fyshe, Haoyan Xu, Joel Zylberberg, 2020, Neural Networks.

Robust information propagation through noisy neural circuits

Peter E. Latham, Alexandre Pouget, Eric Shea-Brown, 2016, PLoS Comput. Biol..

The language of the brain: real-world neural population codes

Joel Zylberberg, J Andrew Pruszynski, J. A. Pruszynski, 2019, Current Opinion in Neurobiology.

Triplet correlations among similarly tuned cells impact population coding

Eric Shea-Brown, Joel Zylberberg, Eric T. Shea-Brown, 2015, Front. Comput. Neurosci..

Dead leaves and the dirty ground: low-level image statistics in transmissive and occlusive imaging environments.

David Pfau, Joel Zylberberg, Michael Robert Deweese, 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

A Sparse Coding Model with Synaptically Local Plasticity and Spiking Neurons Can Account for the Diverse Shapes of V1 Simple Cell Receptive Fields

Michael Robert DeWeese, Joel Zylberberg, Jason Timothy Murphy, 2011, PLoS Comput. Biol..

How efficient coding of binocular disparity statistics in the primary visual cortex influences eye rotation strategy

Sarah E Marzen, Joel Zylberberg, Sarah E. Marzen, 2013, BMC Neuroscience.

Joel Zylberberg, Greg D. Field, Kiersten Ruda, 2019, Nature Communications.

Add HOC?: dendritic nonlinearities shape higher-than-pairwise correlations and improve coding in noisy (spiking) neural populations

Eric Shea-Brown, Joel Zylberberg, 2013 .

A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data

Eric Shea-Brown, N. Alex Cayco-Gajic, Joel Zylberberg, 2018, bioRxiv.

Impact of triplet correlations on neural population codes

Eric Shea-Brown, Joel Zylberberg, J. Zylberberg, 2014, 1412.0363.

From scenes to spikes: understanding vision from the outside in

Joel Zylberberg, 2012 .

Dynamics of robust pattern separability in the hippocampal dentate gyrus

Joel Zylberberg, J. Zylberberg, B. Strowbridge, 2016, Hippocampus.