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Fast and flexible sequence induction in spiking neural networks via rapid excitability changes
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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538377/ https://www.ncbi.nlm.nih.gov/pubmed/31081753 http://dx.doi.org/10.7554/eLife.44324 |
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author | Pang, Rich Fairhall, Adrienne L |
author_facet | Pang, Rich Fairhall, Adrienne L |
author_sort | Pang, Rich |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6538377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-65383772019-05-29 Fast and flexible sequence induction in spiking neural networks via rapid excitability changes Pang, Rich Fairhall, Adrienne L eLife Computational and Systems Biology 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. eLife Sciences Publications, Ltd 2019-05-13 /pmc/articles/PMC6538377/ /pubmed/31081753 http://dx.doi.org/10.7554/eLife.44324 Text en © 2019, Pang and Fairhall http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Pang, Rich Fairhall, Adrienne L Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title | Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title_full | Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title_fullStr | Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title_full_unstemmed | Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title_short | Fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
title_sort | fast and flexible sequence induction in spiking neural networks via rapid excitability changes |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538377/ https://www.ncbi.nlm.nih.gov/pubmed/31081753 http://dx.doi.org/10.7554/eLife.44324 |
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