Robust timing and motor patterns by taming chaos in recurrent neural networks
Published 2013 View Full Article
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Title
Robust timing and motor patterns by taming chaos in recurrent neural networks
Authors
Keywords
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Journal
NATURE NEUROSCIENCE
Volume 16, Issue 7, Pages 925-933
Publisher
Springer Nature
Online
2013-05-27
DOI
10.1038/nn.3405
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- Generating Coherent Patterns of Activity from Chaotic Neural Networks
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- Dissociating explicit timing from temporal expectation with fMRI
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