Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity
- 1School of Computing, University of Leeds, Leeds, UK
- 2Institute of Systems and Membrane Biology, University of Leeds, Leeds, UK
Synfire chains have long been proposed 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 argued 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.
Keywords: activity dependent plasticity, computational model, microcircuits, network development, random walk, songbird, synfire chains, zebra finch
Citation: Waddington A, Appleby PA, De Kamps M and Cohen N (2012) Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity. Front. Comput. Neurosci. 6:88. doi: 10.3389/fncom.2012.00088
Received: 30 January 2012; Accepted: 05 October 2012;
Published online: 12 November 2012.
Reviewed by: Germán Mato
, Centro Atomico Bariloche, Argentina Dezhe Jin
, The Pennsylvania State University, USA
Copyright © 2012 Waddington, Appleby, De Kamps and Cohen. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
*Correspondence: Netta Cohen, School of Computing, University of Leeds, Leeds LS2 9JT, UK.
Institute of Systems and Membrane Biology, University of Leeds, Leeds LS2 9JT, UK. e-mail: firstname.lastname@example.org
†Present address: Peter A. Appleby, Department of Computer Science, University of Sheffield, Sheffield, UK