English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A network of coincidence detector neurons with periodic and chaotic dynamics

Watanabe, M., & Aihara, K. (2004). A network of coincidence detector neurons with periodic and chaotic dynamics. IEEE Transactions on Neural Networks, 15(5), 980-986. doi:10.1109/TNN.2004.834797.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D7D9-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-4912-5
Genre: Journal Article

Files

show Files

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Watanabe, M1, Author              
Aihara, K, Author
Affiliations:
1External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: We propose a simple neural network model to understand the dynamics of temporal pulse coding. The model is composed of coincidence detector neurons with uniform synaptic efficacies and random pulse propagation delays. We also assume a global negative feedback mechanism which controls the network activity, leading to a fixed number of neurons firing within a certain time window. Due to this constraint, the network state becomes well defined and the dynamics equivalent to a piecewise nonlinear map. Numerical simulations of the model indicate that the latency of neuronal firing is crucial to the global network dynamics; when the timing of postsynaptic firing is less sensitive to perturbations in timing of presynaptic spikes, the network dynamics become stable and periodic, whereas increased sensitivity leads to instability and chaotic dynamics. Furthermore, we introduce a learning rule which decreases the Lyapunov exponent of an attractor and enlarges the basin of attraction.

Details

show
hide
Language(s):
 Dates: 2004-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1109/TNN.2004.834797
BibTex Citekey: 5802
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE Transactions on Neural Networks
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York, NY : Institute of Electrical and Electronics Engineers
Pages: - Volume / Issue: 15 (5) Sequence Number: - Start / End Page: 980 - 986 Identifier: ISSN: 1045-9227
CoNE: https://pure.mpg.de/cone/journals/resource/954925591430