Predictability in natural images determines V1 firing rates and 
synchronization: A deep neural network approach

Uran, C.; Peter, A.; Lazar, A.; Barnes, W.; Klon-Lipok, J.; Shapcott, K. A.; Roese, R.; Fries, P.; Singer, W.; Vinck, M.

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Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach

MPS-Authors

Lazar, A.
Neurophysiology Department, Max Planck Institute for Brain Research, Max Planck Society;

Barnes, W.
Neurophysiology Department, Max Planck Institute for Brain Research, Max Planck Society;

Klon-Lipok, J.
Neurophysiology Department, Max Planck Institute for Brain Research, Max Planck Society;

Shapcott, K. A.
Neurophysiology Department, Max Planck Institute for Brain Research, Max Planck Society;

Singer, W.
Neurophysiology Department, Max Planck Institute for Brain Research, Max Planck Society;

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Citation

Uran, C., Peter, A., Lazar, A., Barnes, W., Klon-Lipok, J., Shapcott, K. A., et al. (2020). Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach. bioRxiv.

Cite as: https://hdl.handle.net/21.11116/0000-0007-81CE-F

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