Learning multiple variable-speed sequences in striatum via cortical tutoring
Abstract
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.
Article and author information
Author details
Funding
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
- Michael J Frank, Brown University, United States
Version history
- Received: February 16, 2017
- Accepted: May 7, 2017
- Accepted Manuscript published: May 8, 2017 (version 1)
- Version of Record published: May 26, 2017 (version 2)
Copyright
© 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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