Fast and flexible sequence induction in spiking neural networks via rapid excitability changes
Abstract
Cognitive flexibility likely depends on modulation of the dynamics underlying how biological neural networks process information. While dynamics can be reshaped by gradually modifying connectivity, less is known about mechanisms operating on faster timescales. A compelling entrypoint to this problem is the observation that exploratory behaviors can rapidly cause selective hippocampal sequences to 'replay' during rest. Using a spiking network model, we asked whether simplified replay could arise from three biological components: fixed recurrent connectivity; stochastic 'gating' inputs; and rapid gating input scaling via long-term potentiation of intrinsic excitability (LTP-IE). Indeed, these enabled both forward and reverse replay of recent sensorimotor-evoked sequences, despite unchanged recurrent weights. LTP-IE 'tags' specific neurons with increased spiking probability under gating input, and ordering is reconstructed from recurrent connectivity. We further show how LTP-IE can implement temporary stimulus-response mappings. This elucidates a novel combination of mechanisms that might play a role in rapid cognitive flexibility.
Article and author information
Author details
Funding
National Institutes of Health (R01DC013693)
- Adrienne L Fairhall
Simons Foundation (Collaboration for the Global Brain)
- Adrienne L Fairhall
University of Washington (Computational Neuroscience Training Grant)
- Rich Pang
Washington Research Foundation (UW Institute for Neuroengineering)
- Adrienne L Fairhall
National Institutes of Health (NIH) (R01NS104925)
- Adrienne L Fairhall
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Pang & Fairhall
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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