Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5268
Title: Self-organization of a neural network with heterogeneous neurons enhances coherence and stochastic resonance
Authors: Li, X
Zhang, J
Small, M
Keywords: Neural nets
Stochastic processes
Topology
Issue Date: Mar-2009
Publisher: American Institute of Physics
Source: Chaos: an interdisciplinary journal of nonlinear science, Mar. 2009, v. 19, no. 1, 013126, p. 1-6 How to cite?
Journal: Chaos: an interdisciplinary journal of nonlinear science 
Abstract: Most network models for neural behavior assume a predefined network topology and consist of almost identical elements exhibiting little heterogeneity. In this paper, we propose a self-organized network consisting of heterogeneous neurons with different behaviors or degrees of excitability. The synaptic connections evolve according to the spike-timing dependent plasticity mechanism and finally a sparse and active-neuron-dominant structure is observed. That is, strong connections are mainly distributed to the synapses from active neurons to inactive ones. We argue that this self-emergent topology essentially reflects the competition of different neurons and encodes the heterogeneity. This structure is shown to significantly enhance the coherence resonance and stochastic resonance of the entire network, indicating its high efficiency in information processing.
URI: http://hdl.handle.net/10397/5268
ISSN: 1054-1500 (print)
1089-7682 (online)
DOI: 10.1063/1.3076394
Rights: © 2009 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in X. Li, J. Zhang & M. Small, Chaos: an interdisciplinary journal of nonlinear science 19, 013126 (2009) and may be found at http://link.aip.org/link/?cha/19/013126
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Li_Self-organization_Heterogeneous_Neurons.pdf1.52 MBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

12
Last Week
0
Last month
Citations as of Feb 7, 2016

WEB OF SCIENCETM
Citations

15
Citations as of Feb 6, 2016

Page view(s)

135
Checked on Feb 7, 2016

Google ScholarTM
Citations

loading...

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.