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Digitized neural networks: long-term stability from forgetful neurons

Nature Neuroscience volume 5, pages 709–710 (2002)Cite this article

Understanding how realistic networks integrate input signals over many seconds has eluded neuroscientists for decades. Koulakov and colleagues now propose a computational model to explain how bistable neurons might allow a network to integrate incoming signals.

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Figure 1: Storing values with a marble on a table.

Ivelisse Robles

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Authors and Affiliations

  1. Department of Brain and Cognitive Sciences, University of Rochester, Rochester, 14627, New York, USA

    Alexandre Pouget

  2. Department of Neurobiology, UCLA, Los Angeles, 90095, California, USA

    Peter Latham

Authors
  1. Alexandre Pouget
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  2. Peter Latham
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Pouget, A., Latham, P. Digitized neural networks: long-term stability from forgetful neurons. Nat Neurosci 5, 709–710 (2002). https://doi.org/10.1038/nn0802-709

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