Waddington, A, Appleby, PA, de Kamps, M et al. (1 more author) (2012) Triphasic Spike-Timing-Dependent Plasticity Organizes Networks to Produce Robust Sequences of Neural Activity. Frontiers in Computational Neuroscience, 6. ISSN 1662-5188
Abstract
Synfire chains have long been suggested to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been suggested that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random-walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2012, Frontiers. Reproduced in accordance with the publisher's self-archiving policy. This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission. |
Keywords: | activity dependentplasticity; computational model; microcircuits; networkdevelopment; random walk; songbird; synfire chains; zebra finch |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Jan 2014 12:23 |
Last Modified: | 15 Sep 2014 02:26 |
Published Version: | http://dx.doi.org/10.3389/fncom.2012.00088 |
Status: | Published |
Publisher: | Frontiers |
Identification Number: | 10.3389/fncom.2012.00088 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:77375 |