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Nature Neuroscience
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June 16, 2015
A neural network that finds a naturalistic solution for the production of muscle activity
David Sussillo, Mark M Churchland, Matthew T Kaufman, et al.
Current Opinion in Neurobiology
|
November 1, 2019
Harnessing behavioral diversity to understand neural computations for cognition
Simon Musall, Anne E Urai, David Sussillo, et al.
Nature
|
November 9, 2013
Context-dependent computation by recurrent dynamics in prefrontal cortex
Valerio Mante, David Sussillo, Krishna V Shenoy, et al.
Neuron
|
January 11, 2023
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks
Brian DePasquale, David Sussillo, L F Abbott, et al.
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|
December 1, 2006
Modular propagation of epileptiform activity: evidence for an inhibitory veto in neocortex
Andrew J Trevelyan, David Sussillo, Brendon O Watson, et al.
Annual Review of Neuroscience
|
July 10, 2020
Computation Through Neural Population Dynamics
Saurabh Vyas, Matthew D Golub, David Sussillo, et al.
Advances in Neural Information Processing Systems
|
August 13, 2020
Universality and individuality in neural dynamics across large populations of recurrent networks
Niru Maheswaranathan, Alex H Williams, Matthew D Golub, et al.
Progress in Neurobiology
|
February 27, 2013
From fixed points to chaos: three models of delayed discrimination
Omri Barak, David Sussillo, Ranulfo Romo, et al.
Advances in Neural Information Processing Systems
|
August 13, 2020
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Niru Maheswaranathan, Alex H Williams, Matthew D Golub, et al.
Nature Communications
|
December 14, 2016
Making brain-machine interfaces robust to future neural variability
David Sussillo, Sergey D Stavisky, Jonathan C Kao, et al.
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of 3
Search research articles
Search
Showing results (11-20 of 30) with videos related to
Sort By:
Page
of 3
Nature Neuroscience
|
June 16, 2015
A neural network that finds a naturalistic solution for the production of muscle activity
David Sussillo, Mark M Churchland, Matthew T Kaufman, et al.
Current Opinion in Neurobiology
|
November 1, 2019
Harnessing behavioral diversity to understand neural computations for cognition
Simon Musall, Anne E Urai, David Sussillo, et al.
Nature
|
November 9, 2013
Context-dependent computation by recurrent dynamics in prefrontal cortex
Valerio Mante, David Sussillo, Krishna V Shenoy, et al.
Neuron
|
January 11, 2023
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks
Brian DePasquale, David Sussillo, L F Abbott, et al.
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|
December 1, 2006
Modular propagation of epileptiform activity: evidence for an inhibitory veto in neocortex
Andrew J Trevelyan, David Sussillo, Brendon O Watson, et al.
Annual Review of Neuroscience
|
July 10, 2020
Computation Through Neural Population Dynamics
Saurabh Vyas, Matthew D Golub, David Sussillo, et al.
Advances in Neural Information Processing Systems
|
August 13, 2020
Universality and individuality in neural dynamics across large populations of recurrent networks
Niru Maheswaranathan, Alex H Williams, Matthew D Golub, et al.
Progress in Neurobiology
|
February 27, 2013
From fixed points to chaos: three models of delayed discrimination
Omri Barak, David Sussillo, Ranulfo Romo, et al.
Advances in Neural Information Processing Systems
|
August 13, 2020
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Niru Maheswaranathan, Alex H Williams, Matthew D Golub, et al.
Nature Communications
|
December 14, 2016
Making brain-machine interfaces robust to future neural variability
David Sussillo, Sergey D Stavisky, Jonathan C Kao, et al.
Page
of 3