1. Neuroscience
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Learning multiple variable-speed sequences in striatum via cortical tutoring

  1. James M Murray  Is a corresponding author
  2. G Sean Escola
  1. Columbia University, United States
Research Article
  • Cited 11
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Cite this article as: eLife 2017;6:e26084 doi: 10.7554/eLife.26084


Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.

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Author details

  1. James M Murray

    Center for Theoretical Neuroscience, Columbia University, New York City, United States
    For correspondence
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3706-4895
  2. G Sean Escola

    Center for Theoretical Neuroscience, Columbia University, New York City, United States
    Competing interests
    The authors declare that no competing interests exist.


National Institutes of Health (NIH DP5 OD019897)

  • G Sean Escola

Leon Levy Foundation (Fellowship)

  • G Sean Escola

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Michael J Frank, Brown University, United States

Publication history

  1. Received: February 16, 2017
  2. Accepted: May 7, 2017
  3. Accepted Manuscript published: May 8, 2017 (version 1)
  4. Version of Record published: May 26, 2017 (version 2)


© 2017, Murray & Escola

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


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