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Eric Shea-Brown

Showing results (41-50 of 66) with videos related to

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Neural Computation|January 11, 2022
Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a SwitchDoris Voina, Stefano Recanatesi, Brian Hu, et al.
Arxiv|December 9, 2024
Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networksYuxiu Shao, David Dahmen, Stefano Recanatesi, et al.
Journal of Neural Engineering|April 6, 2007
Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: concepts and lessons from a computational modelXiao-Jiang Feng, Brian Greenwald, Herschel Rabitz, et al.
Neural Networks : the Official Journal of the International Neural Network Society|May 6, 2021
Autoencoder networks extract latent variables and encode these variables in their connectomesMatthew Farrell, Stefano Recanatesi, R Clay Reid, et al.
Neuron|January 23, 2016
Direction-Selective Circuits Shape Noise to Ensure a Precise Population CodeJoel Zylberberg, Jon Cafaro, Maxwell H Turner, et al.
Proceedings of the National Academy of Sciences of the United States of America|December 17, 2021
Cell-type-specific neuromodulation guides synaptic credit assignment in a spiking neural networkYuhan Helena Liu, Stephen Smith, Stefan Mihalas, et al.
Plos Computational Biology|October 23, 2018
Predicting how and when hidden neurons skew measured synaptic interactionsBraden A W Brinkman, Fred Rieke, Eric Shea-Brown, et al.
Plos Computational Biology|October 15, 2016
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?Braden A W Brinkman, Alison I Weber, Fred Rieke, et al.
Arxiv|September 4, 2023
Expressive probabilistic sampling in recurrent neural networksShirui Chen, Linxing Preston Jiang, Rajesh P N Rao, et al.
Journal of Computational Neuroscience|May 8, 2007
Optimal deep brain stimulation of the subthalamic nucleus--a computational studyXiao-Jiang Feng, Eric Shea-Brown, Brian Greenwald, et al.
Pageof 7

Showing results (41-50 of 66) with videos related to

Sort By:
Pageof 7
Neural Computation|January 11, 2022
Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a SwitchDoris Voina, Stefano Recanatesi, Brian Hu, et al.
Arxiv|December 9, 2024
Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networksYuxiu Shao, David Dahmen, Stefano Recanatesi, et al.
Journal of Neural Engineering|April 6, 2007
Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: concepts and lessons from a computational modelXiao-Jiang Feng, Brian Greenwald, Herschel Rabitz, et al.
Neural Networks : the Official Journal of the International Neural Network Society|May 6, 2021
Autoencoder networks extract latent variables and encode these variables in their connectomesMatthew Farrell, Stefano Recanatesi, R Clay Reid, et al.
Neuron|January 23, 2016
Direction-Selective Circuits Shape Noise to Ensure a Precise Population CodeJoel Zylberberg, Jon Cafaro, Maxwell H Turner, et al.
Proceedings of the National Academy of Sciences of the United States of America|December 17, 2021
Cell-type-specific neuromodulation guides synaptic credit assignment in a spiking neural networkYuhan Helena Liu, Stephen Smith, Stefan Mihalas, et al.
Plos Computational Biology|October 23, 2018
Predicting how and when hidden neurons skew measured synaptic interactionsBraden A W Brinkman, Fred Rieke, Eric Shea-Brown, et al.
Plos Computational Biology|October 15, 2016
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?Braden A W Brinkman, Alison I Weber, Fred Rieke, et al.
Arxiv|September 4, 2023
Expressive probabilistic sampling in recurrent neural networksShirui Chen, Linxing Preston Jiang, Rajesh P N Rao, et al.
Journal of Computational Neuroscience|May 8, 2007
Optimal deep brain stimulation of the subthalamic nucleus--a computational studyXiao-Jiang Feng, Eric Shea-Brown, Brian Greenwald, et al.
Pageof 7